2009-11-21T06:28:19Zhttp://open-archive.highwire.org/handler

oai:open-archive.highwire.org:bioinfo:12/2/1092006-11-07HighWireOUPbioinfo:12:2

Motif identification neural design for rapid and sensitive protein family search Wu, Cathy H. Zhao, Sheng Chen, Hsi-Lien Lo, Chin-Ju McLarty, Jerry ORIGINAL PAPERS A new method, the motif identification neural design (MOTIFIND), has been developed for rapid and sensitive protein family identification. The method is an extension of our previous gene classification artificial neural system and employs new designs to enhance the detection of distant relationships. The new designs include an n-gram term weighting algorithm for extracting local motif patterns, an enhanced n-gram method for extracting residues of long-range correlation, and integrated neural networks for combining global and motif sequence information. The system has been tested and compared with several existing methods using three protein families, the cytochrome c, cytochrome b and flavodoxin. Overall it achieves 100% sensitivity and > 99.6% specificity, an accuracy comparable to BLAST, but at a speed of ∼20 times faster. The system is much more robust than the PROSITE search which is based on simple signature patterns. MOTIFIND also compares favorably with BLIMPS, the Hidden Markov Model and PROFILESEARCH in detecting fragmentary sequences lacking complete motif regions and in detecting distant relationships, especially for members of under-represented subgroups within a family. MOTIFIND may be generally applicable to other proteins and has the potential to become a full-scale database search and sequence analysis tool. Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/109 http://dx.doi.org/10.1093/bioinformatics/12.2.109 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/1192006-11-07HighWireOUPbioinfo:12:2

Object-oriented sequence analysis: SCL-a C+ + class library Vahrson, Wolfgang Hermann, Klaus Kleffe, Jürgen Wittig, Burghardt ORIGINAL PAPERS SCL (Sequence Class Library) is a class library written in the C+ + programming language. Designed using object-oriented programming principles, SCL consists of classes of objects performing tasks typically needed for analyzing DNA or protein sequences. Among them are very flexible sequence classes, classes accessing databases in various formats, classes managing collections of sequences, as well as classes performing higher-level tasks like calculating a pairwise sequence alignment. SCL also includes classes that provide general programming support, like a dynamically growing array, sets, matrices, strings, classes performing file input/output, and utilities for error handling. By providing these components, SCL fosters an explorative programming style: experimenting with algorithms and alternative implementations is encouraged rather than punished. A description of SCL's overall structure as well as an overview of its classes is given. Important aspects of the work with SCL are discussed in the context of a sample program. Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/119 http://dx.doi.org/10.1093/bioinformatics/12.2.119 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/1292006-11-07HighWireOUPbioinfo:12:2

FastAlert-an automatic search system to alert about new entries in biological sequence databanks Eggenberger, F. Redaschi, N. Doelz, R. ORIGINAL PAPERS This paper describes a new tool enabling awareness of new sequence databank entries of interest. The Fast Alert system relieves the researcher from the burden of repeating FASTA searches in order to keep up with the rapidly growing amount of information found in biological sequence databanks. The query sequence can be submitted from any computer connected to the Internet. Upon registration, the databank, including the updates, is scanned at periodic intervals with the sequence provided. The results, so-called FastAlert reports, are delivered via electronic mail. The reports contain the FASTA best-scores list and the similarity statistics for each entry listed. Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/129 http://dx.doi.org/10.1093/bioinformatics/12.2.129 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/1352006-11-07HighWireOUPbioinfo:12:2

Using substitution probabilities to improve position-specific scoring matrices Henikoff, Jorja G. Henikoff, Steven ORIGINAL PAPERS Each column of amino acids in a multiple alignment of protein sequences can be represented as a vector of 20 amino acid counts. For alignment and searching applications, the count vector is an imperfect representation of a position, because the observed sequences are an incomplete sample of the full set of related sequences. One general solution to this problem is to model unobserved sequences by adding artificial ‘pseudo-counts’ to the observed counts. We introduce a simple method for computing pseudo-counts that combines the diversity observed in each alignment position with amino acid substitution probabilities. In extensive empirical tests, this position-based method out-performed other pseudo-count methods and was a substantial improvement over the traditional average score method used for constructing profiles. Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/135 http://dx.doi.org/10.1093/bioinformatics/12.2.135 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/1452006-11-07HighWireOUPbioinfo:12:2

An extensible network query unification system for biological databases Jamison, D.Curtis Mills, Brad Schatz, Bruce ORIGINAL PAPERS Database federation enables biological researchers to utilize resources more effectively, creating an environment in which the researcher can query multiple data sources without spending time learning new query mechanisms or issuing redundant queries which need to be integrated. Several mechanisms exist to federate databases. The ENQUire system is a network database federation system which uses a World-Wide-Web (WWW) interface to connect the users to various databases. Generic queries entered via a query generator form are sent in parallel to multiple databases, and the results are presented to the user in a unified format. All forms building, query generation, and results translation is done on the fly, and individual database translation modules can be added dynamically. ENQUire is a flexible answer to the problems of database federation on the WWW. Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/145 http://dx.doi.org/10.1093/bioinformatics/12.2.145 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/1512006-11-07HighWireOUPbioinfo:12:2

A Tcl-based SRS v. 4 Interface Schaftenaar, Gijs Cuelenaere, Koen Noordik, Jan H. Etzold, Thure APPLICATIONS NOTES A new SRS (Sequence Retrieval System) user interface has been developed for SRS v. 4. Key features are the support of simple character-oriented (ASCII, VT100) terminals by coding in Tcl augmented by some dedicated Curses calls, support of graphics terminals in an X-Windows version by using the Tk extension to Tcl, and support of a client/server environment by using the TDP extension to Tcl. The Sequence Retrieval System (SRS) is a powerful tool for the fast extraction of information from flat file libraries (Etzold and Argos, 1993) and has rapidly established itself as a major research instrument for the bio-informatics community. Internally the system employs a query language, which is user accessible through either a command-line user interface, ‘getz’, or a more user friendly, character-oriented window interface. For SRS versions up to release v. 3, this window interface supported VT100-compatible terminals. Because of major changes in the underlying SRS libraries, the v. 3 interface became fully incompatible with the most recent version of SRS (v. 4.x). Thus the many users with only a simple terminal/terminal emulator connection were either deprived of access to SRS, or were forced to use the ASCII WWW client LYNX. This prompted us to develop a character-oriented SRS v. 4 window interface with the look and feel of its SRS v. 3.1 predecessor and coded to be as library independent as possible to maintain compatibility with future SRS releases. In addition, some ‘extensions’ were coded to widen the applicability to graphics terminals and to a client/server environment. At the time of preparation of this paper, the SRS interface described had been implemented in one form or another on most EMBnet nodes and on all the platforms given in Table II. The code has been stored at the EMBL in Heidelberg, where it will be available, with installation instructions and scripts, as part of the SRS distribution. Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/151 http://dx.doi.org/10.1093/bioinformatics/12.2.151 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/1572006-11-07HighWireOUPbioinfo:12:2

SIGNAL SCAN 4.0: additional databases and sequence formats Prestridge, Dan S. APPLICATIONS NOTES SIGNAL SCAN is a program that utilizes transcription factor databases to find potential transcription factor binding sites in DNA sequences. The program is now in its fourth version. SIGNAL SCAN 4 now includes, in addition to the Transcription Factor Database, the TRANSFAC and IMD (Information Matrix Database) databases. In addition, it now accepts GCG and FASTA formatted DNA sequences in addition to Staden formatted sequences. SIGNAL SCAN is available for both IBM-compatible PC and Unix workstation platforms. Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/157 http://dx.doi.org/10.1093/bioinformatics/12.2.157 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/812006-11-07HighWireOUPbioinfo:12:2

An algorithm to analyse the hydrolysis pathway of peptides and proteins by sequence analyses of unfractionated digestion mixtures Caporale, Carlo Sepe, Ciro Caruso, Carla Garzillo, Anna Maria V. Buonocore, Vincenzo ORIGINAL PAPERS We have designed and implemented on a personal computer a program for identifying and quantifying the fragments present in a peptide mixture obtained by hydrolysing a polypeptide of known sequence using digesting agents. The qualitative data utilized by the main algorithm consist of the target sequence of the intact molecule and the amino acid residues identified at each step of the automatic sequence analysis of the unfractionated digestion mixture. In this way, the sequence of each fragment present in the mixture is quickly reconstructed. Furthermore, if the quantitative data of the amino acid residues identified at each step of the sequence analysis are utilized, the program will correlate the sequence of each fragment to its amount. We furnish an example of the application intended for the rapid identification and characterization of the extracellular proteinases produced by a basidiomycete fungus, utilizing the bovine insulin β3-chain as target substrate. A variety of uses for the method are discussed. Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/81 http://dx.doi.org/10.1093/bioinformatics/12.2.81 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/892006-11-07HighWireOUPbioinfo:12:2

XFINGER: A tool for searching and visualising protein fingerprints and patterns Perkins, D.N. Attwood, T.K. ORIGINAL PAPERS A tool for searching pattern and fingerprint databases is described. Fingerprints are groups of motifs excised from conserved regions of sequence alignments and used for iterative database scanning. The constituent motifs are thus encoded as small alignments in which sequence information is maximised with each database pass; they therefore differ from regular-expression patterns, in which alignments are reduced to single consensus sequences. Different database formats have evolved to store these disparate types of information, namely the PROSITE dictionary of patterns and the PRINTS fingerprint database, but programs have not been available with the flexibility to search them both. We have developed a facility to do this: the system allows query sequences to be scanned against either PROSITE, the full PRINTS database, or against individual fingerprints. The results of fingerprint searches are displayed simultaneously in both text and graphical windows to render them more tangible to the user. Where structural coordinates are available, identified motifs may be visualised in a 3D context. The program runs on Silicon Graphics machines using GL graphics libraries and on machines with X servers supporting the PEX extension: its use is illustrated here by depicting the location of low-density lipoprotein-binding (LDL) motifs and leucine-rich repeats in a mosaic G-protein-coupled receptor (GPCR). Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/89 http://dx.doi.org/10.1093/bioinformatics/12.2.89 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/952006-11-07HighWireOUPbioinfo:12:2

Hidden Markov models for sequence analysis: extension and analysis of the basic method Hughey, Richard Krogh, Anders ORIGINAL PAPERS Hidden Markov models (HMMs) are a highly effective means of modeling a family of unaligned sequences or a common motif within a set of unaligned sequences. The trained HMM can then be used for discrimination or multiple alignment. The basic mathematical description of an HMM and its expectation-maximization training procedure is relatively straightforward. In this paper, we review the mathematical extensions and heuristics that move the method from the theoretical to the practical. We then experimentally analyze the effectiveness of model regularization, dynamic model modification and optimization strategies. Finally it is demonstrated on the SH2 domain how a domain can be found from unaligned sequences using a special model type. The experimental work was completed with the aid of the Sequence Alignment and Modeling software suite. Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/95 http://dx.doi.org/10.1093/bioinformatics/12.2.95 en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/119b1996-04-01HighWireOUPbioinfo:12:2

Object-oriented sequence analysis: SCL--a C++ class library Vahrson, W Hermann, K Kleffe, J Wittig, B ARTICLES Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/119b en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/135b1996-04-01HighWireOUPbioinfo:12:2

Using substitution probabilities to improve position-specific scoring matrices Henikoff, JG Henikoff, S ARTICLES Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/135b en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/151b1996-04-01HighWireOUPbioinfo:12:2

A Tcl-based SRS v. 4 interface Schaftenaar, G Cuelenaere, K Noordik, JH Etzold, T ARTICLES Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/151b en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:12/2/157b1996-04-01HighWireOUPbioinfo:12:2

SIGNAL SCAN 4.0: additional databases and sequence formats Prestridge, DS ARTICLES Oxford University Press 1996-04-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/12/2/157b en Copyright (C) 1996, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/2292006-11-07HighWireOUPbioinfo:11:3

An algorithm for analysing probed partial digestion experiments Karp, Richard M. Newberg, Lee A. ORIGINAL PAPERS A partial digestion of DNA (e.g. cosmid, Lambda, YAC, chromosome) is performed and the lengths of thoses fragments which hybridize to a labeled probe are measured using gel electrophoresis. We give an efficient algorithm that takes as input this experimental data and proposes one or more candidate solutions. Each solution designates the location of each restriction site and spec the endpoints of each fragment. (Further experiments can then be designed to select the correct solution from this small set of candidates.) The algorithm works well even when the experiment gives inexact values for the lengths. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/229 http://dx.doi.org/10.1093/bioinformatics/11.3.229 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/2372006-11-07HighWireOUPbioinfo:11:3

A new data model for biological classification Jung, Sungwon Perkins, Stephen Zhong, Yang Pramanik, Sakti Beaman, John ORIGINAL PAPERS In the domain of biological classification, class are performed hierarchically. There are no standard classifications which are unanimously accepted by the community of each domain; many different interacting views of classification exist about the same data, and the discovery of new data results in changes to the existing class. Even a single individual may change his or her own classification of a particular group. Since multiple class views interact, they are semantically related. It is d to model this kind of dynamically evolving and semantically interacting classification system using traditional data models, which lack the structural flexibility necessary to support dynamic views of hierarchic classification and cannot properly capture the history of these complex interactions. We have developed a new data model which is suitable for supporting semantically interacting dynamic views of hierarchic biological classification on the basis of our new data model we have developed a prototype database system called HICLAS (Hierarchical CLAssification System); its domain is plant taxonomy. HICLAS is available through the Internet and an X-window interface has been implemented to support queries to classification data. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/237 http://dx.doi.org/10.1093/bioinformatics/11.3.237 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/2472006-11-07HighWireOUPbioinfo:11:3

Comparative analysis by independent contrasts (CAIC): an Apple Macintosh application for analysing comparative data Purvis, Andy Rambaut, Andrew ORIGINAL PAPERS CAIC is an application for the Apple Macintosh which allows the valid analysis of comparative (multi-species) data sets that include continuous variables. Comparison among species is the most common technique for testing hypotheses of how organisms are adapted to their environments, but standard statistical tests like regression should not be used with species data. Such tests assume independence of data points, but related species often share traits by common descent rather than through independent adaptation. CAIC uses a phylogeny of the species in the data set to partition the variance among species into independent comparisons (technically, linear contrasts), each comparison being made at a d node in the phylogeny. There are two partitioning procedures—one used when all variables are continuous, the other when one variable is discrete. The resulting comparisons can be analysed validly in standard statistical packages to lest hypotheses about correlated evolution among trails, to estimate parameters such as allometric exponents, and to compare rates of evolution. Previous versions of the package have already been used widely; this version is simpler to use and works on a wider range of machines. The package and manual are freely available by anonymous ftp or from the authors. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/247 http://dx.doi.org/10.1093/bioinformatics/11.3.247 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/2532006-11-07HighWireOUPbioinfo:11:3

LGANN: a parallel system combining a local genetic algorithm and neural networks for the prediction of secondary structure of proteins Vivarelli, Francesco Giusti, Giuliano Villani, Marco Campanini, Renato Fariselli, Piero Compiani, Mario Casadio, Rita ORIGINAL PAPERS In this work we describe a parallel system consisting of feed-forward neural networks supervised by a local genetic algorithm. The system is implemented in a transputer architecture and is used to predict the secondary structures of globular proteins. This method allows a wide search in the parameter space of the neural networks and the determination of their optimal topology for the predictive task. Different neural network topologies are selected by the genetic algorithm on the basis of minimal values of mean square errors on the testing set. When the α-helix, β-strand and random coil motifs of secondary structures are discriminated, the maximal efficiency obtained is 0.62, with correlation coefficients of 0.35, 0.31 and 0.37 respectively. This level of accuracy is similar to that previously attained by means of neural networks without hidden layers and using single protein sequences as input. The results validate the neural network topologies used for the prediction of protein secondary structures and highlight the relevance of the input information in determining the limit of their performance. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/253 http://dx.doi.org/10.1093/bioinformatics/11.3.253 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/2612006-11-07HighWireOUPbioinfo:11:3

