bluuebunny/crossref_metadata_2025 huggingface dataset:
Pre-TCRα and TCRα Are Not Interchangeable Partners of TCRβ during T Lymphocyte Development
Authors: Borowski Christine , Li Xiaoyan , Aifantis Iannis , Gounari Fotini , von Boehmer Harald
Published: March 2004

In contrast with the αβ T cell receptor (TCR), the pre-TCR spontaneously segregates to membrane rafts from where it signals in a cell-autonomous fashion. The disparate behaviors of these two receptors may stem either from differences inherent to the distinct developmental stages during which they are expressed, or from features intrinsic and unique to the receptor components themselves. Here, we express TCRα precisely at the pre-TCR checkpoint, at levels resembling those of endogenous pre-TCRα (pTα), and in the absence of endogenous pTα. Both in isolation and more dramatically when in competition with pTα, TCRα induced defective proliferation, survival, and differentiation of αβ T lymphocyte precursors, as well as impaired commitment to the αβ T lymphocyte lineage. Substitution of TCRα transmembrane and cytoplasmic domains with those of pTα generated a hybrid molecule possessing enhanced competitive abilities. We conclude that features intrinsic to the pre-TCR, which are absent in TCRα, are essential for its unique function.
Can Behaviors Be Adaptations?
Authors: Driscoll Catherine
Published: March 2004

Kim Sterelny and Paul Griffiths (Sterelny 1992, Sterelny and Griffiths 1999) have argued that sociobiology is unworkable because it requires that human behaviors can be adaptations; however, behaviors produced by a functionalist psychology do not meet Lewontin's quasi-independence criterion and therefore cannot be adaptations. Consequently, an evolutionary psychology—which regards psychological mechanisms as adaptations—should replace sociobiology. I address two interpretations of their argument. I argue that the strong interpretation fails because functionalist psychology need not prevent behaviors from evolving independently, and it relies on too strong an interpretation of the quasi-independence criterion. The weaker interpretation does not undermine sociobiology, and evolutionary psychology would be vulnerable to the same criticism. Finally, I offer reasons to think that both mental mechanisms and behaviors can be adaptations.
Non-defensible Middle Ground for Experimental Realism: Why We Are Justified to Believe in Colored Quarks
Authors: Massimi Michela
Published: March 2004

Experimental realism aims at striking a middle ground between scientific realism and anti-realism, between the success of experimental physics it would explain and the realism about scientific theories it would supplant. This middle ground reinstates the engineering idea that belief in scientific entities is justified on purely experimental grounds, without any commitment to scientific theories and laws. This paper argues that there is no defensible middle ground to be staked out when it comes to justifying physicists’ belief in colored quarks, and that experimental realism shifts, under analysis, into scientific realism.
A Revealing Flaw in Colyvan's Indispensability Argument
Authors: Pincock† Christopher
Published: March 2004

Mark Colyvan uses applications of mathematics to argue that mathematical entities exist. I claim that his argument is invalid based on the assumption that a certain way of thinking about applications, called ‘the mapping account,’ is correct. My main contention is that successful applications depend only on there being appropriate structural relations between physical situations and the mathematical domain. As a variety of non-realist interpretations of mathematics deliver these structural relations, indispensability arguments are invalid.
Discussion Note: Making Sense of Understanding
Authors: de Regt Henk W.
Published: March 2004

J.D. Trout (2002) presents a challenge to all theorists of scientific explanation who appeal to the notion of understanding. Trout denounces understanding as irrelevant, if not dangerous, from an epistemic perspective and he endorses a radically objectivist view of explanation instead. In this note I accept Trout's challenge. I criticize his argument and defend a non-objectivist, pragmatic conception of understanding that is epistemically relevant.
PHIRE, a deterministic approach to reveal regulatory elements in bacteriophage genomes
Authors: Lavigne R. , Sun W.D. , Volckaert G.
Published: March 2004

Motivation:  In silico genome analysis of bacteriophage genomes focuses mainly on gene discovery and functional assignment. The search for regulatory elements contained within these genome sequences is often based on prior knowledge of other genomic elements or on learning algorithms of experimentally determined data, potentially leading to a biased prediction output.

The PHage In silico Regulatory Elements (PHIRE) program is a standalone program in Visual Basic. It performs an algorithmic string-based search on bacteriophage genome sequences to uncover and extract subsequence alignments hinting at regulatory elements contained within these genomes, in a deterministic manner without any prior experimental or predictive knowledge.

Results: The PHIRE program was tested on known phage genomes with experimentally verified regulatory elements. PHIRE was able to extract phage regulatory sequences correctly for bacteriophages T7, T3, ϕYeO3-12 and λ, based solely on the genome sequence. For 11 bacteriophages, new predictions of conserved phage-specific putative regulatory elements were made, further corroborating this approach.

Availability:  http://www.agr.kuleuven.ac.be/logt/PHIRE.htm. Freely available for academic use. Commercial users should contact the corresponding author.
Disulfide connectivity prediction using recursive neural networks and evolutionary information
Authors: Vullo Alessandro , Frasconi Paolo
Published: March 2004

Motivation: We focus on the prediction of disulfide bridges in proteins starting from their amino acid sequence and from the knowledge of the disulfide bonding state of each cysteine. The location of disulfide bridges is a structural feature that conveys important information about the protein main chain conformation and can therefore help towards the solution of the folding problem. Existing approaches based on weighted graph matching algorithms do not take advantage of evolutionary information. Recursive neural networks (RNN), on the other hand, can handle in a natural way complex data structures such as graphs whose vertices are labeled by real vectors, allowing us to incorporate multiple alignment profiles in the graphical representation of disulfide connectivity patterns.

Results: The core of the method is the use of machine learning tools to rank alternative disulfide connectivity patterns. We develop an ad-hoc RNN architecture for scoring labeled undirected graphs that represent connectivity patterns. In order to compare our algorithm with previous methods, we report experimental results on the SWISS-PROT 39 dataset. We find that using multiple alignment profiles allows us to obtain significant prediction accuracy improvements, clearly demonstrating the important role played by evolutionary information.

Availability: The Web interface of the predictor is available at http://neural.dsi.unifi.it/cysteines
Variance-stabilizing transformations for two-color microarrays
Authors: Durbin Blythe P. , Rocke David M.
Published: March 2004

Motivation: Authors of several recent papers have independently introduced a family of transformations (the generalized-log family), which stabilizes the variance of microarray data up to the first order. However, for data from two-color arrays, tests for differential expression may require that the variance of the difference of transformed observations be constant, rather than that of the transformed observations themselves.

Results: We introduce a transformation within the generalized-log family which stabilizes, to the first order, the variance of the difference of transformed observations. We also introduce transformations from the ‘started-log’ and log-linear-hybrid families which provide good approximate variance stabilization of differences. Examples using control–control data show that any of these transformations may provide sufficient variance stabilization for practical applications, and all perform well compared to log ratios.
404 not found: the stability and persistence of URLs published in MEDLINE
Authors: Wren Jonathan D.
Published: March 2004

Motivation: The advent of the World Wide Web has enabled unprecedented supplementation of traditional journal publications, allowing access to resources, such as video, sound, software, databases, datasets too large to publish, and even supplementary information and discussion. However, unlike traditional publications, continued availability of these online resources is not guaranteed. An automated survey was conducted to quantify the growth in Uniform Resource Locators (URLs) published to date in MEDLINE abstracts, their current availability and distribution by journal.

Results: Of 1630 unique URLs identified, formatting and/or spelling errors were detected within 201 (12%) of them as published. After corrections were made, a survey revealed that ∼63% of these URLs were consistently available, and another 19% were available intermittently. The rate of failure was far worse for anonymous login to FTP sites, with only 12 of 33 sites (36%) responding. This survey also shows that journals vary disproportionately in the number of web citations published, suggesting policy implementation among a few could have a profound impact overall. Out of the 306 journals with a URL published in an abstract, Bioinformatics published the most (12% of total).

Availability: URL database and program available by request.
Comparison of various algorithms for recognizing short coding sequences of human genes
Authors: Gao Feng , Zhang Chun-Ting
Published: March 2004

Motivation: Since the early 1980s of the twentieth century, there has been great progress in the development of computational gene-finding algorithms. Some problems, however, have not yet been solved currently. Recognizing short genes in prokaryotes and short exons in eukaryotes is one of such problems. The paper is devoted to assessing various algorithms, including those currently available and the new ones proposed here, in order to find the best algorithm to solve the issue.