Automat and BLAST: comparison of two protein sequence similarity search programs Cantalloube, H. Labesse, G. Chomilier, J. Nahum, C. Cho, Y.Y. Chams, V. Achour, A. Lachgar, A. Mbika, J.P. Issing, W. Mornon, J.P. Bizzini, B. Zagury, D. Zagury, J.-F. ORIGINAL PAPERS Since the early 1980s, protein/DNA sequence similarity search has become of major importance to biologists, and the need for fast and efficient tools grows with the size of databanks. Two programs use the strategy of finite state deterministic automatons to accomplish these searches. One of these two is BLAST, which is now widely used, and the other Automat, which has just been published. The differences and similarities in their basic principles, their use and their performances are analysed in this paper in order to allow optimal use of these important softwares. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/261 http://dx.doi.org/10.1093/bioinformatics/11.3.261 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/2732006-11-07HighWireOUPbioinfo:11:3

A rapid access motif database (RAMdb) with a search algorithm for the retrieval patterns in nucleic acids or protein databanks Fondrat, Christian Dessen, Phillippe ORIGINAL PAPERS We present here a codification structure, entirely interfaced with the main packages for biomolecule database management, associated with a new search algorithm to retrieve quickly a sequence in a database. This system is derived from a method previously proposed for homology search in databanks with a preprocessed codification of an entire database in which all the overlapping subsequences of a specific length in a sequence were converted into a code and stored in a hash-coding file. This new algorithm is designed for an improved use of the codification. It is based on the recognition of the rarest strings which characterize the query sequence and the intersection of sorted lists read in the codification structure. The system is applicable to both nucleic acid and protein sequences and is used to find patterns in databanks or large sets of sequences. A few examples of applications are given. In addition, the comparison of our method with existing ones shows that this new approach speeds up the search for query patterns in large data sets. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/273 http://dx.doi.org/10.1093/bioinformatics/11.3.273 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/2812006-11-07HighWireOUPbioinfo:11:3

NUPARM and NUCGEN: software for analysis and generation of sequence dependent nucleic acid structures Bansal, M. Bhattacharyya, D. Ravi, B. ORIGINAL PAPERS Software packages NUFARM and NUCGEN, are described, which can be used to understand sequence directed structural variations in nucleic acids, by analysis and generation of non-uniform structures. A set of local inter basepair parameters (viz, tilt, roll, twist, shift, slide and rise) have been defined, which use geometry and coordinates of two successive basepairs only and can be used to generate polymeric structures with varying geometries for each of the 16 possible dinucleotide steps. Intra basepair parameters, propeller, buckle, opening and the C6…C8 distance can also be varied, if required, while the sugar phosphate backbone atoms are fixed in some standard conformation in each of the nucleotides. NUPARM can be used to analyse both DNA and RNA structures, with single as well as double stranded helices. The NUCGEN software generates double helical models with the backbone fixed in B-form DNA, but with appropriate modifications in the input data, it can also generate A-form DNA and RNA duplex structures. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/281 http://dx.doi.org/10.1093/bioinformatics/11.3.281 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/2892006-11-07HighWireOUPbioinfo:11:3

NUVIEW: software for display and interactive manipulation of nucleic acid models Bansal, M. Bhattacharyya, D. Vijaylakshmi, S. ORIGINAL PAPERS The NUVIEW software package allows skeletal models of any double helical nucleic acid molecule to be displayed on a graphics monitor and to apply various rotations, translations and scaling transformations interactively, through the keyboard. The skeletal model is generated by connecting any pair of representative points, one from each of the bases in the basepair. In addition to the above mentioned manipulations, the base residues can be identified by using a locator and the distance between any pair of residues can be obtained. A sequence based color coded display allows easy identification of sequence repeats, such as runs of Adenines. The real time interactive manipulation of such skeletal models for large DNA/RNA double helices, can be used to trace the path of the nucleic acid chain in three dimensions and hence get a better idea of its topology, location of linear or curved regions, distances between far off regions in the sequence etc. A physical picture of these features will assist in understanding the relationship between base sequence, structure and biological function in nucleic acids. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/289 http://dx.doi.org/10.1093/bioinformatics/11.3.289 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/2932006-11-07HighWireOUPbioinfo:11:3

Analysis of transcription control signals using artificial neural networks Nair, T.Murlidharan Tambe, Sanjeev S. Kulkarni, B.D. ORIGINAL PAPERS The role of the upstream region in controlling the transcription efficiency of a gene is well established. However, the question of predicting the extent of gene expressed given the upstream region has so far remained unresolved. Using an art neural network (ANN) to capture the internal representation associated with the transcription control signal, the present work predicts the rate of mRNA synthesis based on the pattern contained in the upstream region. Further, the model has been used to predict the transcription efficiency for all possible single base mutations associated with the β-globin promoter. The simulation results reveal that apart from the experimental observation that a -79G-A and -78G-A mutation increases the efficiency of transcription, mutation in these regions by C or T also causes an increase in transcription. Furthermore the simulation results verify that mutations in these conserved region, in general, decrease the transcriptional efficiency. However, the results also show that certain sequence elements, when mutated, either cause a marginal increase in the level of transcription or have no effect on transcription levels. The simulation results can be used as a guide in designing mutation experiments since an a priori estimate of the possible outcome of a mutation can be obtained. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/293 http://dx.doi.org/10.1093/bioinformatics/11.3.293 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/3012006-11-07HighWireOUPbioinfo:11:3

An image-processing approach to dotplots: an X-Window-based program for interactive analysis of dotplots derived from sequence and structural data Trelles-Salazar, Oswaldo Zapata, Emilio L. Dopazo, Joaquín Coulson, Andrew F.W. Carazo, José-María ORIGINAL PAPERS We present an approach to the study of the relationships between biological sequences and structures applying image analysis methods to dotplots. We introduce a set of analytical tools based on different types of digital image-processing filters that are new within the context of dotplots. We have reformulated some of the usual approaches in dotplot analysis as mathematical operations on images within the framework of mathematical morphology. An X-Window-based implementation of this new approach has been developed and is available by anonymous FTP. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/301 http://dx.doi.org/10.1093/bioinformatics/11.3.301 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/3092006-11-07HighWireOUPbioinfo:11:3

A parallel neural network simulator on the connection machine CM-5 Reczko, M. Hatzigeorigiou, A. Mache, N. Zell, A. Suhai, S. ORIGINAL PAPERS We here present a parallel implementation of art neural networks on the connection machine CM-5 and compare it with other parallel implementations on SIMD and MIMD architectures. This parallel implementation was developed with the goal of efficiently training large neural networks with huge training pattern sets for applications in molecular biology, in particular the prediction of coding regions in DNA sequences. The implementation uses training pattern parallelism and makes use of the parallel I/O facilities of the CM-5 and its efficient reduction operations available within the control network to achieve a high scalability. The parallel simulator obtains a maximum speed of 149.25 MCUPS for training feed-forward networks with backpropagation on a 512 processor CM-5 system without using the CM-5 vector facility. The implementation poses no restriction on the type of network topology and works with different batch training algorithms like BP, Quickprop and Rprop. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/309 http://dx.doi.org/10.1093/bioinformatics/11.3.309 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/3172006-11-07HighWireOUPbioinfo:11:3

DNAView: A quality assessment tool for the visualization of large sequenced regions Singh, Gautam B. Krawetz, A. ORIGINAL PAPERS This communication describes DNAView, a graphical tool for the visualization and printing of large nucleic acid sequences. DNAView uses color coding to compactly display genomic segments of up to 100kb on a single printed page. The specific color schemes integrated into DNAView can highlight ‘local aggregate’ properties of large segments of DNA. We have also incorporated a confidence expression for the assigned sequence. This is represented by base color intensity that is proportional to the number of times that base was sequenced. Areas of interest, such as exons, introns, repetitive elements and splice sites, can be emphasized using overlays. The colored image can be saved in a standard TIFF image file format that may be imported and annotated by other application software. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/317 http://dx.doi.org/10.1093/bioinformatics/11.3.317 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/3212006-11-07HighWireOUPbioinfo:11:3

Co-inertia analysis of amino-acid physico-chemical properties and protein composition with the ADE package Thioulouse, J. Lobry, J.R. ORIGINAL PAPERS A multivariate analysis method called co-inertia analysis was used to determine the main relationships between two data tables having identical rows. This method is available in the ADE multivariate analysis package for Macintosh micro-computers. It was applied to two data sets, one containing the amino-acid composition of 999 <it>E. coli</it> proteins, and the other the values of 402 physico-chemical properties for the 20 natural amino-acids. There were strong relationships between amino-acid physico-chemical properties and the composition of proteins. The first common factor was hydrophobicity; it is linked to the biological environment of proteins, either in the cytoplasm (or outside the cell), or in the nonpolar environment of the phospholipid bilayer of biological membranes. The second factor linked the expressivity of protein genes and the propensity of amino-acids to form alpha helix&sol;beta sheets. The third factor showed that heavy, aromatic amino-acids tend to be avoided, except when they are needed for structural or functional reasons. These results are discussed in terms of selective pressure acting on amino-acid composition of proteins. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/321 http://dx.doi.org/10.1093/bioinformatics/11.3.321 en Copyright (C) 1995, Oxford University Press

oai:open-archive.highwire.org:bioinfo:11/3/3312006-11-07HighWireOUPbioinfo:11:3

DNASUN: a package of computer programs for the biotechnology laboratory Mironov, A.A. Alexandrov, N.N. Bogodarova, N.Yu. Grigorjev, A. Lebedev, V.F. Lunovskaya, L.V. Truchan, M.E. Pevzner, P.A. COMMUNICATION The paper describes a new software package DNASUN developed for supporting gene engineering laboratories. The package provides a user-friendly interface for experimental researches and supports the traditional nucleotide&sol;protein sequence analysis as well as physical mapping, sequencing, plasmid manipulations, optimal oligonucleotide probe selection and other common molecular biology procedures. Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/331 http://dx.doi.org/10.1093/bioinformatics/11.3.331 en Copyright (C) 1995, Oxford University Press

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Reference Manager v. 6.0 Windows Bryant, Trevor SOFTWARE REVIEW Oxford University Press 1995-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/11/3/337 http://dx.doi.org/10.1093/bioinformatics/11.3.337 en Copyright (C) 1995, Oxford University Press

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Reading the book of life Searls, David B. EDITORIAL Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/579 http://dx.doi.org/10.1093/bioinformatics/17.7.579 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/5812006-11-07HighWireOUPbioinfo:17:7

LDB2000: sequence-based integrated maps of the human genome Ke, Xiayi Tapper, William Collins, Andrew ORIGINAL PAPERS Motivation: Integrated maps are useful for gene mapping and establishing the relationship between recombination and sequence. In this paper we describe algorithms and their implementation for constructing sequence-based integrated maps of the human chromosomes, which are presented in LDB2000, a web based resource. Gene mapping efforts are now focussing on linkage disequilibrium mapping and extension of the integrated map to represent the extent of linkage disequilibrium in different genomic regions would further increase the utility of these maps. Results: Sequence-based integrated maps have been completed for chromosomes 21 and 22. These maps provide locations for genes and polymorphic markers in sequence and on genetic linkage, radiation hybrid and cytogenetic scales. Single nucleotide polymorphisms associated with genes in the maps are also included and their sequence locations indicated. Related locus information, such as aliases and expression information, can be searched on the WWW site. Availability: <inter-ref locator="http://cedar.genetics.soton.ac.uk/public_html/LDB2000.html" locator-type="url">http://cedar.genetics.soton.ac.uk/public_html/LDB2000.html</inter-ref> Contact: <inter-ref locator="arc@soton.ac.uk" locator-type="email">arc&commat;soton.ac.uk</inter-ref> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/581 http://dx.doi.org/10.1093/bioinformatics/17.7.581 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/5872006-11-07HighWireOUPbioinfo:17:7

Extending traditional query-based integration approaches for functional characterization of post-genomic data Eckman, Barbara A. Kosky, Anthony S. Laroco, Leonardo A. ORIGINAL PAPERS Motivation: To identify and characterize regions of functional interest in genomic sequence requires full, flexible query access to an integrated, up-to-date view of all related information, irrespective of where it is stored (within an organization or across the Internet) and its format (traditional database, flat file, web site, results of runtime analysis). Wide-ranging multi-source queries often return unmanageably large result sets, requiring non-traditional approaches to exclude extraneous data. Results: Target Informatics Net (TINet) is a readily extensible data integration system developed at GlaxoSmith- Kline (GSK), based on the Object-Protocol Model (OPM) multidatabase middleware system of Gene Logic Inc. Data sources currently integrated include: the Mouse Genome Database (MGD) and Gene Expression Database (GXD), GenBank, SwissProt, PubMed, GeneCards, the results of runtime BLAST and PROSITE searches, and GSK proprietary relational databases. Special-purpose class methods used to filter and augment query results include regular expression pattern-matching over BLAST HSP alignments and retrieving partial sequences derived from primary structure annotations. All data sources and methods are accessible through an SQL-like query language or a GUI, so that when new investigations arise no additional programming beyond query specification is required. The power and flexibility of this approach are illustrated in such integrated queries as: (1) ‘find homologs in genomic sequence to all novel genes cloned and reported in the scientific literature within the past three months that are linked to the MeSH term ‘neoplasms”; (2) ‘using a neuropeptide precursor query sequence, return only HSPs where the target genomic sequences conserve the G[KR][KR] motif at the appropriate points in the HSP alignment’; and (3) ‘of the human genomic sequences annotated with exon boundaries in GenBank, return only those with valid putative donor/acceptor sites and start/stop codons’. Availability: Freely available to non-profit educational and research institutions. Usage by commercial entities requires a license agreement. Contact: <inter-ref locator="barbara_ eckman@sbphrd.com" locator-type="email">barbara_ eckman&commat;sbphrd.com</inter-ref> <fn id="fn0"><no>*</no> To whom correspondence should be addressed. </fn> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/587 http://dx.doi.org/10.1093/bioinformatics/17.7.587 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6022006-11-07HighWireOUPbioinfo:17:7

Identifying the 3'-terminal exon in human DNA Tabaska, Jack E. Davuluri, Ramana V. Zhang, Michael Q. ORIGINAL PAPERS Motivation: We present JTEF, a new program for finding 3′ terminal exons in human DNA sequences. This program is based on quadratic discriminant analysis, a standard non-linear statistical pattern recognition method. The quadratic discriminant functions used for building the algorithm were trained on a set of 3′ terminal exons of type 3tuexon (those containing the true STOP codon). Results: We showed that the average predictive accuracy of JTEF is higher than the presently available best programs (GenScan and Genemark.hmm) based on a test set of 65 human DNA sequences with 121 genes. In particular JTEF performs well on larger genomic contigs containing multiple genes and significant amounts of intergenic DNA. It will become a valuable tool for genome annotation and gene functional studies. Availability: JTEF is available free for academic users on request from <inter-ref locator="ftp://cshl.org/pub/science/mzhanglab/JTEF" locator-type="url">ftp://cshl.org/pub/science/mzhanglab/JTEF</inter-ref> and will be made available through the World Wide Web (<inter-ref locator="http://argon.cshl.org/" locator-type="url">http://argon.cshl.org/</inter-ref>). Contact: <inter-ref locator="mzhang@cshl.org" locator-type="email">mzhang&commat;cshl.org</inter-ref>; <inter-ref locator="ramana@cshl.org" locator-type="email">ramana&commat;cshl.org</inter-ref> <fn id="fn0"><no>*</no> To whom correspondence should be addressed. </fn> <fn id="fn2"><no>2</no> Present address: Monsanto Company, 800 North Lindbergh, St Louis, MO 63167, USA. </fn> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/602 http://dx.doi.org/10.1093/bioinformatics/17.7.602 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6082006-11-07HighWireOUPbioinfo:17:7