Results: The databases consisting of phase-specific coding and non-coding sequences of human genes with length of 192, 162, 129, 108, 87, 63 and 42 bp, respectively, have been established. Based on the databases and a standard benchmark, 19 algorithms were evaluated, which include the methods of Markov models with orders of 1 through 5, codon usage, hexamer usage, codon preference, amino acid usage, codon prototype, Fourier transform and 8 Z curve methods with various numbers of parameters. Consequently, the Z curve methods with 69 and 189 parameters are the best ones among them, based on the databases constructed here. In addition to the highest recognition accuracy confirmed by 10-fold cross-validation tests, the Z curve methods are much simpler computationally than the second best one, the fifth-order Markov chain model, in which 12 288 parameters are used. We hope that the Z curve methods presented in this paper would be beneficial to the further development of gene-finding algorithms.

Availability: The programs of various Z curve methods are available on request.
A statistical framework for combining and interpreting proteomic datasets
Authors: Gilchrist Michael A. , Salter Laura A. , Wagner Andreas
Published: March 2004

Motivation: To identify accurately protein function on a proteome-wide scale requires integrating data within and between high-throughput experiments. High-throughput proteomic datasets often have high rates of errors and thus yield incomplete and contradictory information. In this study, we develop a simple statistical framework using Bayes’ law to interpret such data and combine information from different high-throughput experiments. In order to illustrate our approach we apply it to two protein complex purification datasets.

Results: Our approach shows how to use high-throughput data to calculate accurately the probability that two proteins are part of the same complex. Importantly, our approach does not need a reference set of verified protein interactions to determine false positive and false negative error rates of protein association. We also demonstrate how to combine information from two separate protein purification datasets into a combined dataset that has greater coverage and accuracy than either dataset alone. In addition, we also provide a technique for estimating the total number of proteins which can be detected using a particular experimental technique.

Availability: A suite of simple programs to accomplish some of the above tasks is available at www.unm.edu/~compbio/software/DatasetAssess
Java-based application framework for visualization of gene regulatory region annotations
Authors: Sun Hao , Davuluri Ramana V.
Published: March 2004

Motivation: The genome sequences of several organisms are either complete, or being sequenced. Each genome needs to be integrated with various types of annotations, e.g. locations of genes, promoters and other functional elements such as transcriptional regulatory elements. A robust application framework will be useful for developing web-based applications to visualize various genome annotations.

Results: We developed genome data visualization toolkit (GDVTK) as an application framework that consists of a set of data structures and core classes, using Java™ technology. GDVTK is a sound framework for developing web-based applications to present the gene regulatory region annotations in visual form. The current version of GDVTK consists of eight packages and 38 Java classes that are portable, reusable and extensible for plugging in new data sources and models. We implemented GDVTK for visualization of promoter annotations in Mammalian Promoter Database (MPromDb), a web-based gene-regulatory information server.

Availability: GDVTK is available under GNU general public license. Source code and software documentation can be found at the URL http://bioinformatics.med.ohio-state.edu/GDVTK.
ESPD: a pattern detection model underlying gene expression profiles
Authors: Tang Chun , Zhang Aidong , Ramanathan Murali
Published: March 2004

Motivation: DNA arrays permit rapid, large-scale screening for patterns of gene expression and simultaneously yield the expression levels of thousands of genes for samples. The number of samples is usually limited, and such datasets are very sparse in high-dimensional gene space. Furthermore, most of the genes collected may not necessarily be of interest and uncertainty about which genes are relevant makes it difficult to construct an informative gene space. Unsupervised empirical sample pattern discovery and informative genes identification of such sparse high-dimensional datasets present interesting but challenging problems.

Results: A new model called empirical sample pattern detection (ESPD) is proposed to delineate pattern quality with informative genes. By integrating statistical metrics, data mining and machine learning techniques, this model dynamically measures and manipulates the relationship between samples and genes while conducting an iterative detection of informative space and the empirical pattern. The performance of the proposed method with various array datasets is illustrated.

Availability: Software code is available by request from the first author. All programs were written in MATLAB.
Algorithms for variable length Markov chain modeling
Authors: Bejerano Gill
Published: March 2004

Summary: We present a general purpose implementation of variable length Markov models. Contrary to fixed order Markov models, these models are not restricted to a predefined uniform depth. Rather, by examining the training data, a model is constructed that fits higher order Markov dependencies where such contexts exist, while using lower order Markov dependencies elsewhere. As both theoretical and experimental results show, these models are capable of capturing rich signals from a modest amount of training data, without the use of hidden states.

Availability: The source code is freely available at http://www.soe.ucsc.edu/~jill/src/
CAAT-Box, contigs-Assembly and Annotation Tool-Box for genome sequencing projects
Authors: Frangeul L. , Glaser P. , Rusniok C. , Buchrieser C. , Duchaud E. , Dehoux P. , Kunst F.
Published: March 2004

Motivation: Contigs-Assembly and Annotation Tool-Box (CAAT-Box) is a software package developed for the computational part of a genome project where the sequence is obtained by a shotgun strategy. CAAT-Box contains new tools to predict links between contigs by using similarity searches with other whole genome sequences. Most importantly, it allows annotation of a genome to commence during the finishing phase using a gene-oriented strategy. For this purpose, CAAT-Box creates an Individual Protein file (IPF) for each ORF of an assembly. The nucleotide sequence reported in an IPF corresponds to the sequence of the ORF with 500 additional bases before the ORF and 200 bases after. For annotation, additional information like Blast results can be added or linked to the IPFs as well as automatic and/or manual annotations. When a new assembly is performed, CAAT-Box creates new IPFs according to the old IPF panel. CAAT-Box recognizes the modified IPFs which are the only ones used for a new automatic analysis after each assembly. Using this strategy, the user works with a group of IPFs independently of the closure phase progression. The IPFs are accessible by a web server and can therefore be modified and commented by different groups.

Result: CAAT-Box was used to obtain and to annotate several complete genomes like Listeria monocytogenes or Strepcoccus agalactiae.

Availability: The program may be obtained from the authors and is freely available to non-profit organisations.
In silico analysis of complete bacterial genomes: PCR, AFLP–PCR and endonuclease restriction
Authors: Bikandi Joseba , Millán Rosario San , Rementeria Aitor , Garaizar Javier
Published: March 2004

Summary: We have developed a website, www.in-silico.com, which runs a software program that performs three basic tasks in completely sequenced bacterial genomes by in silico analysis: PCR amplification, amplified fragment length polymorphism (AFLP–PCR) and endonuclease restriction. For PCR, after selection of the genome and introduction of primers, fragment size, DNA sequence and corresponding open reading frame (ORF) identity of the resulting PCR product is computed. Plasmids of sequenced species may be included in the analysis. Theoretical AFLP–PCR analyzes similar parameters, and includes a suggestion tool providing a list of commercial restriction enzyme pairs yielding up to 50 amplicons in the selected genome. Endonuclease restriction analysis of complete genomes and plasmids calculates the number of restriction sites for endonucleases in a given genome. If the number of fragments is 50 or fewer, pulsed field gel electrophoresis image and restriction maps are illustrated. Other tools that have been included in this site are ORF search by name and DNA to protein translation as well as restriction digestion of user-defined DNA sequences.

Availability: This is a new molecular biology resource freely available over the Internet at http://www.in-silico.com
Gene selection for oligonucleotide array: an approach using PM probe level data
Authors: Chen Dung-Tsa , Lin Sue-Hwa , Soong Seng-jaw
Published: March 2004

Motivation: Analysis of oligonucleotide array data, especially to select genes of interest, is a highly challenging task because of the large volume of information and various experimental factors. Moreover, interaction effect (i.e. expression changes depend on probe effects) complicates the analysis because current methods often use an additive model to analyze data. We propose an approach to address these issues with the aim of producing a more reliable selection of differentially expressed genes. The approach uses the rank for normalization, employs the percentile-range to measure expression variation, and applies various filters to monitor expression changes.

Results: We compare our approach with MAS and Dchip models. A data set from an angiogenesis study is used for illustration. Results show that our approach performs better than other methods either in identification of the positive control gene or in PCR confirmatory tests. In addition, the invariant set of genes in our approach provides an efficient way for normalization.
Optimizing substitution matrices by separating score distributions
Authors: Hourai Yuichiro , Akutsu Tatsuya , Akiyama Yutaka
Published: March 2004

Motivation:Homology search is one of the most fundamental tools in Bioinformatics. Typical alignment algorithms use substitution matrices and gap costs. Thus, the improvement of substitution matrices increases accuracy of homology searches. Generally, substitution matrices are derived from aligned sequences whose relationships are known, and gap costs are determined by trial and error. To discriminate relationships more clearly, we are encouraged to optimize the substitution matrices from statistical viewpoints using both positive and negative examples utilizing Bayesian decision theory.