Identifying target sites for cooperatively binding factors GuhaThakurta, Debraj Stormo, Gary D. ORIGINAL PAPERS Motivation: Transcriptional activation in eukaryotic organisms normally requires combinatorial interactions of multiple transcription factors. Though several methods exist for identification of individual protein binding site patterns in DNA sequences, there are few methods for discovery of binding site patterns for cooperatively acting factors. Here we present an algorithm, Co-Bind (for COperative BINDing), for discovering DNA target sites for cooperatively acting transcription factors. The method utilizes a Gibbs sampling strategy to model the cooperativity between two transcription factors and defines position weight matrices for the binding sites. Sequences from both the training set and the entire genome are taken into account, in order to discriminate against commonly occurring patterns in the genome, and produce patterns which are significant only in the training set. Results: We have tested Co-Bind on semi-synthetic and real data sets to show it can efficiently identify DNA target site patterns for cooperatively binding transcription factors. In cases where binding site patterns are weak and cannot be identified by other available methods, Co-Bind, by virtue of modeling the cooperativity between factors, can identify those sites efficiently. Though developed to model protein–DNA interactions, the scope of Co-Bind may be extended to combinatorial, sequence specific, interactions in other macromolecules. Availability: The program is available upon request from the authors or may be downloaded from <inter-ref locator="http://ural.wustl.edu" locator-type="url">http://ural.wustl.edu</inter-ref>. Contact: <inter-ref locator="dg@genetics.wustl.edu" locator-type="email">dg&commat;genetics.wustl.edu</inter-ref>; <inter-ref locator="stormo@genetics.wustl.edu" locator-type="email">stormo&commat;genetics.wustl.edu</inter-ref> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/608 http://dx.doi.org/10.1093/bioinformatics/17.7.608 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6222006-11-07HighWireOUPbioinfo:17:7

Conformational model for binding site recognition by the E.coli MetJ transcription factor Liu, Rongxiang Blackwell, Thomas W. States, David J. ORIGINAL PAPERS Motivation: Current methods for identifying sequence specific binding sites in DNA sequence using position specific weight matrices are limited in both sensitivity and specificity. Double strand DNA helix exhibits sequence dependent variations in conformation. Interactions between macromolecules result from complementarity of the two tertiary structures. We hypothesize that this conformational variation plays a role in transcription factor binding site recognition, and that the use of this structure information will improve the predictive power of transcription factor binding site models. Results: Conformation models for the sequence dependence of DNA helix distortion have been developed. Using our conformational models, we defined a tertiary structure template for the met operon repressor MetJ binding site. Both naturally occurring sites and precursor binding sites identified through in vitro selection were used as the basis for template definition. The conformational model appears to recognize features of protein binding sites that are distinct from the features recognized by primary sequence based profiles. Combining the conformational model and primary sequence profile yields a hybrid model with improved discriminatory power compared with either the conformational model or sequence profile alone. Using our hybrid model, we searched the E.coli genome. We are able to identify the documented MetJ sites in the promoter regions of metA, metB, metC, metR and metF. In addition, we find several novel loci with characteristics suggesting that they are functional MetJ repressor binding sites. Novel MetJ binding sites are found upstream of the metK gene, as well as upstream of a gene, abc, a gene that encodes for a component of a multifunction transporter which may transport amino acids across the membrane. The false positive rate is significantly lower than the sequence profile method. Availability: The programs of implementation of this algorithm are available upon request. The list of crystal structures used for compiling the mean base step parameters of DNA is available by anonymous ftp at <inter-ref locator="http://stateslab.wustl.edu/pub/helix/StructureList" locator-type="url">http://stateslab.wustl.edu/pub/helix/StructureList</inter-ref>. Contact: <inter-ref locator="states@ccb.wustl.edu" locator-type="email">states&commat;ccb.wustl.edu</inter-ref> <fn id="fn0"><no>*</no> To whom correspondence should be addressed. </fn> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/622 http://dx.doi.org/10.1093/bioinformatics/17.7.622 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6342006-11-07HighWireOUPbioinfo:17:7

Automated image analysis for array hybridization experiments Steinfath, Matthias Wruck, Wasco Seidel, Henrik Lehrach, Hans Radelof, Uwe O’Brien, John ORIGINAL PAPERS Motivation: Image analysis is a major part of data evaluation for array hybridization experiments in molecular biology. The program presented here is designed to analyze automatically images from hybridization experiments with various arrangements: different kinds of probes (oligonucleotides or complex probes), different supports (nylon filters or glass slides), different labeling of probes (radioactively or fluorescently). The program is currently applied to oligonucleotide fingerprinting projects and complex hybridizations. The only precondition for the use of the program is that the targets are arrayed in a grid, which can be approximately transformed to an orthogonal equidistant grid by a projective mapping. Results: We demonstrate that our program can cope with the following problems: global distortion of the grid, missing of grid nodes, local deviation of the spot from its specified grid position. This is checked by different quality measures. The image analysis of oligonucleotide fingerprint experiments on an entire genetic library is used, in clustering procedures, to group related clones together. The results show that the program yields automatically generated high quality input data for follow up analysis such as clustering procedures. Availability: The executable files will be available upon request for academics. Contact: <inter-ref locator="steinfat@molgen.mpg.de" locator-type="email">steinfat&commat;molgen.mpg.de</inter-ref> <fn id="fn0"><no>*</no> To whom correspondence should be addressed. </fn> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/634 http://dx.doi.org/10.1093/bioinformatics/17.7.634 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6422006-11-07HighWireOUPbioinfo:17:7

Semi-automated update and cleanup of structural RNA alignment databases Gorodkin, J. Zwieb, C. Knudsen, B. ORIGINAL PAPERS Summary: We have developed a series of programs which assist in maintenance of structural RNA databases. A main program BLASTs the RNA database against GenBank and automatically extends and realigns the sequences to include the entire range of the RNA query sequences. After manual update of the database, other programs can examine base pair consistency and phylogenetic support. The output can be applied iteratively to refine the structural alignment of the RNA database. Using these tools, the number of potential misannotations per sequence was reduced from 20 to 3 in the Signal Recognition Particle RNA database. Availability: A quick-server and programs are available at <inter-ref locator="http://www.bioinf.au.dk/rnadbtool/" locator-type="url">http://www.bioinf.au.dk/rnadbtool/</inter-ref> Contact: <inter-ref locator="gorodkin@bioinf.au.dk" locator-type="email">gorodkin&commat;bioinf.au.dk</inter-ref> <fn id="fn0"><no>*</no> These authors contributed equally to this work. </fn> <fn id="fn1"><no>†</no> To whom correspondence should be addressed. </fn> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/642 http://dx.doi.org/10.1093/bioinformatics/17.7.642 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6462006-11-07HighWireOUPbioinfo:17:7

Evaluation of methods for the prediction of membrane spanning regions Möller, Steffen Croning, Michael D. R. Apweiler, Rolf ORIGINAL PAPERS Motivation: A variety of tools are available to predict the topology of transmembrane proteins. To date no independent evaluation of the performance of these tools has been published. A better understanding of the strengths and weaknesses of the different tools would guide both the biologist and the bioinformatician to make better predictions of membrane protein topology. Results: Here we present an evaluation of the performance of the currently best known and most widely used methods for the prediction of transmembrane regions in proteins. Our results show that TMHMM is currently the best performing transmembrane prediction program. Contact: <inter-ref locator="moeller@ebi.ac.uk" locator-type="email">moeller&commat;ebi.ac.uk</inter-ref>; <inter-ref locator="croning@ebi.ac.uk" locator-type="email">croning&commat;ebi.ac.uk</inter-ref>; <inter-ref locator="apweiler@ebi.ac.uk" locator-type="email">apweiler&commat;ebi.ac.uk</inter-ref> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/646 http://dx.doi.org/10.1093/bioinformatics/17.7.646 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6542006-11-07HighWireOUPbioinfo:17:7

An integrated system for high throughput TaqManTM based SNP genotyping Hampe, Jochen Wollstein, Andreas Lu, Timothy Frevel, Hans-Jürgen Will, Marcus Manaster, Carl Schreiber, Stefan APPLICATIONS NOTES Summary: We have developed an integrated laboratory information system that allows the flexible handling of pedigree, phenotype and genotype information. Specifically, it includes client applications for an integrated data import from TaqMan typing files, Mendel checking, data export, handling of pedigree and phenotype information and analysis features. Availability: The SQL source code, sources and binaries of the client applications (NT and Windows95/98 platforms) and additional documentation are available at <inter-ref locator="http://www.mucosa.de/" locator-type="url">http://www.mucosa.de/</inter-ref>. Contact: <inter-ref locator="J.Hampe@mucosa.de" locator-type="email">J.Hampe&commat;mucosa.de</inter-ref> <fn id="fn0"><no>*</no> To whom correspondence should be addressed. </fn> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/654 http://dx.doi.org/10.1093/bioinformatics/17.7.654 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6562006-11-07HighWireOUPbioinfo:17:7

MEDUSA: large scale automatic selection and visual assessment of PCR primer pairs Podowski, Raf M. Sonnhammer, Erik L. L. APPLICATIONS NOTES Summary: MEDUSA is a tool for automatic selection and visual assessment of PCR primer pairs, developed to assist large scale gene expression analysis projects. The system allows specification of constraints of the location and distances between the primers in a pair. For instance, primers in coding, non-coding, exon/intron-spanning regions might be selected. Medusa applies these constraints as a filter to primers predicted by three external programs, and displays the resulting primer pairs graphically in the Blixem (Sonnhammer and Durbin, <it>Comput. Appl. Biosci.</it> <b>10</b>, 301–307, 1994; <inter-ref locator="http://www.cgr.ki.se/cgr/groups/sonnhammer/Blixem.html" locator-type="url">http://www.cgr.ki.se/cgr/groups/sonnhammer/Blixem.html</inter-ref>) viewer. Availability: The MEDUSA web server is available at <inter-ref locator="http://www.cgr.ki.se/cgr/MEDUSA" locator-type="url">http://www.cgr.ki.se/cgr/MEDUSA</inter-ref>. The source code and user information are available at <inter-ref locator="ftp://ftp.cgr.ki.se/pub/prog/medusa" locator-type="url">ftp://ftp.cgr.ki.se/pub/prog/medusa</inter-ref>. Contact: <inter-ref locator="Erik.Sonnhammer@cgr.ki.se" locator-type="email">Erik.Sonnhammer&commat;cgr.ki.se</inter-ref> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/656 http://dx.doi.org/10.1093/bioinformatics/17.7.656 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6582006-11-07HighWireOUPbioinfo:17:7

Visualization of expression clusters using Sammon's non-linear mapping Ewing, Rob M. Cherry, J. Michael APPLICATIONS NOTES Summary: A method of exploratory analysis and visualization of multi-dimensional gene expression data using Sammon’s Non-Linear Mapping (NLM) is presented. Availability: Scripts are available from the authors. Contact: <inter-ref locator="ewing@genome.stanford.edu" locator-type="email">ewing&commat;genome.stanford.edu</inter-ref> <fn id="fn0"><no>*</no> To whom correspondence should be addressed. </fn> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/658 http://dx.doi.org/10.1093/bioinformatics/17.7.658 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6602006-11-07HighWireOUPbioinfo:17:7

ADAPTSITE: detecting natural selection at single amino acid sites Suzuki, Yoshiyuki Gojobori, Takashi Nei, Masatoshi APPLICATIONS NOTES Summary: ADAPTSITE is a program package for detecting natural selection at single amino acid sites, using a multiple alignment of protein-coding sequences for a given phylogenetic tree. The program infers ancestral codons at all interior nodes, and computes the total numbers of synonymous (c<inf>S</inf>) and nonsynonymous (c<inf>N</inf>) substitutions as well as the average numbers of synonymous (s<inf>S</inf>) and nonsynonymous (s<inf>N</inf>) sites for each codon site. The probabilities of occurrence of synonymous and nonsynonymous substitutions are approximated by s<inf>S</inf> / (s<inf>S</inf> + s<inf>N</inf>) and s<inf>N</inf> / (s<inf>S</inf> + s<inf>N</inf>), respectively. The null hypothesis of selective neutrality is tested for each codon site, assuming a binomial distribution for the probability of obtaining c<inf>S</inf> and c<inf>N</inf>. Availability: ADAPTSITE is available free of charge at the World-Wide Web sites <inter-ref locator="http://mep.bio.psu.edu/adaptivevol.html" locator-type="url">http://mep.bio.psu.edu/adaptivevol.html</inter-ref> and <inter-ref locator="http://www.cib.nig.ac.jp/dda/yossuzuk/welcome.html" locator-type="url">http://www.cib.nig.ac.jp/dda/yossuzuk/welcome.html</inter-ref>. The package includes the source code written in C, binary files for UNIX operating systems, manual, and example files. Contact: <inter-ref locator="yis1@psu.edu" locator-type="email">yis1&commat;psu.edu</inter-ref> <fn id="fn0"><no>*</no> To whom correspondence should be addressed. </fn> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/660 http://dx.doi.org/10.1093/bioinformatics/17.7.660 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6622006-11-07HighWireOUPbioinfo:17:7

PAL: an object-oriented programming library for molecular evolution and phylogenetics Drummond, Alexei Strimmer, Korbinian APPLICATIONS NOTES Summary: Phylogenetic Analysis Library (PAL) is a collection of Java classes for use in molecular evolution and phylogenetics. PAL provides a modular environment for the rapid construction of both special-purpose and general analysis programs. PAL version 1.1 consists of 145 public classes or interfaces in 13 packages, including classes for models of character evolution, maximum-likelihood estimation, and the coalescent, with a total of more than 27000 lines of code. The PAL project is set up as a collaborative project to facilitate contributions from other researchers. Availability: The program is free and is available at <inter-ref locator="http://www.pal-project.org" locator-type="url">http://www.pal-project.org</inter-ref>. It requires Java 1.1 or later. PAL is licensed under the GNU General Public License. Contact: <inter-ref locator="a.drummond@auckland.ac.nz" locator-type="email">a.drummond&commat;auckland.ac.nz</inter-ref>; <inter-ref locator="korbinian.strimmer@zoo.ox.ac.uk" locator-type="email">korbinian.strimmer&commat;zoo.ox.ac.uk</inter-ref> Supplementary information: An online description of the Application Programming Interface (API) of all public classes in PAL is available at <inter-ref locator="http://www.pal-project.org/api/" locator-type="url">http://www.pal-project.org/api/</inter-ref>. <fn id="fn0"><no>*</no> To whom correspondence should be addressed. </fn> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/662 http://dx.doi.org/10.1093/bioinformatics/17.7.662 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6642006-11-07HighWireOUPbioinfo:17:7

T-REX: reconstructing and visualizing phylogenetic trees and reticulation networks Makarenkov, Vladimir APPLICATIONS NOTES Summary: T-REX (tree and reticulogram reconstruction) is an application to reconstruct phylogenetic trees and reticulation networks from distance matrices. The application includes a number of tree fitting methods like NJ, UNJ or ADDTREE which have been very popular in phylogenetic analysis. At the same time, the software comprises several new methods of phylogenetic analysis such as: tree reconstruction using weights, tree inference from incomplete distance matrices or modeling a reticulation network for a collection of objects or species. T-REX also allows the user to visualize obtained tree or network structures using Hierarchical, Radial or Axial types of tree drawing and manipulate them interactively. Availability: T-REX is a freeware package available online at: <inter-ref locator="http://www.fas.umontreal.ca/biol/casgrain/en/labo/t-rex" locator-type="url">http://www.fas.umontreal.ca/biol/casgrain/en/labo/t-rex</inter-ref> Contact: <inter-ref locator="makarenv@magellan.umontreal.ca" locator-type="email">makarenv&commat;magellan.umontreal.ca</inter-ref> or <inter-ref locator="casgrain@magellan.umontreal.ca" locator-type="email">casgrain&commat;magellan.umontreal.ca</inter-ref> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/664 http://dx.doi.org/10.1093/bioinformatics/17.7.664 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:17/7/6692006-11-07HighWireOUPbioinfo:17:7

A Java applet for visualizing protein-protein interaction Mrowka, Ralf APPLICATIONS NOTES Summary: A web applet for browsing protein–protein interactions was implemented. It enables the display of interaction relationships, based upon neighboring distance and biological function. Availability: The Java applet is available at <inter-ref locator="http://www.charite.de/bioinformatics" locator-type="url">http://www.charite.de/bioinformatics</inter-ref> Contact: <inter-ref locator="Mrowka@rz.hu-berlin.de" locator-type="email">Mrowka&commat;rz.hu-berlin.de</inter-ref> Oxford University Press 2001-07-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/17/7/669 http://dx.doi.org/10.1093/bioinformatics/17.7.669 en Copyright (C) 2001, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/23612007-09-17HighWireOUPbioinfo:23:18

The global trace graph, a novel paradigm for searching protein sequence databases Heger, Andreas Mallick, Swapan Wilton, Christopher Holm, Liisa SEQUENCE ANALYSIS <b>Motivation:</b> Propagating functional annotations to sequence-similar, presumably homologous proteins lies at <cross-ref type="fn" refid="FN1"></cross-ref>the <cross-ref type="fn" refid="FN2"></cross-ref>heart <cross-ref type="fn" refid="FN3"></cross-ref>of the bioinformatics industry. Correct propagation is crucially dependent on the accurate identification of subtle sequence motifs that are conserved in evolution. The evolutionary signal can be difficult to detect because functional sites may consist of non-contiguous residues while segments in-between may be mutated without affecting fold or function. <b>Results:</b> Here, we report a novel graph clustering algorithm in which all known protein sequences simultaneously self-organize into hypothetical multiple sequence alignments. This eliminates noise so that non-contiguous sequence motifs can be tracked down between extremely distant homologues. The novel data structure enables fast sequence database searching methods which are superior to profile-profile comparison at recognizing distant homologues. This study will boost the leverage of structural and functional genomics and opens up new avenues for data mining a complete set of functional signature motifs. <b>Availability:</b> <inter-ref locator="http://www.bioinfo.biocenter.helsinki.fi/gtg" locator-type="url">http://www.bioinfo.biocenter.helsinki.fi/gtg</inter-ref> <b>Contact:</b> <inter-ref locator="liisa.holm@helsinki.fi" locator-type="email">liisa.holm@helsinki.fi</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2361 http://dx.doi.org/10.1093/bioinformatics/btm358 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/23682007-09-17HighWireOUPbioinfo:23:18

A quantitative genotype algorithm reflecting H5N1 Avian influenza niches Wan, Xiu-Feng Chen, Guorong Luo, Feng Emch, Michael Donis, Ruben PHYLOGENETICS <b>Motivation:</b> Computational genotyping analyses are critical for characterizing molecular evolutionary footprints, thus providing important information for designing the strategies of influenza prevention and control. Most of the current methods that are available are based on multiple sequence alignment and phylogenetic tree construction, which are time consuming and limited by the number of taxa. Arbitrarily defining genotypes further complicates the interpretation of genotyping results. <b>Methods:</b> In this study, we describe a quantitative influenza genotyping algorithm based on the theory of quasispecies. First, the complete composition vector (CCV) was utilized to calculate the pairwise evolutionary distance between genotypes. Next, Hierarchical Bayesian Modeling using the Gibbs Sampling algorithm was applied to identify the segment genotype threshold, which is used to identify influenza segment genotype through a modularity calculation. The viral genotype was defined by combining eight segment genotypes based on the genetic reassortment feature of influenza A viruses. <b>Results:</b> We applied this method for H5N1 avian influenza viruses and identified 107 niches among 283 viruses with a complete genome set. The diversity of viral genotypes, and their correlation with geographic locations suggests that these viruses form local niches after being introduced to a new ecological environment through poultry trade or bird migration. This novel method allows us to define genotypes in a robust, quantitative as well as hierarchical manner. <b>Contact:</b> <inter-ref locator="wanhenry@yahoo.com" locator-type="email">wanhenry@yahoo.com</inter-ref> or <inter-ref locator="fvq7@cdc.gov" locator-type="email">fvq7@cdc.gov</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2368 http://dx.doi.org/10.1093/bioinformatics/btm354 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/23532007-09-17HighWireOUPbioinfo:23:18

Methods of remote homology detection can be combined to increase coverage by 10% in the midnight zone Reid, Adam James Yeats, Corin Orengo, Christine Anne SEQUENCE ANALYSIS <b>Motivation:</b> A recent development in sequence-based remote homologue detection is the introduction of profile–profile comparison methods. These are more powerful than previous technologies and can detect potentially homologous relationships missed by structural classifications such as CATH and SCOP. As structural classifications traditionally act as the gold standard of homology this poses a challenge in benchmarking them. <b>Results:</b> We present a novel approach which allows an accurate benchmark of these methods against the CATH structural classification. We then apply this approach to assess the accuracy of a range of publicly available methods for remote homology detection including several profile–profile methods (COMPASS, HHSearch, PRC) from two perspectives. First, in distinguishing homologous domains from non-homologues and second, in annotating proteomes with structural domain families. PRC is shown to be the best method for distinguishing homologues. We show that SAM is the best practical method for annotating genomes, whilst using COMPASS for the most remote homologues would increase coverage. Finally, we introduce a simple approach to increase the sensitivity of remote homologue detection by up to 10 %. This is achieved by combining multiple methods with a jury vote. <b>Contact:</b> <inter-ref locator="reid@bioichem.ucl.ac.uk" locator-type="email">reid@bioichem.ucl.ac.uk</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2353 http://dx.doi.org/10.1093/bioinformatics/btm355 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24332007-09-17HighWireOUPbioinfo:23:18

Modular decomposition of metabolic reaction networks based on flux analysis and pathway projection Yoon, Jeongah Si, Yaguang Nolan, Ryan Lee, Kyongbum SYSTEMS BIOLOGY <b>Motivation:</b> The rational decomposition of biochemical networks into sub-structures has emerged as a useful approach to study the design of these complex systems. A biochemical network is characterized by an inhomogeneous connectivity distribution, which gives rise to several organizational features, including modularity. To what extent the connectivity-based modules reflect the functional organization of the network remains to be further explored. In this work, we examine the influence of physiological perturbations on the modular organization of cellular metabolism. <b>Results:</b> Modules were characterized for two model systems, liver and adipocyte primary metabolism, by applying an algorithm for top–down partition of directed graphs with non-uniform edge weights. The weights were set by the engagement of the corresponding reactions as expressed by the flux distribution. For the base case of the fasted rat liver, three modules were found, carrying out the following biochemical transformations: ketone body production, glucose synthesis and transamination. This basic organization was further modified when different flux distributions were applied that describe the liver's metabolic response to whole body inflammation. For the fully mature adipocyte, only a single module was observed, integrating all of the major pathways needed for lipid storage. Weaker levels of integration between the pathways were found for the early stages of adipocyte differentiation. Our results underscore the inhomogeneous distribution of both connectivity and connection strengths, and suggest that global activity data such as the flux distribution can be used to study the organizational flexibility of cellular metabolism. <b>Contact:</b> <inter-ref locator="kyongbum.lee@tufts.edu" locator-type="email">kyongbum.lee@tufts.edu</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2433 http://dx.doi.org/10.1093/bioinformatics/btm374 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24412007-09-17HighWireOUPbioinfo:23:18

Quantitative quality-assessment techniques to compare fractionation and depletion methods in SELDI-TOF mass spectrometry experiments Harezlak, Jaroslaw Wang, Mike Christiani, David Lin, Xihong DATA AND TEXT MINING <b>Motivation:</b> Mass spectrometry (MS), such as the surface-enhanced laser desorption and ionization time-of-flight (SELDI-TOF) MS, provides a potentially promising proteomic technology for biomarker discovery. An important matter for such a technology to be used routinely is its reproducibility. It is of significant interest to develop quantitative measures to evaluate the quality and reliability of different experimental methods. <b>Results:</b> We compare the quality of SELDI-TOF MS data using unfractionated, fractionated plasma samples and abundant protein depletion methods in terms of the numbers of detected peaks and reliability. Several statistical quality-control and quality-assessment techniques are proposed, including the Graeco–Latin square design for the sample allocation on a Protein chip, the use of the pairwise Pearson correlation coefficient as the similarity measure between the spectra in conjunction with multi-dimensional scaling (MDS) for graphically evaluating similarity of replicates and assessing outlier samples; and the use of the reliability ratio for evaluating reproducibility. Our results show that the number of peaks detected is similar among the three sample preparation technologies, and the use of the Sigma multi-removal kit does not improve peak detection. Fractionation of plasma samples introduces more experimental variability. The peaks detected using the unfractionated plasma samples have the highest reproducibility as determined by the reliability ratio. <b>Availability:</b> Our algorithm for assessment of SELDI-TOF experiment quality is available at <inter-ref locator="http://www.biostat.harvard.edu/~xlin" locator-type="url">http://www.biostat.harvard.edu/~xlin</inter-ref> <b>Contact:</b> <inter-ref locator="harezlak@post.harvard.edu" locator-type="email">harezlak@post.harvard.edu</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2441 http://dx.doi.org/10.1093/bioinformatics/btm346 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/23762007-09-17HighWireOUPbioinfo:23:18

Natively unstructured regions in proteins identified from contact predictions Schlessinger, Avner Punta, Marco Rost, Burkhard STRUCTURAL BIOINFORMATICS <b>Motivation:</b> Natively unstructured (also dubbed <it>intrinsically disordered</it>) regions in proteins lack a defined 3D structure under physiological conditions and often adopt regular structures under particular conditions. Proteins with such regions are overly abundant in eukaryotes, they may increase functional complexity of organisms and they usually evade structure determination in the unbound form. Low propensity for the formation of internal residue contacts has been previously used to predict natively unstructured regions. <b>Results:</b> We combined PROFcon predictions for protein-specific contacts with a generic pairwise potential to predict unstructured regions. This novel method, <it>Ucon</it>, outperformed the best available methods in predicting proteins with long unstructured regions. Furthermore, <it>Ucon</it> correctly identified cases missed by other methods. By computing the difference between predictions based on specific contacts (approach introduced here) and those based on generic potentials (realized in other methods), we might identify unstructured regions that are involved in protein–protein binding. We discussed one example to illustrate this ambitious aim. Overall, Ucon added quality and an orthogonal aspect that may help in the experimental study of unstructured regions in network hubs. <b>Availability:</b> <inter-ref locator="http://www.predictprotein.org/submit_ucon.html" locator-type="url">http://www.predictprotein.org/submit_ucon.html</inter-ref> <b>Contact:</b> <inter-ref locator="as2067@columbia.edu" locator-type="email">as2067@columbia.edu</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2376 http://dx.doi.org/10.1093/bioinformatics/btm349 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/23852007-09-17HighWireOUPbioinfo:23:18

AffyProbeMiner: a web resource for computing or retrieving accurately redefined Affymetrix probe sets Liu, Hongfang Zeeberg, Barry R. Qu, Gang Koru, A. Gunes Ferrucci, Alessandro Kahn, Ari Ryan, Michael C. Nuhanovic, Antej Munson, Peter J. Reinhold, William C. Kane, David W. Weinstein, John N. GENE EXPRESSION <b>Motivation:</b> Affymetrix microarrays are widely used to measure global expression of mRNA transcripts. That technology is based on the concept of a probe set. Individual probes within a probe set were originally designated by Affymetrix to hybridize with the same unique mRNA transcript. Because of increasing accuracy in knowledge of genomic sequences, however, a substantial number of the manufacturer's original probe groupings and mappings are now known to be inaccurate and must be corrected. Otherwise, analysis and interpretation of an Affymetrix microarray experiment will be in error. <b>Results:</b> AffyProbeMiner is a computationally efficient platform-independent tool that uses all RefSeq mature RNA protein coding transcripts and validated complete coding sequences in GenBank to (1) regroup the individual probes into consistent probe sets and (2) remap the probe sets to the correct sets of mRNA transcripts. The individual probes are grouped into probe sets that are ‘transcript-consistent’ in that they hybridize to the same mRNA transcript (or transcripts) and, therefore, measure the same entity (or entities). About 65.6 % of the probe sets on the HG-U133A chip were affected by the remapping. Pre-computed regrouped and remapped probe sets for many Affymetrix microarrays are made freely available at the AffyProbeMiner web site. Alternatively, we provide a web service that enables the user to perform the remapping for any type of short-oligo commercial or custom array that has an Affymetrix-format Chip Definition File (CDF). Important features that differentiate AffyProbeMiner from other approaches are flexibility in the handling of splice variants, computational efficiency, extensibility, customizability and user-friendliness of the interface. <b>Availability:</b> The web interface and software (GPL open source license), are publicly-accessible at <inter-ref locator="http://discover.nci.nih.gov/affyprobeminer" locator-type="url">http://discover.nci.nih.gov/affyprobeminer</inter-ref>. <b>Contact:</b> <inter-ref locator="hl224@georgetown.edu" locator-type="email">hl224@georgetown.edu</inter-ref> or <inter-ref locator="barry@discover.nci.nih.gov" locator-type="email">barry@discover.nci.nih.gov</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2385 http://dx.doi.org/10.1093/bioinformatics/btm360 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/23912007-09-17HighWireOUPbioinfo:23:18

Selection and validation of normalization methods for c-DNA microarrays using within-array replications Fan, Jianqing Niu, Yue GENE EXPRESSION <b>Motivation:</b> Normalization of microarray data is essential for multiple-array analyses. Several normalization protocols have been proposed based on different biological or statistical assumptions. A fundamental problem arises whether they have effectively normalized arrays. In addition, for a given array, the question arises how to choose a method to most effectively normalize the microarray data. <b>Results:</b> We propose several techniques to compare the effectiveness of different normalization methods. We approach the problem by constructing statistics to test whether there are any systematic biases in the expression profiles among duplicated spots within an array. The test statistics involve estimating the genewise variances. This is accomplished by using several novel methods, including empirical Bayes methods for moderating the genewise variances and the smoothing methods for aggregating variance information. <it>P</it>-values are estimated based on a normal or χ approximation. With estimated <it>P</it>-values, we can choose a most appropriate method to normalize a specific array and assess the extent to which the systematic biases due to the variations of experimental conditions have been removed. The effectiveness and validity of the proposed methods are convincingly illustrated by a carefully designed simulation study. The method is further illustrated by an application to human placenta cDNAs comprising a large number of clones with replications, a customized microarray experiment carrying just a few hundred genes on the study of the molecular roles of Interferons on tumor, and the Agilent microarrays carrying tens of thousands of total RNA samples in the MAQC project on the study of reproducibility, sensitivity and specificity of the data. <b>Availability:</b> Code to implement the method in the statistical package R is available from the authors. <b>Contact:</b> <inter-ref locator="jqfan@princeton.edu" locator-type="email">jqfan@princeton.edu</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2391 http://dx.doi.org/10.1093/bioinformatics/btm361 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24152007-09-17HighWireOUPbioinfo:23:18