Results: Using Cluster of Orthologous Group (COG) database, we optimized substitution matrices. The classification accuracy of the obtained matrix is better than that of conventional substitution matrices to COG database. It also achieves good performance in classifying with other databases.

Availability: The optimized substitution matrices and the programs are available from the http://olab.is.s.u-tokyo.ac.jp/~hourai/optssd/index.html
On the significance of sequence alignments when using multiple scoring matrices
Authors: Frommlet Florian , Futschik Andreas , Bogdan Małgorzata
Published: March 2004

Motivation: Pairwise local sequence alignment is commonly used to search data bases for sequences related to some query sequence. Alignments are obtained using a scoring matrix that takes into account the different frequencies of occurrence of the various types of amino acid substitutions. Software like BLAST provides the user with a set of scoring matrices available to choose from, and in the literature it is sometimes recommended to try several scoring matrices on the sequences of interest.

The significance of an alignment is usually assessed by looking at E-values and p-values. While sequence lengths and data base sizes enter the standard calculations of significance, it is much less common to take the use of several scoring matrices on the same sequences into account. Altschul proposed corrections of the p-value that account for the simultaneous use of an infinite number of PAM matrices. Here we consider the more realistic situation where the user may choose from a finite set of popular PAM and BLOSUM matrices, in particular the ones available in BLAST. It turns out that the significance of a result can be considerably overestimated, if a set of substitution matrices is used in an alignment problem and the most significant alignment is then quoted.

Results: Based on extensive simulations, we study the multiple testing problem that occurs when several scoring matrices for local sequence alignment are used. We consider a simple Bonferroni correction of the p-values and investigate its accuracy. Finally, we propose a more accurate correction based on extreme value distributions fitted to the maximum of the normalized scores obtained from different scoring matrices. For various sets of matrices we provide correction factors which can be easily applied to adjust p- and E-values reported by software packages.

Availability: The code used for our simulations is available on http://mailbox.univie.ac.at/Florian.Frommlet/MSMsoftware.htm/
Modeling the relationship between LVAD support time and gene expression changes in the human heart by penalized partial least squares
Authors: Huang Xiaohong , Pan Wei , Park Soon , Han Xinqiang , Miller Leslie W. , Hall Jennifer
Published: March 2004

Motivation: Heart failure affects more than 20 million people in the world. Heart transplantation is the most effective therapy, but the number of eligible patients far outweighs the number of available donor hearts. The left mechanical ventricular assist device (LVAD) has been developed as a successful substitution therapy that aids the failing ventricle while a patient is waiting for the donor heart. We obtained genomics data from paired human heart samples harvested at the time of LVAD implant and explant. The heart failure patients in our study were supported by the LVAD for various periods of time. The goal of this study is to model the relationship between the time of LVAD support and gene expression changes.

Results: To serve the purpose, we propose a novel penalized partial least squares (PPLS) method to build a regression model. Compared with partial least squares and Breiman's random forest method, PPLS gives the best prediction results for the LVAD data.
ReDiT: Repeat Discrepancy Tagger—a shotgun assembly finishing aid
Authors: Tammi Martti T. , Arner Erik , Kindlund Ellen , Andersson Björn
Published: March 2004

Summary: Finishing, i.e. gap closure and editing, is the most time-consuming part of genome sequencing. Repeated sequences together with sequencing errors complicate the assembly and often result in misassemblies that are difficult to correct. Repeat Discrepancy Tagger (ReDiT) is a tool designed to aid in the finishing step. This software processes assembly results produced by any fragment assembly program that outputs ace files. The input sequences are analyzed to determine possible differences between repeated sequences. The output is written as tags in an ace file that can be viewed by, e.g. the Consed sequence editor.

Availability: The ReDiT program is freely available at http://web.cgb.ki.se/redit
Alu repeat analysis in the complete human genome: trends and variations with respect to genomic composition
Authors: Grover Deepak , Mukerji Mitali , Bhatnagar Pankaj , Kannan K. , Brahmachari Samir K.
Published: March 2004

Motivation: Transposon-derived Alu repeats are exclusively associated with primate genomes. They have gained considerable importance in the recent times with evidence of their involvement in various aspects of gene regulation, e.g. alternative splicing, nucleosome positioning, CpG methylation, binding sites for transcription factors and hormone receptors, etc. The objective of this study is to investigate the factors that influence the distribution of Alu repeat elements in the human genome. Such analysis is expected to yield insights into various aspects of gene regulation in primates.