Robustness analysis and tuning of synthetic gene networks Batt, Grégory Yordanov, Boyan Weiss, Ron Belta, Calin SYSTEMS BIOLOGY <b>Motivation:</b> The goal of synthetic biology is to design and construct biological systems that present a desired behavior. The construction of synthetic gene networks implementing simple functions has demonstrated the feasibility of this approach. However, the design of these networks is difficult, notably because existing techniques and tools are not adapted to deal with uncertainties on molecular concentrations and parameter values. <b>Results:</b> We propose an approach for the analysis of a class of uncertain piecewise-multiaffine differential equation models. This modeling framework is well adapted to the experimental data currently available. Moreover, these models present interesting mathematical properties that allow the development of efficient algorithms for solving robustness analyses and tuning problems. These algorithms are implemented in the tool RoVerGeNe, and their practical applicability and biological relevance are demonstrated on the analysis of the tuning of a synthetic transcriptional cascade built in <it>Escherichia coli</it>. <b>Availability:</b> RoVerGeNe and the transcriptional cascade model are available at <inter-ref locator="http://iasi.bu.edu/%7Ebatt/rovergene/rovergene.htm" locator-type="url">http://iasi.bu.edu/%7Ebatt/rovergene/rovergene.htm</inter-ref> <b>Contact:</b> <inter-ref locator="gregory.batt@imag.fr" locator-type="email">gregory.batt@imag.fr</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2415 http://dx.doi.org/10.1093/bioinformatics/btm362 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24072007-09-17HighWireOUPbioinfo:23:18

LICORN: learning cooperative regulation networks from gene expression data Elati, Mohamed Neuvial, Pierre Bolotin-Fukuhara, Monique Barillot, Emmanuel Radvanyi, François Rouveirol, Céline SYSTEMS BIOLOGY <b>Motivation:</b> One of the most challenging tasks in the post-genomic era is the reconstruction of transcriptional regulation networks. The goal is to identify, for each gene expressed in a particular cellular context, the regulators affecting its transcription, and the co-ordination of several regulators in specific types of regulation. DNA microarrays can be used to investigate relationships between regulators and their target genes, through simultaneous observations of their RNA levels. <b>Results:</b> We propose a <it>data mining</it> system for inferring transcriptional regulation relationships from RNA expression values. This system is particularly suitable for the detection of cooperative transcriptional regulation. We model regulatory relationships as labelled two-layer gene regulatory networks, and describe a method for the efficient learning of these bipartite networks from discretized expression data sets. We also evaluate the statistical significance of such inferred networks and validate our methods on two public yeast expression data sets. <b>Availability:</b> <inter-ref locator="http://www.lri.fr/~elati/licorn.html" locator-type="url">http://www.lri.fr/~elati/licorn.html</inter-ref> <b>Contact:</b> <inter-ref locator="mohamed.elati@curie.fr" locator-type="email">mohamed.elati@curie.fr</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2407 http://dx.doi.org/10.1093/bioinformatics/btm352 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/23992007-09-17HighWireOUPbioinfo:23:18

Haplotype inference for present absent genotype data using previously identified haplotypes and haplotype patterns Yoo, Yun Joo Tang, Jianming Kaslow, Richard A. Zhang, Kui GENETICS AND POPULATION ANALYSIS <b>Motivation:</b> Killer immunoglobulin-like receptor (KIR) genes vary considerably in their presence or absence on a specific regional haplotype. Because presence or absence of these genes is largely detected using locus-specific genotyping technology, the distinction between homozygosity and hemizygosity is often ambiguous. The performance of methods for haplotype inference (e.g. PL-EM, PHASE) for KIR genes may be compromised due to the large portion of ambiguous data. At the same time, many haplotypes or partial haplotype patterns have been previously identified and can be incorporated to facilitate haplotype inference for unphased genotype data. To accommodate the increased ambiguity of present–absent genotyping of KIR genes, we developed a hybrid approach combining a greedy algorithm with the Expectation-Maximization (EM) method for haplotype inference based on previously identified haplotypes and haplotype patterns. <b>Results:</b> We implemented this algorithm in a software package named HAPLO-IHP (Haplotype inference using identified haplotype patterns) and compared its performance with that of HAPLORE and PHASE on simulated KIR genotypes. We compared five measures in order to evaluate the reliability of haplotype assignments and the accuracy in estimating haplotype frequency. Our method outperformed the two existing techniques by all five measures when either 60 % or 25 % of previously identified haplotypes were incorporated into the analyses. <b>Availability:</b> The HAPLO-IHP is available at <inter-ref locator="http://www.soph.uab.edu/Statgenetics/People/KZhang/HAPLO-IHP/index.html" locator-type="url">http://www.soph.uab.edu/Statgenetics/People/KZhang/HAPLO-IHP/index.html</inter-ref> <b>Contact:</b> <inter-ref locator="KZhang@ms.soph.uab.edu" locator-type="email">KZhang@ms.soph.uab.edu</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2399 http://dx.doi.org/10.1093/bioinformatics/btm371 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24232007-09-17HighWireOUPbioinfo:23:18

miniTUBA: medical inference by network integration of temporal data using Bayesian analysis Xiang, Zuoshuang Minter, Rebecca M. Bi, Xiaoming Woolf, Peter J. He, Yongqun SYSTEMS BIOLOGY <b>Motivation:</b> Many biomedical and clinical research problems involve discovering causal relationships between observations gathered from temporal events. Dynamic Bayesian networks are a powerful modeling approach to describe causal or apparently causal relationships, and support complex medical inference, such as future response prediction, automated learning, and rational decision making. Although many engines exist for creating Bayesian networks, most require a local installation and significant data manipulation to be practical for a general biologist or clinician. No software pipeline currently exists for interpretation and inference of dynamic Bayesian networks learned from biomedical and clinical data. <b>Results:</b> miniTUBA is a web-based modeling system that allows clinical and biomedical researchers to perform complex medical/clinical inference and prediction using dynamic Bayesian network analysis with temporal datasets. The software allows users to choose different analysis parameters (e.g. Markov lags and prior topology), and continuously update their data and refine their results. miniTUBA can make temporal predictions to suggest interventions based on an automated learning process pipeline using all data provided. Preliminary tests using synthetic data and laboratory research data indicate that miniTUBA accurately identifies regulatory network structures from temporal data. <b>Availability:</b> miniTUBA is available at <inter-ref locator="http://www.minituba.org" locator-type="url">http://www.minituba.org</inter-ref> <b>Contact:</b> <inter-ref locator="yongqunh@med.umich.edu" locator-type="email">yongqunh@med.umich.edu</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2423 http://dx.doi.org/10.1093/bioinformatics/btm372 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24632007-09-17HighWireOUPbioinfo:23:18

Robust smooth segmentation approach for array CGH data analysis Huang, Jian Gusnanto, Arief O'Sullivan, Kathleen Staaf, Johan Borg, Åke Pawitan, Yudi DATA AND TEXT MINING <b>Motivation:</b> Array comparative genomic hybridization (aCGH) provides a genome-wide technique to screen for copy number alteration. The existing segmentation approaches for analyzing aCGH data are based on modeling data as a series of discrete segments with unknown boundaries and unknown heights. Although the biological process of copy number alteration is discrete, in reality a variety of biological and experimental factors can cause the signal to deviate from a stepwise function. To take this into account, we propose a smooth segmentation (smoothseg) approach. <b>Methods:</b> To achieve a robust segmentation, we use a doubly heavy-tailed random-effect model. The first heavy-tailed structure on the errors deals with outliers in the observations, and the second deals with possible jumps in the underlying pattern associated with different segments. We develop a fast and reliable computational procedure based on the iterative weighted least-squares algorithm with band-limited matrix inversion. <b>Results:</b> Using simulated and real data sets, we demonstrate how smoothseg can aid in identification of regions with genomic alteration and in classification of samples. For the real data sets, smoothseg leads to smaller false discovery rate and classification error rate than the circular binary segmentation (CBS) algorithm. In a realistic simulation setting, smoothseg is better than wavelet smoothing and CBS in identification of regions with genomic alterations and better than CBS in classification of samples. For comparative analyses, we demonstrate that segmenting the <it>t</it>-statistics performs better than segmenting the data. <b>Availability:</b> The R package <ty>smoothseg</ty> to perform smooth segmentation is available from <inter-ref locator="http://www.meb.ki.se/~yudpaw" locator-type="url">http://www.meb.ki.se/~yudpaw</inter-ref> <b>Contact:</b> <inter-ref locator="yudi.pawitan@ki.se" locator-type="email">yudi.pawitan@ki.se</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2463 http://dx.doi.org/10.1093/bioinformatics/btm359 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24772007-09-17HighWireOUPbioinfo:23:18

Medline search engine for finding genetic markers with biological significance Xuan, Weijian Wang, Pinglang Watson, Stanley J. Meng, Fan DATA AND TEXT MINING <b>Motivation:</b> Genome-wide high density SNP association studies are expected to identify various SNP alleles associated with different complex disorders. Understanding the biological significance of these SNP alleles in the context of existing literature is a major challenge since existing search engines are not designed to search literature for SNPs or other genetic markers. The literature mining of gene and protein functions has received significant attention and effort while similar work on genetic markers and their related diseases is still in its infancy. Our goal is to develop a web-based tool that facilitates the mining of Medline literature related to genetic studies and gene/protein function studies. Our solution consists of four main function modules for (1) identification of different types of genetic markers or genetic variations in Medline records (2) distinguishing positive versus negative linkage or association between genetic markers and diseases (3) integrating marker genomic location data from different databases to enable the retrieval of Medline records related to markers in the same linkage disequilibrium region (4) and a web interface called MarkerInfoFinder to search, display, sort and download Medline citation results. Tests using published data suggest MarkerInfoFinder can significantly increase the efficiency of finding genetic disorders and their underlying molecular mechanisms. The functions we developed will also be used to build a knowledge base for genetic markers and diseases. <b>Availability:</b> The MarkerInfoFinder is publicly available at: <inter-ref locator="http://brainarray.mbni.med.umich.edu/brainarray/datamining/MarkerInfoFinder" locator-type="url">http://brainarray.mbni.med.umich.edu/brainarray/datamining/MarkerInfoFinder</inter-ref> <b>Contact:</b> <inter-ref locator="mengf@umich.edu" locator-type="email">mengf@umich.edu</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2477 http://dx.doi.org/10.1093/bioinformatics/btm375 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24492007-09-17HighWireOUPbioinfo:23:18

An approach to predict transcription factor DNA binding site specificity based upon gene and transcription factor functional categorization Qian, Ziliang Lu, Lingyi Liu, XiaoJun Cai, Yu-Dong Li, Yixue DATA AND TEXT MINING <b>Motivation:</b> To understand transcription regulatory mechanisms, it is indispensable to investigate transcription factor (TF) DNA binding preferences. We noted that the generally acknowledged information of functional annotations of TFs as well as that of their target genes should provide useful hints in determining TF DNA binding preferences. <b>Results:</b> In this contribution, we developed an integrative method based on the Nearest Neighbor Algorithm, to predict DNA binding preferences through integrating both the functional/structural information of TFs and the interaction between TFs and their targets. The accuracy of cross-validation tests on the dataset consisting of 3430 positive samples and 7000 negative samples reaches 87.0 % for 10-fold cross-validation and 87.9 % for jackknife cross-validation test, which is a much better result than that in our previous work. The prediction result indicates that the improved method we developed could be a powerful approach to infer the TF DNA preference <it>in silico</it>. <b>Contact:</b> <inter-ref locator="cyd@picb.ac.cn" locator-type="email">cyd@picb.ac.cn</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2449 http://dx.doi.org/10.1093/bioinformatics/btm348 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24702007-09-17HighWireOUPbioinfo:23:18

Analysis of array CGH data for cancer studies using fused quantile regression Li, Youjuan Zhu, Ji DATA AND TEXT MINING <b>Motivation:</b> The identification of DNA copy number changes provides insights that may advance our understanding of initiation and progression of cancer. Array-based comparative genomic hybridization (array-CGH) has emerged as a technique allowing high-throughput genome-wide scanning for chromosomal aberrations. A number of statistical methods have been proposed for the analysis of array-CGH data. In this article, we consider a fused quantile regression model based on three motivations: (1) quantile regression may provide a more comprehensive picture for the ratio profile of copy numbers than the standard mean regression approach; (2) for simplicity, most available methods assume uniform spacing between neighboring clones, while incorporating the information of physical locations of clones may be helpful and (3) most current methods have a set of tuning parameters that must be carefully tuned, which introduces complexity to the implementation. <b>Results:</b> We formulate the detection of regions of gains and losses in a fused regularized quantile regression framework, incorporating physical locations of clones. We derive an efficient algorithm that computes the entire solution path for the resulting optimization problem, and we propose a simple estimate for the complexity of the fitted model, which leads to convenient selection of the tuning parameter. Three published array-CGH datasets are used to demonstrate our approach. <b>Availability:</b> R code are available at <inter-ref locator="http://www.stat.lsa.umich.edu/~jizhu/code/cgh/" locator-type="url">http://www.stat.lsa.umich.edu/~jizhu/code/cgh/</inter-ref> <b>Contact:</b> <inter-ref locator="jizhu@umich.edu" locator-type="email">jizhu@umich.edu</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2470 http://dx.doi.org/10.1093/bioinformatics/btm364 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24882007-09-17HighWireOUPbioinfo:23:18

Quality estimation of multiple sequence alignments by Bayesian hypothesis testing Tomovic, Andrija Oakeley, Edward J. SEQUENCE ANALYSIS <b>Summary:</b> In this work we present a web-based tool for estimating multiple alignment quality using Bayesian hypothesis testing. The proposed method is very simple, easily implemented and not time consuming with a linear complexity. We evaluated method against a series of different alignments (a set of random and biologically derived alignments) and compared the results with tools based on classical statistical methods (such as sFFT and csFFT). Taking correlation coefficient as an objective criterion of the true quality, we found that Bayesian hypothesis testing performed better on average than the classical methods we tested. This approach may be used independently or as a component of any tool in computational biology which is based on the statistical estimation of alignment quality. <b>Availability:</b> <inter-ref locator="http://www.fmi.ch/groups/functional.genomics/tool.htm" locator-type="url">http://www.fmi.ch/groups/functional.genomics/tool.htm</inter-ref> <b>Contact:</b> <inter-ref locator="edward.oakeley@fmi.ch" locator-type="email">edward.oakeley@fmi.ch</inter-ref> <b>Supplementary information:</b> Supplementary data are available from <inter-ref locator="http://www.fmi.ch/groups/functional.genomics/tool-Supp.htm" locator-type="url">http://www.fmi.ch/groups/functional.genomics/tool-Supp.htm</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2488 http://dx.doi.org/10.1093/bioinformatics/btm366 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24852007-09-17HighWireOUPbioinfo:23:18

HMMoC a compiler for hidden Markov models Lunter, Gerton SEQUENCE ANALYSIS <b>Summary:</b> Hidden Markov models are widely applied within computational biology. The large data sets and complex models involved demand optimized implementations, while efficient exploration of model space requires rapid prototyping. These requirements are not met by existing solutions, and hand-coding is time-consuming and error-prone. Here, I present a compiler that takes over the mechanical process of implementing HMM algorithms, by translating high-level XML descriptions into efficient C++ implementations. The compiler is highly customizable, produces efficient and bug-free code, and includes several optimizations. <b>Availability:</b> <inter-ref locator="http://genserv.anat.ox.ac.uk/software" locator-type="url">http://genserv.anat.ox.ac.uk/software</inter-ref> <b>Contact:</b> <inter-ref locator="gerton.lunter@dpag.ox.ac.uk" locator-type="email">gerton.lunter@dpag.ox.ac.uk</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2485 http://dx.doi.org/10.1093/bioinformatics/btm350 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24552007-09-17HighWireOUPbioinfo:23:18

Mining complex genotypic features for predicting HIV-1 drug resistance Saigo, Hiroto Uno, Takeaki Tsuda, Koji DATA AND TEXT MINING <b>Motivation:</b> Human immunodeficiency virus type 1 (HIV-1) evolves in human body, and its exposure to a drug often causes mutations that enhance the resistance against the drug. To design an effective pharmacotherapy for an individual patient, it is important to accurately predict the drug resistance based on genotype data. Notably, the resistance is not just the simple sum of the effects of all mutations. Structural biological studies suggest that the association of mutations is crucial: even if mutations A or B alone do not affect the resistance, a significant change might happen when the two mutations occur together. Linear regression methods cannot take the associations into account, while decision tree methods can reveal only limited associations. Kernel methods and neural networks implicitly use all possible associations for prediction, but cannot select salient associations explicitly. <b>Results:</b> Our method, <it>itemset boosting</it>, performs linear regression in the complete space of power sets of mutations. It implements a forward feature selection procedure where, in each iteration, one mutation combination is found by an efficient branch-and-bound search. This method uses all possible combinations, and salient associations are explicitly shown. In experiments, our method worked particularly well for predicting the resistance of nucleotide reverse transcriptase inhibitors (NRTIs). Furthermore, it successfully recovered many mutation associations known in biological literature. <b>Availability:</b> <inter-ref locator="http://www.kyb.mpg.de/bs/people/hiroto/iboost/" locator-type="url">http://www.kyb.mpg.de/bs/people/hiroto/iboost/</inter-ref> <b>Contact:</b> <inter-ref locator="koji.tsuda@tuebingen.mpg.de" locator-type="email">koji.tsuda@tuebingen.mpg.de</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2455 http://dx.doi.org/10.1093/bioinformatics/btm353 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24912007-09-17HighWireOUPbioinfo:23:18

Con-Struct Map: a comparative contact map analysis tool Chung, Jo-Lan Beaver, John E. Scheeff, Eric D. Bourne, Philip E. STRUCTURAL BIOINFORMATICS <b>Summary:</b> Con-Struct Map is a graphical tool for the comparative study of protein structures. The tool detects potential conserved residue contacts shared by multiple protein structures by superimposing their contact maps according to a multiple structure alignment. In general, Con-Struct Map allows the study of structural changes resulting from, e.g. sequence substitutions, or alternatively, the study of conserved components of a structure framework across structurally aligned proteins. Specific applications include the study of sequence-structure relationship in distantly related proteins and the comparisons of wild type and mutant proteins. <b>Availability:</b> <inter-ref locator="http://pdbrs3.sdsc.edu/ConStructMap/viewer_argument_generator/singleArguments" locator-type="url">http://pdbrs3.sdsc.edu/ConStructMap/viewer_argument_generator/singleArguments</inter-ref> <b>Contact:</b> <inter-ref locator="bourne@sdsc.edu" locator-type="email">bourne@sdsc.edu</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2491 http://dx.doi.org/10.1093/bioinformatics/btm356 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/25012007-09-17HighWireOUPbioinfo:23:18

EcoProDB: the Escherichia coli protein database Yun, Hongseok Lee, Jeong Wook Jeong, Joonwoo Chung, Jaesung Park, Jong Myoung Myoung, Han Na Lee, Sang Yup DATABASES AND ONTOLOGIES <b>Summary:</b> EcoProDB is a web-based database for comparative proteomics of <it>Escherichia coli</it>. The database contains information on <it>E. coli</it> proteins identified on 2D gels along with other resources collected from various databases and published literature, with a special feature of showing the expression levels of <it>E. coli</it> proteins under different genetic and environmental conditions. It also provides comparative information of subcellular localization, theoretical 2D map, experimental 2D map and integrated protein information via an interactive web interface and application such as the Map Browser. Users can also upload their own 2D gels, extract core information associated with the proteins and 2D gel results from different experiments and consequently generate new knowledge and hypotheses for further studies. <b>Availability:</b> EcoProDB database system is accessible at <inter-ref locator="http://eecoli.kaist.ac.kr" locator-type="url">http://eecoli.kaist.ac.kr</inter-ref> <b>Contact:</b> <inter-ref locator="leesy@kaist.ac.kr" locator-type="email">leesy@kaist.ac.kr</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2501 http://dx.doi.org/10.1093/bioinformatics/btm351 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24932007-09-17HighWireOUPbioinfo:23:18

RefPlus: an R package extending the RMA Algorithm Harbron, Chris Chang, Kai-Ming South, Marie C. GENE EXPRESSION <b>Summary:</b> RMA has become a widely used methodology to pre-process Affymetrix gene expression microarrays. A limitation of RMA is that the calculated probeset intensities change when a set of microarrays is re-pre-processed after the inclusion of additional microarrays into the analysis set. Here we report the availability of the RefPlus package containing functions to perform the Extrapolation Strategy and Extrapolation Averaging algorithms which address these issues. <b>Availability:</b> The software is implemented in the R language and can be downloaded from the Bioconductor project website (<inter-ref locator="http://www.bioconductor.org" locator-type="url">http://www.bioconductor.org</inter-ref>). <b>Contact:</b> <inter-ref locator="Chris.Harbron@AstraZeneca.Com" locator-type="email">Chris.Harbron@AstraZeneca.Com</inter-ref> <b>Supplementary information:</b> Further details of the workings and evaluation of these functions are given in the documentation available on the Bioconductor website. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2493 http://dx.doi.org/10.1093/bioinformatics/btm357 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24982007-09-17HighWireOUPbioinfo:23:18

sMOL Explorer: an open source, web-enabled database and exploration tool for Small MOLecules datasets Ingsriswang, Supawadee Pacharawongsakda, Eakasit DATA AND TEXT MINING <b>Summary:</b> sMOL Explorer is a 2D ligand-based computational tool that provides three major functionalities: data management, information retrieval and extraction and statistical analysis and data mining through Web interface. With sMOL Explorer, users can create personal databases by adding each small molecule via a drawing interface or uploading the data files from internal and external projects into the sMOL database. Then, the database can be browsed and queried with textual and structural similarity search. The molecule can also be submitted to search against external public databases including PubChem, KEGG, DrugBank and eMolecules. Moreover, users can easily access a variety of data mining tools from Weka and R packages to perform analysis including (1) finding the frequent substructure, (2) clustering the molecular fingerprints, (3) identifying and removing irrelevant attributes from the data and (4) building the classification model of biological activity. <b>Availability:</b> sMOL Explorer is an Open Source project and is freely available to all interested users at <inter-ref locator="http://www.biotec.or.th/ISL/SMOL/" locator-type="url">http://www.biotec.or.th/ISL/SMOL/</inter-ref> <b>Contact:</b> <inter-ref locator="supawadee@biotec.or.th" locator-type="email">supawadee@biotec.or.th</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2498 http://dx.doi.org/10.1093/bioinformatics/btm363 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/25042007-09-17HighWireOUPbioinfo:23:18

A Laboratory Information Management System (LIMS) for a high throughput genetic platform aimed at candidate gene mutation screening Voegele, C. Tavtigian, S.V. de Silva, D. Cuber, S. Thomas, A. Le Calvez-Kelm, F. DATABASES AND ONTOLOGIES <b>Summary:</b> High throughput mutation screening in an automated environment generates large data sets that have to be organized and stored reliably. Complex multistep workflows require strict process management and careful data tracking. We have developed a Laboratory Information Management Systems (LIMS) tailored to high throughput candidate gene mutation scanning and resequencing that respects these requirements. Designed with a client/server architecture, our system is platform independent and based on open-source tools from the database to the web application development strategy. Flexible, expandable and secure, the LIMS, by communicating with most of the laboratory instruments and robots, tracks samples and laboratory information, capturing data at every step of our automated mutation screening workflow. An important feature of our LIMS is that it enables tracking of information through a laboratory workflow where the process at one step is contingent on results from a previous step. <b>Availability:</b> Script for MySQL database table creation and source code of the whole JSP application are freely available on our website: <inter-ref locator="http://www-gcs.iarc.fr/lims/" locator-type="url">http://www-gcs.iarc.fr/lims/</inter-ref>. <b>Contact:</b> <inter-ref locator="voegele@iarc.fr" locator-type="email">voegele@iarc.fr</inter-ref> <b>Supplementary information:</b> System server configuration, database structure and additional details on the LIMS and the mutation screening workflow are available on our website: <inter-ref locator="http://www-gcs.iarc.fr/lims/" locator-type="url">http://www-gcs.iarc.fr/lims/</inter-ref> Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2504 http://dx.doi.org/10.1093/bioinformatics/btm365 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:23/18/24952007-09-17HighWireOUPbioinfo:23:18

APID2NET: unified interactome graphic analyzer Hernandez-Toro, Juan Prieto, Carlos De Las Rivas, Javier SYSTEMS BIOLOGY <b>Motivation:</b> Exploration and analysis of interactome networks at systems level requires unification of the biomolecular elements and annotations that come from many different high-throughput or small-scale proteomic experiments. Only such integration can provide a non-redundant and consistent identification of proteins and interactions. APID2NET is a new tool that works with Cytoscape to allow surfing unified interactome data by querying APID server (<inter-ref locator="http://bioinfow.dep.usal.es/apid/" locator-type="url">http://bioinfow.dep.usal.es/apid/</inter-ref>) to provide interactive analysis of protein–protein interaction (PPI) networks. The program is designed to visualize, explore and analyze the proteins and interactions retrieved, including the annotations and attributes associated to them, such as: GO terms, InterPro domains, experimental methods that validate each interaction, PubMed IDs, UniProt IDs, etc. The tool provides interactive graphical representation of the networks with all Cytoscape capabilities, plus new automatic tools to find concurrent functional and structural attributes along all protein pairs in a network. <b>Availability:</b> <inter-ref locator="http://bioinfow.dep.usal.es/apid/apid2net.html" locator-type="url">http://bioinfow.dep.usal.es/apid/apid2net.html</inter-ref> <b>Contact:</b> <inter-ref locator="jrivas@usal.es" locator-type="email">jrivas@usal.es</inter-ref> <b>Supplementary information:</b> Installation Guide and User's Guide are supplied at the Web site indicated above. Oxford University Press 2007-09-17 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/23/18/2495 http://dx.doi.org/10.1093/bioinformatics/btm373 en Copyright (C) 2007, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/4652006-11-07HighWireOUPbioinfo:10:5

Identification of a set of frequent decanucleotides in plants and in animals Scapoli, C. Rodríguez-Larralde, A. Volinia, S. Beretta, M. Barrai, I. ORIGINAL PAPERS We studied the frequency distribution of 1048576 oligo-nucleotides 10 bp long in a sample of 1.961 Mbase of genes from plants, made of 635 sequences extracted from GenBank 71.0, with the aim of detecting transcription control signals. Among all decamers, 3255, or 0.3&percnt;, had a frequency 10 times higher than the mean and were subjected to further statistical analysis. For each of the 3255 decamers (parents), we counted the individual frequencies of the 30 decamers (progeny) differing from the parent by one base mutation, and calculated two variance&sol;mean chi-squares for the progeny, with and without the parent decamer. By studying the distribution of the ratio between the two chi-squares we observed that out of 3255 decamers >10 times frequent than average, 432 had a chi-square ratio >1.9. In this residual set, which corresponds to <0.04 per cent of all possible decamers, only 15 known eukaryotic transcription control elements were found; on the other hand, it included 29 decanucleotides that matched with decanucleotides of a set of Drosophila, 24 with a set from mammals, 13 with a set from yeast and four with a set of viruses—all sets identified with the statistical procedures here described. These decanucloetides are highly repetitive and seem to be present throughout all higher organisms, whereas they are uncommon in mammalian viruses. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/465 http://dx.doi.org/10.1093/bioinformatics/10.5.465 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/4712006-11-07HighWireOUPbioinfo:10:5

Rapid numerical integration algorithm for finding the equilibrium state of a system of coupled binding reactions Bray, Dennis Lay, Steven ORIGINAL PAPERS We have adapted a simple method of numerical integration to predict the equilibrium state of a population of components undergoing reversible association according to the Law of Mass Action. Its particular application is to populations of protein molecules in aqueous solution. The method is based on Euler integration but employs an adaptive step size: the time increment being reduced if it would make the concentration of any component negative and increased while the concentration of any component changes at greater than a specified rate. Parameters of the algorithm have been optimized empirically using a model set of binding equilibria with dissociation constants ranging from 10−5 M to 10−9 M. The method obtains the solution to a set of binding equilibria more rapidly than the conventional initial value methods (simple Euler, 4th order Runge-Kutta and variable-step Runge-Kutta methods were tested) for the same accuracy. A computer code in standard C is presented. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/471 http://dx.doi.org/10.1093/bioinformatics/10.5.471 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/4772006-11-07HighWireOUPbioinfo:10:5

BIOESTIM: software for automatic design of estimators in bioprocess engineering Farza, Mondher Chéruy, Arlette ORIGINAL PAPERS This paper describes BIOESTIM, a software package devoted to on-line estimation in bioprocess engineering. BIOESTIM enables bioengineers automatically to design state and parameter estimators from a minimal knowledge of the process kinetics. Such estimators allow development of software sensors capable of coping with the lack of reliable instrumentation suited to real-time monitoring. The estimator building procedure through BIOESTIM starts up from a dynamical material balance model of the bioprocess. This model, supplied by the user, is next completed by other information with no requirement for numerical values: the user has only to specify available measurements, coupled reactions and the known yield coefficients. On the base of this knowledge, BIOESTIM proceeds to symbolic algebraic manipulations on the model in order to study estimation possibilities and check identifiability of yield coefficients. When the design of an estimator is possible, the corresponding equations are automatically generated. Moreover, these estimators are stored in a user-specified file which is automatically interfaced with a specialized simulation software including data treatment and numerical integration packages. Thus, the user can simulate the estimator performances under various operational conditions using available experimental measurements. A typical example dealing with microbial growth and biosynthesis reactions is given in order to illustrate the main functional capabilities of BIOESTIM. BIOESTIM has been designed and written in a modular fashion. The module dealing with estimators design makes use of symbolic computation; it is written in Mathematica and runs on every computer on which this language is available. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/477 http://dx.doi.org/10.1093/bioinformatics/10.5.477 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/4892006-11-07HighWireOUPbioinfo:10:5

An algorithm to determine protein sequence alignment by utilizing data obtained from a peptide mixture and individual peptides Caporale, Carlo Sepe, Ciro Caruso, Carla Petrilli, Pasquale Buonocore, Vincenzo ORIGINAL PAPERS With the aim of limiting peptide purification steps and unambiguously ascertaining protein sequences, we have designed and implemented on a personal computer an algorithm to determine sequence alignment by utilizing data obtained from automatic Edman degradation performed on a single peptide mixture and individual peptides. The protein under study is digested by two different hydrolysis methods and fragments are just isolated from one mixture and sequenced, while the second mixture is submitted unfractionated to sequence analysis. The algorithm provides for the exact alignment of the individual peptides using the mixture data for the overlapping. We report an example of application of this approach by utilizing experimental data obtained from a protein of known sequence. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/489 http://dx.doi.org/10.1093/bioinformatics/10.5.489 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/4952006-11-07HighWireOUPbioinfo:10:5

An Excel spreadsheet computer program combining algorithms for prediction of protein structural characteristics Clotet, Josep Cedano, Juan Querol, Enrique ORIGINAL PAPERS A program running on personal computers (either Apple Macintosh or PC, using Excel worksheets) for the prediction of some protein structural characteristics is reported. The program runs according to the Chou and Fasman algorithm, with some modifications, for secondary structure prediction. The program also incorporates several complementary analyses for secondary structure prediction to help the user in the decision-making process: rules for amino acid preferences in the N-cap and C-cap of α-helices; prediction of the protein structural class and search of sequential motifs related to secondary structure. Additional algorithms performed by the program are: prediction of domain boundaries, prediction of loops, prediction of the state of cysteines (reduced or in disulfide bridge), hydropathy profiles according to Kyte and Doolittle, Hoop and Woods, and flexibility plot according to Karplus and Schulz. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/495 http://dx.doi.org/10.1093/bioinformatics/10.5.495 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5012006-11-07HighWireOUPbioinfo:10:5

A set of Alu-free frequent decamers from mammalian genomes enriched in transcription factor signals Gambari, R. Volinia, S. Nesti, C. Scapoli, C. Barrai, I. ORIGINAL PAPERS We have recently reported that the statistical analysis of the frequency distribution of short oligonucleotides within mammalian and viral genomes allows the production of sets of DNA sequences enriched in signals for transcription factors. Such statistical approaches could facilitate the identification of new promoter regions playing a role in the transcriptional regulation of gene expression. In the case of mammalian oligonucleotides, we found that the published set of frequent decamers enriched in transcriptional motifs is not suitable for studies on genes of Homo sapiens and evolutionarily related genomes, because it contains decameric sequences belonging to genomic repeats. We report here that most of the decameric sequences of DNA repeats belong to Alu repeats. Accordingly, we produced a subset of Alu-free frequent decamers. In addition, we eliminated from the subset of Alu-free frequent decamers those that are frequently present within other common human repeats, including (GT)<inf>n</inf>, (AT)<inf>n</inf>, (CA)<inf>n</inf>, (ATT)<inf>n</inf>, (CAA)<inf>n</inf> and (GTT)<inf>n</inf>. The Alu-free (repeats-free) subset of frequent mammalian decamers is enriched in signals for transcription factors and allows the identification of putative signals in genes, such as those coding for plasminogen activator, adenosine deaminase and p53, that contain a large number of Alu-like repeats interspersed within our genomic sequences. The newly generated compilation of frequent decamers described here might be used to locate genomic regions playing functional roles in the expression of genes of Homo sapiens and related primates. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/501 http://dx.doi.org/10.1093/bioinformatics/10.5.501 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5092006-11-07HighWireOUPbioinfo:10:5

On an efficient parallelization of exhaustive sequence comparison algorithms on message passing architectures Trelles-Salazar, O. Zapata, E.L. Carazo, J.M. ORIGINAL PAPERS We present a new parallel computing approach to the case of exhaustive sequential sequence comparison algorithms on message-passing architectures. In this context a modification of guided self-scheduling as well as efficient buffering strategies are presented. We discuss two specific implementations, one on the Paramid parallel computer, and the other on a cluster of workstations running PVM. In both cases the parallel performance is higher than with any other method presented so far. The code is public domain and can be obtained by anonymous ftp at ftp.cnb.uam.es. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/509 http://dx.doi.org/10.1093/bioinformatics/10.5.509 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5132006-11-07HighWireOUPbioinfo:10:5

Maximum likelihood estimation of quantitative trait loci parameters with the aid of genetic markers using a standard statistical package Elkind, Y. Nir, B. Weller, J.I. ORIGINAL PAPERS Consistent parameter estimates of quantitative trait loci linked to genetic markers can be derived by maximum likelihood methodology. For many experimental designs of interest, parameter estimates and their standard errors can be obtained by program LE of BMDP, which uses the Newton–Raphson method of iteration. Program LE was tested on data simulated for a backcross between two inbred lines. A single quantitative trait locus linked to either one or two genetic markers was simulated. Convergence was rapid, and computing and programming time were insignificant. All parameter estimates were within the expected bounds. Many different designs can be readily analyzed. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/513 http://dx.doi.org/10.1093/bioinformatics/10.5.513 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5192006-11-07HighWireOUPbioinfo:10:5

A new concept of sequence data distribution on wide area networks Heumann, K. George, D. Mewes, H.-W. ORIGINAL PAPERS Accepted concepts in distributed applications design have been applied in the development of a network-based system for the synchronization of remote sequence database access sites by an incremental update mechanism. Computer hardware requirements, network bandwidth, and stability considerations make centralized access to essential computerized resources undesirable. A network model has been developed to distribute access over a collection of remotely situated computer centers. The formally independent database-access nodes join to form a heterogeneous, long distance, co-operating network that can compensate for the deficiencies of unstable network links thereby ensuring uninterrupted access to the resource. In order to guarantee consistency among these nodes, several distributed transaction protocols have been investigated; based on these results, a prototype system has been implemented. A layered software architecture makes the distributed transaction protocol transparent to the individual database system and the underlying network. Individual components of this network communicate by means of Remote Procedure Calls (RPCs). A prototype software system operates to synchronize up to date copies of the PIR-International Protein Sequence Database (Barker et al., 1993) at a number of different sites using the public Internet as the transport vehicle. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/519 http://dx.doi.org/10.1093/bioinformatics/10.5.519 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5272006-11-07HighWireOUPbioinfo:10:5

A consensus procedure for predicting the location of {alpha}-Helical transmembrane segments in proteins Parodi, L.A. Granatir, C.A. Maggiora, G.M. ORIGINAL PAPERS To aid in the development of three-dimensional models of membrane-bound proteins, a consensus procedure for predicting α-helical transmembrane segments from amino acid sequences is presented. The algorithm combines the results of six individual prediction methods and some basic properties of membrane-spanning helices to obtain a final concensus prediction. Comparison with experiment and several other recently developed methods shows that the consensus procedure performs quite well in comparison to other recent methods. A FORTRAN program has been developed which takes an input file containing an amino acid sequence in one-letter code and outputs a list of the α-helical transmembrane segments predicted by the consensus algorithm. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/527 http://dx.doi.org/10.1093/bioinformatics/10.5.527 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5372006-11-07HighWireOUPbioinfo:10:5

VISA: Visual Sequence Analysis for the comparison of multiple amino acid sequences Pósfai, János Száraz, Zoltán Roberts, Richard J. ORIGINAL PAPERS VISA (VIsual Sequence Analysis) is a software package that displays global similarities within a set of related protein sequences. The program identifies amino acid patterns that are common to many members of the set of sequences and displays them as a series of histograms. Individual peaks on the display can be assigned a color and analogous peaks in the other sequences are then automatically marked in the same color. This can be repeated for each significant peak and leads to a display in which major matching segments of multiple amino acid sequences appear as dominant peaks of the histograms with matching colors. These peaks usually correspond to the conserved sequence motifs that are characteristic of particular proteins. An extensive set of software tools is included to help the localization, visualization and analysis of the global similarities displayed. VISA provides a graphic overview of the sequence similarity that can help to understand the architecture of the protein family and can be helpful while designing experiments to probe function. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/537 http://dx.doi.org/10.1093/bioinformatics/10.5.537 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5452006-11-07HighWireOUPbioinfo:10:5

PdbMotif - A tool for the automatic identification and display of motifs in protein structures Saqi, Monsoor A. S. Sayle, Roger COMMUNICATIONS A program PdbMotif, which automatically identifies protein motifs in a protein data bank file and generates a script file which can be read directly by the molecular rendering program RasMol, is described. PdbMotif accepts the standard PROSITE pattern syntax and will scan the PROSITE pattern database or a set of user defined patterns. Any motifs detected are automatically highlighted in the RasMol image. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/545 http://dx.doi.org/10.1093/bioinformatics/10.5.545 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5472006-11-07HighWireOUPbioinfo:10:5

Gnome - an Internet-based sequence analysis tool Nakai, Kenta Tokimori, Takeo Ogiwara, Atsushi Uchiyama, Ikuo Niiyama, Toshiyuki COMMUNICATIONS Gnome (GenomeNet Open Mail-service Environment) is a sequence analysis tool that enables an end-user to make use of several Internet- (mainly e-mail) based services with an easy-to-use graphical user interface. Users can conduct homology and motif searches, and database-entry retrieval against the latest databases by emitting search requests to and receiving their results from a search-server by e-mail. The search results are viewed and managed efficiently with this system. The Macintosh and X (Motif) versions of the Gnome client and the UNIX version of the Gnome server are available to academic users free of charge. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/547 http://dx.doi.org/10.1093/bioinformatics/10.5.547 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5512006-11-07HighWireOUPbioinfo:10:5

Navigating the Brookhaven Protein Data Bank Walsh, L.L. COMMUNICATIONS The Protein Data Bank maintained at Brookhaven National Laboratories has expanded to the point where even experienced users have difficulty understanding, exploring, and exploiting it. This paper describes a text file, an annotation of the Protein Data Bank, which helps users find information on related files and structures. The most recent version of this file includes information on homologous structures, including both sequence homology and structural homology. This file is in ASCII format and is available electronically. It is easy to search locally on any type of computer, using an editor or a pattern-matching program, such as grep. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/551 http://dx.doi.org/10.1093/bioinformatics/10.5.551 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5592006-11-07HighWireOUPbioinfo:10:5

Computing heart rate variability using spectral analysis techniques: HRVUAB, a ready-to-use program Altimiras, J. Feliu, M. Aissaoui, A. Tort, L. COMMUNICATIONS The application of spectral analysis techniques to study the nervous modulation of the vertebrate heart have given interesting results in clinical studies although nearly nothing is known in lower vertebrates. A program to compute this heart rate variability is described in detail and preliminary results are shown. Data is first statistically qualified and fragmented in smaller segments, each being further processed through linear trend removal and normalization before the application of the Fast Fourier Transform algorithm to estimate the interval spectrum. All consecutive periodograms are averaged and the interval spectrum plotted and saved. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/559 http://dx.doi.org/10.1093/bioinformatics/10.5.559 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5632006-11-07HighWireOUPbioinfo:10:5

TRACTOR, a program to locate subclones in a nucleotide sequence using only one sequencing reaction Niemi, J.T. Mäntsälä, P. COMMUNICATIONS The QuickBasic program TRACTOR is used to locate clones in a known sequence using only one sequencing reaction, a method generally known as ‘T-tracking’. The program can reduce workload at the end stage of a sequencing project using the random subcloning strategy. Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/563 http://dx.doi.org/10.1093/bioinformatics/10.5.563 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5672006-11-07HighWireOUPbioinfo:10:5

GenFrag 2.1: new features for more robust fragment assembly benchmarks Engle, Michael L. Burks, Christian APPLICATION NOTES Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/567 http://dx.doi.org/10.1093/bioinformatics/10.5.567 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5692006-11-07HighWireOUPbioinfo:10:5

TREECON for Windows: a software package for the construction and drawing of evolutionary trees for the Microsoft Windows environment Van de Peer, Yves De Wachter, Rupert APPLICATION NOTES Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/569 http://dx.doi.org/10.1093/bioinformatics/10.5.569 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:10/5/5712006-11-07HighWireOUPbioinfo:10:5

Literature Review UPDATE Oxford University Press 1994-09-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/10/5/571 http://dx.doi.org/10.1093/bioinformatics/10.5.571 en Copyright (C) 1994, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/12892006-11-07HighWireOUPbioinfo:22:11

Detection of a tandem BRCT in Nbs1 and Xrs2 with functional implications in the DNA damage response Becker, Emmanuelle Meyer, Vincent Madaoui, Hocine Guerois, Raphaël STRUCTURAL BIOINFORMATICS <b>Motivation:</b> Human Nbs1 and its homolog Xrs2 in <it>Saccharomyces cerevisiae</it> are part of the conserved MRN complex (MRX in yeast) which plays a crucial role in maintaining genomic stability. NBS1 corresponds to the gene mutated in the Nijmegen breakage syndrome (NBS) known as a radiation hyper-sensitive disease. Despite the conservation and the importance of the MRN complex, the high sequence divergence between Nbs1 and Xrs2 precluded the identification of common domains downstream of the N-terminal Fork-Head Associated (FHA) domain. <b>Results:</b> Using HMM–HMM profile comparisons and structure modelling, we assessed the existence of a tandem BRCT in both Nbs1 and Xrs2 after the FHA. The structure-based conservation analysis of the tandem BRCT in Nbs1 supports its function as a phosphoserine binding domain. Remarkably, the 5 bp deletion observed in 95% of NBS patients cleaves the tandem at the linker region while preserving the structural integrity of each BRCT domain in the resulting truncated gene products. <b>Contact:</b> <inter-ref locator="guerois@cea.fr" locator-type="email">guerois@cea.fr</inter-ref> <b>Supplementary information:</b> <inter-ref locator="http://www-spider.cea.fr/Groups/si6661/view.html" locator-type="url">http://www-spider.cea.fr/Groups/si6661/view.html</inter-ref> Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1289 http://dx.doi.org/10.1093/bioinformatics/btl075 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/12932006-11-07HighWireOUPbioinfo:22:11

Convergence of the proteomic pattern in cancer Müller, Ute Ernst, Günther Melle, Christian Guthke, Reinhard von Eggeling, Ferdinand SYSTEMS BIOLOGY <b>Motivation:</b> On the histological level the differentiation of normal epithelial tissues is well known. The phenomenon of dedifferentiation, which occurs as cells develop towards malignancy is also well described. To identify an epithelial tumor-specific proteomic profile as well as to measure the proximities between we used data from tumor tissue and adjacent normal tissue microdissected from head and neck and colon cancer samples which were analyzed using ProteinChip technology and performed a bioinformatic meta-analysis on the resulting four complex datasets. <b>Results:</b> All four groups could be identified based on their proteomic signatures and the tumor tissues were found to be more similar to one another than to the normal epithelial tissue from which they progressed. This study shows at the proteomic level that changes in the histological features of tumors as compared to the tissues from which they arise are reflected in the convergence of proteomic pattern during the development to cancer. <b>Contact:</b> <inter-ref locator="fegg@mti.uni-jena.de" locator-type="email">fegg@mti.uni-jena.de</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1293 http://dx.doi.org/10.1093/bioinformatics/btl077 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/12972006-11-07HighWireOUPbioinfo:22:11

Cyanobacterial response regulator PatA contains a conserved N-terminal domain (PATAN) with an alpha-helical insertion Makarova, Kira S. Koonin, Eugene V. Haselkorn, Robert Galperin, Michael Y. SEQUENCE ANALYSIS The cyanobacterium <it>Anabaena</it> (<it>Nostoc</it>) PCC 7120 responds to starvation for nitrogen compounds by differentiating approximately every 10th cell in the filament into nitrogen-fixing cells called heterocysts. Heterocyst formation is subject to complex regulation, which involves an unusual response regulator PatA that contains a CheY-like phosphoacceptor (receiver, REC) domain at its C-terminus. PatA-like response regulators are widespread in cyanobacteria; one of them regulates phototaxis in <it>Synechocystis</it> PCC 6803. Sequence analysis of PatA revealed, in addition to the REC domain, a previously undetected, conserved domain, which we named PATAN (after PatA N-terminus), and a potential helix–turn–helix (HTH) domain. PATAN domains are encoded in a variety of environmental bacteria and archaea, often in several copies per genome, and are typically associated with REC, Roadblock and other signal transduction domains, or with DNA-binding HTH domains. Many PATAN domains contain insertions of a small additional domain, termed <it>α</it>-clip, which is predicted to form a four-helix bundle. PATAN domains appear to participate in protein–protein interactions that regulate gliding motility and processes of cell development and differentiation in cyanobacteria and some proteobacteria, such as <it>Myxococcus xanthus</it> and <it>Geobacter sulfurreducens</it>. <b>Contact</b>: <inter-ref locator="galperin@ncbi.nlm.nih.gov" locator-type="email">galperin@ncbi.nlm.nih.gov</inter-ref> <b>Supplementary information:</b> <inter-ref locator="http://www.ncbi.nlm.nih.gov/Complete_Genomes/SigCensus/PATAN.html" locator-type="url">http://www.ncbi.nlm.nih.gov/Complete_Genomes/SigCensus/PATAN.html</inter-ref> Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1297 http://dx.doi.org/10.1093/bioinformatics/btl096 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/13022006-11-07HighWireOUPbioinfo:22:11

A generalization of the PST algorithm: modeling the sparse nature of protein sequences Leonardi, Florencia G. SEQUENCE ANALYSIS <b>Motivation:</b> A central problem in genomics is to determine the function of a protein using the information contained in its amino acid sequence. Variable length Markov chains (VLMC) are a promising class of models that can effectively classify proteins into families and they can be estimated in linear time and space. <b>Results:</b> We introduce a new algorithm, called Sparse Probabilistic Suffix Trees (SPST), that identifies equivalences between the contexts of a VLMC. We show that, in many cases, the identification of these equivalences can improve the classification rate of the classical Probabilistic Suffix Trees (PST) algorithm. We also show that better classification can be achieved by identifying representative fingerprints in the amino acid chains, and this variation in the SPST algorithm is called F-SPST. <b>Availability:</b> The SPST algorithm can be freely downloaded from the site <inter-ref locator="http://www.ime.usp.br/~leonardi/spst/" locator-type="url">http://www.ime.usp.br/~leonardi/spst/</inter-ref> <b>Contact:</b> <inter-ref locator="leonardi@ime.usp.br" locator-type="email">leonardi@ime.usp.br</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1302 http://dx.doi.org/10.1093/bioinformatics/btl088 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/13082006-11-07HighWireOUPbioinfo:22:11

Using hidden Markov models and observed evolution to annotate viral genomes McCauley, Stephen Hein, Jotun SEQUENCE ANALYSIS <b>Motivation:</b> ssRNA (single stranded) viral genomes are generally constrained in length and utilize overlapping reading frames to maximally exploit the coding potential within the genome length restrictions. This overlapping coding phenomenon leads to complex evolutionary constraints operating on the genome. In regions which code for more than one protein, silent mutations in one reading frame generally have a protein coding effect in another. To maximize coding flexibility in all reading frames, overlapping regions are often compositionally biased towards amino acids which are 6-fold degenerate with respect to the 64 codon alphabet. Previous methodologies have used this fact in an <it>ad hoc</it> manner to look for overlapping genes by motif matching. In this paper differentiated nucleotide compositional patterns in overlapping regions are incorporated into a probabilistic hidden Markov model (HMM) framework which is used to annotate ssRNA viral genomes. This work focuses on single sequence annotation and applies an HMM framework to ssRNA viral annotation. A description of how the HMM is parameterized, whilst annotating within a missing data framework is given. A Phylogenetic HMM (Phylo-HMM) extension, as applied to 14 aligned HIV2 sequences is also presented. This evolutionary extension serves as an illustration of the potential of the Phylo-HMM framework for ssRNA viral genomic annotation. <b>Results:</b> The single sequence annotation procedure (SSA) is applied to 14 different strains of the HIV2 virus. Further results on alternative ssRNA viral genomes are presented to illustrate more generally the performance of the method. The results of the SSA method are encouraging however there is still room for improvement, and since there is overwhelming evidence to indicate that comparative methods can improve coding sequence (CDS) annotation, the SSA method is extended to a Phylo-HMM to incorporate evolutionary information. The Phylo-HMM extension is applied to the same set of 14 HIV2 sequences which are pre-aligned. The performance improvement that results from including the evolutionary information in the analysis is illustrated. <b>Availability:</b> We implement the SSA method in the MATLAB programming language and provide the source code at <inter-ref locator="http://www.stats.ox.ac.uk/Qmccauley" locator-type="url">http://www.stats.ox.ac.uk/Qmccauley</inter-ref>. Additional supplementary material referred to in the text is available on the same webpage. <b>Contact:</b> <inter-ref locator="mccauley@stats.ox.ac.uk" locator-type="email">mccauley@stats.ox.ac.uk</inter-ref> <b>Supplementary Information:</b> Supplementary data are available at <inter-ref locator="http://www.stats.ox.ac.uk/Qmccauley" locator-type="url">http://www.stats.ox.ac.uk/Qmccauley</inter-ref> Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1308 http://dx.doi.org/10.1093/bioinformatics/btl092 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/13172006-11-07HighWireOUPbioinfo:22:11

Analysis of internal loops within the RNA secondary structure in almost quadratic time Ogurtsov, Aleksey Y. Shabalina, Svetlana A. Kondrashov, Alexey S. Roytberg, Mikhail A. SEQUENCE ANALYSIS <b>Motivation:</b> Evaluating all possible internal loops is one of the key steps in predicting the optimal secondary structure of an RNA molecule. The best algorithm available runs in time <it>O</it>(<it>L</it>3), <it>L</it> is the length of the RNA. <b>Results:</b> We propose a new algorithm for evaluating internal loops, its run-time is <it>O</it>(<it>M</it>*log2<it>L</it>), <it>M</it> <it><</it> <it>L2</it> is a number of possible nucleotide pairings. We created a software tool Afold which predicts the optimal secondary structure of RNA molecules of lengths up to 28 000 nt, using a computer with 2 Gb RAM. We also propose algorithms constructing sets of conditionally optimal multi-branch loop free (MLF) structures, e.g. the set that for every possible pairing (<it>x</it>, <it>y</it>) contains an optimal MLF structure in which nucleotides <it>x</it> and <it>y</it> form a pair. All the algorithms have run-time <it>O</it>(<it>M</it>*log2<it>L</it>). <b>Availability:</b> Executables of Afold software tool, precompiled for Linux and Windows, are available at <inter-ref locator="ftp://ftp.ncbi.nlm.nih.gov/pub/ogurtsov/Afold" locator-type="url">ftp://ftp.ncbi.nlm.nih.gov/pub/ogurtsov/Afold</inter-ref>. <b>Contact:</b> <inter-ref locator="MRoytberg@impb.psn.ru" locator-type="email">MRoytberg@impb.psn.ru</inter-ref> <b>Supplementary information:</b> <inter-ref locator="ftp://ftp.ncbi.nlm.nih.gov/pub/ogurtsov/Afold" locator-type="url">ftp://ftp.ncbi.nlm.nih.gov/pub/ogurtsov/Afold</inter-ref> Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1317 http://dx.doi.org/10.1093/bioinformatics/btl083 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/13252006-11-07HighWireOUPbioinfo:22:11

Combining multi-species genomic data for microRNA identification using a Naive Bayes classifier Yousef, Malik Nebozhyn, Michael Shatkay, Hagit Kanterakis, Stathis Showe, Louise C. Showe, Michael K. SEQUENCE ANALYSIS <b>Motivation:</b> Most computational methodologies for microRNA gene prediction utilize techniques based on sequence conservation and/or structural similarity. In this study we describe a new technique, which is applicable across several species, for predicting miRNA genes. This technique is based on machine learning, using the Naïve Bayes classifier. It automatically generates a model from the training data, which consists of sequence and structure information of known miRNAs from a variety of species. <b>Results:</b> Our study shows that the application of machine learning techniques, along with the integration of data from multiple species is a useful and general approach for miRNA gene prediction. Based on our experiments, we believe that this new technique is applicable to an extensive range of eukaryotes' genomes. Specific structure and sequence features are first used to identify miRNAs followed by a comparative analysis to decrease the number of false positives (FPs). The resulting algorithm exhibits higher specificity and similar sensitivity compared to currently used algorithms that rely on conserved genomic regions to decrease the rate of FPs. <b>Availability:</b> The BayesMiRNAfind program is available at <inter-ref locator="http://wotan.wistar.upenn.edu/miRNA" locator-type="url">http://wotan.wistar.upenn.edu/miRNA</inter-ref> <b>Contact:</b> <inter-ref locator="showe@wistar.org" locator-type="email">showe@wistar.org</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1325 http://dx.doi.org/10.1093/bioinformatics/btl094 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/13352006-11-07HighWireOUPbioinfo:22:11

Predicting protein interaction sites: binding hot-spots in protein-protein and protein-ligand interfaces Burgoyne, Nicholas J. Jackson, Richard M. STRUCTURAL BIOINFORMATICS <b>Motivation:</b> Protein assemblies are currently poorly represented in structural databases and their structural elucidation is a key goal in biology. Here we analyse clefts in protein surfaces, likely to correspond to binding ‘hot-spots’, and rank them according to sequence conservation and simple measures of physical properties including hydrophobicity, desolvation, electrostatic and van der Waals potentials, to predict which are involved in binding in the native complex. <b>Results:</b> The resulting differences between predicting binding-sites at protein–protein and protein–ligand interfaces are striking. There is a high level of prediction accuracy (≤93%) for protein–ligand interactions, based on the following attributes: van der Waals potential, electrostatic potential, desolvation and surface conservation. Generally, the prediction accuracy for protein–protein interactions is lower, with the exception of enzymes. Our results show that the ease of cleft desolvation is strongly predictive of interfaces and strongly maintained across all classes of protein-binding interface. <b>Contact:</b> <inter-ref locator="r.m.jackson@leeds.ac.uk" locator-type="email">r.m.jackson@leeds.ac.uk</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1335 http://dx.doi.org/10.1093/bioinformatics/btl079 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/13432006-11-07HighWireOUPbioinfo:22:11

A permissive secondary structure-guided superposition tool for clustering of protein fragments toward protein structure prediction via fragment assembly Wainreb, Gilad Haspel, Nurit Wolfson, Haim J. Nussinov, Ruth STRUCTURAL BIOINFORMATICS <b>Motivation:</b> Secondary-Structure Guided Superposition tool (SSGS) is a permissive secondary structure-based algorithm for matching of protein structures and in particular their fragments. The algorithm was developed towards protein structure prediction via fragment assembly. <b>Results:</b> In a fragment-based structural prediction scheme, a protein sequence is cut into building blocks (BBs). The BBs are assembled to predict their relative 3D arrangement. Finally, the assemblies are refined. To implement this prediction scheme, a clustered structural library representing sequence patterns for protein fragments is essential. To create a library, BBs generated by cutting proteins from the PDB are compared and structurally similar BBs are clustered. To allow structural comparison and clustering of the BBs, which are often relatively short with flexible loops, we have devised SSGS. SSGS maintains high similarity between cluster members and is highly efficient. When it comes to comparing BBs for clustering purposes, the algorithm obtains better results than other, non-secondary structure guided protein superimposition algorithms. <b>Availability:</b> SSGS is available for download at <inter-ref locator="http://www.cs.tau.ac.il/~wainreb" locator-type="url">http://www.cs.tau.ac.il/~wainreb</inter-ref> <b>Contact:</b> <inter-ref locator="ruthn@ncifcrf.gov" locator-type="email">ruthn@ncifcrf.gov</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1343 http://dx.doi.org/10.1093/bioinformatics/btl098 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/13532006-11-07HighWireOUPbioinfo:22:11

Prediction of viable circular permutants using a graph theoretic approach Paszkiewicz, Konrad H. Sternberg, Michael J. E. Lappe, Michael STRUCTURAL BIOINFORMATICS <b>Motivation:</b> In recent years graph-theoretic descriptions have been applied to aid the analysis of a number of complex biological systems. However, such an approach has only just begun to be applied to examine protein structures and the network of interactions between residues with promising results. Here we examine whether a graph measure known as closeness is capable of predicting regions where a protein can be split to form a viable circular permutant. Circular permutants are a powerful experimental tool to probe folding mechanisms and more recently have been used to design split enzyme reporter proteins. <b>Results:</b> We test our method on an extensive set of experiments carried out on dihydrofolate reductase in which circular permutants were constructed for every amino acid position in the sequence, together with partial data from studies on other proteins. Results show that closeness is capable of correctly identifying significantly more residues which are suitable for circular permutation than solvent accessibility. This has potential implications for the design of successful split enzymes having particular importance for the development of protein–protein interaction screening methods and offers new perspectives on protein folding. More generally, the method illustrates the success with which graph-theoretic measures encapsulate the variety of long and short range interactions between residues during the folding process. <b>Contact:</b> <inter-ref locator="konrad.paszkiewicz@imperial.ac.uk" locator-type="email">konrad.paszkiewicz@imperial.ac.uk</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <it>Bioinformatics</it> online. Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1353 http://dx.doi.org/10.1093/bioinformatics/btl095 en Copyright (C) 2006, Oxford University Press

oai:open-archive.highwire.org:bioinfo:22/11/13592006-11-07HighWireOUPbioinfo:22:11

Comparing gene expression networks in a multi-dimensional space to extract similarities and differences between organisms Lelandais, Gaëlle Vincens, Pierre Badel-Chagnon, Anne Vialette, Stéphane Jacq, Claude Hazout, Serge GENE EXPRESSION <b>Motivation:</b> Molecular evolution, which is classically assessed by comparison of individual proteins or genes between species, can now be studied by comparing co-expressed functional groups of genes. This approach, which better reflects the functional constraints on the evolution of organisms, can exploit the large amount of data generated by genome-wide expression analyses. However, it requires new methodologies to represent the data in a more accessible way for cross-species comparisons. <b>Results:</b> In this work, we present an approach based on Multi-dimensional Scaling techniques, to compare the conformation of two gene expression networks, represented in a multi-dimensional space. The expression networks are optimally superimposed, taking into account two criteria: (1) inter-organism orthologous gene pairs have to be nearby points in the final multi-dimensional space and (2) the distortion of the gene expression networks, the organization of which reflects the similarities between the gene expression measurements, has to be circumscribed. Using this approach, we compared the transcriptional programs that drive sporulation in budding and fission yeasts, extracting some common properties and differences between the two species. <b>Availability:</b> The source code is freely distributed to academic users upon request to the authors. More information can be found online at <inter-ref locator="http://www.biologie.ens.fr/lgmgml/publication/comp3d/" locator-type="url">http://www.biologie.ens.fr/lgmgml/publication/comp3d/</inter-ref>. <b>Contact:</b> <inter-ref locator="lelandais@biologie.ens.fr" locator-type="email">lelandais@biologie.ens.fr</inter-ref> <b>Supplementary information:</b> Supplementary data are available at <inter-ref locator="http://www.biologie.ens.fr/lgmgml/publication/comp3d/SupData.php" locator-type="url">http://www.biologie.ens.fr/lgmgml/publication/comp3d/SupData.php</inter-ref> Oxford University Press 2006-06-01 00:00:00.0 TEXT text/html http://bioinformatics.oxfordjournals.org/cgi/content/short/22/11/1359 http://dx.doi.org/10.1093/bioinformatics/btl087 en Copyright (C) 2006, Oxford University Press 1258784899839!0001-01-01!9999-12-31!bioinfo!100!oai_dc