Results: Analysis of Alu repeat distribution for the human genome build 32 (released in January 2003) reveals that they occupy nearly one-tenth portion of the sequenced regions. Huge variations in Alu frequencies were seen across the genome with chromosome 19 being the most and chromosome Y being the least Alu dense chromosomes. The highlights of the analysis are as follows: (1) three-fourth of the total genes in the genome are associated with Alus. (2) Alu density is higher in genes as compared with intergenic regions in all the chromosomes except 19 and 22. (3) Alu density in human genome is highly correlated with GC content, gene density and intron density with GC content being major deterministic factor compared with other two. (4) Alu densities were correlated more with gene density than intron density indicating the insertion of Alus in untranslated regions of exons.

Supplementary information: Online supplementary data is available at the web page http://www.igib.res.in/manuscriptdata/aluanalysis.html
The Hera database and its use in the characterization of endoplasmic reticulum proteins
Authors: Scott M. , Lu G. , Hallett M. , Thomas D. Y.
Published: March 2004

Motivation: Information concerning endoplasmic reticulum (ER) proteins is widely dispersed and cannot be easily and rapidly processed by the biological community. We present a comprehensive database of human ER proteins, called Human ER Aperçu (Hera). The Hera database was constructed by exhaustively searching through public databases and the scientific literature for ER proteins.

Results: Hera was used for the analysis of characteristics common to all human ER proteins. Our results show that a high proportion of ER proteins (59%) have at least one transmembrane domain and display physical characteristics consistent with this observation. In addition, one-third of ER proteins contain known ER retrieval or retention signals and 70% of ER proteins contain a signal peptide or anchor. Finally, 85% of ER proteins contain at least one InterPro motif. The most abundant InterPro motifs in ER proteins represent many of the most well-characterized functions of the ER.

Availability: Hera is available at http://www.mcb.mcgill.ca/~hera.
Finding coexpressed genes in counts-based data: an improved measure with validation experiments
Authors: Price Morgan N. , Rieffel Eleanor
Published: March 2004

Motivation: Expressed sequence tag (EST) data reflects variation in gene expression, but previous methods for finding coexpressed genes in EST data are subject to bias and vastly overstate the statistical significance of putatively coexpressed genes.

Results: We introduce a new method (LNP) that reports reasonable p-values and also detects more biological relationships in human dbEST than do previous methods. In simulations with human dbEST library sizes, previous methods report p-values as low as 10−30 on 1/1000 uncorrelated pairs, while LNP reports significance correctly. We validate the analysis on real human genes by comparing coexpressed pairs to gene ontology annotations and find that LNP is more sensitive than the three previous methods. We also find a small but statistically significant level of coexpression between interacting proteins relative to randomized controls. The LNP method is based on a log-normal prior on the distribution of expression levels.

Availability: Source code in Java or R is available at http://ests.sourceforge.net/

Supplementary information:  http://ests/sourceforge.net/lnp_supplement.pdf
Visualization of near-optimal sequence alignments
Authors: Smoot Michael E. , Guerlain Stephanie A. , Pearson William R.
Published: March 2004

Motivation: Mathematically optimal alignments do not always properly align active site residues or well-recognized structural elements. Most near-optimal sequence alignment algorithms display alternative alignment paths, rather than the conventional residue-by-residue pairwise alignment. Typically, these methods do not provide mechanisms for finding effectively the most biologically meaningful alignment in the potentially large set of options.

Results: We have developed Web-based software that displays near optimal or alternative alignments of two protein or DNA sequences as a continuous moving picture. A WWW interface to a C++ program generates near optimal alignments, which are sent to a Java Applet, which displays them in a series of alignment frames. The Applet aligns residues so that consistently aligned regions remain at a fixed position on the display, while variable regions move. The display can be stopped to examine alignment details.

Availability: Available at http://fasta.bioch.virginia.edu/noptalign. For source code contact the authors at wrp@virginia.edu
ClusterControl: a web interface for distributing and monitoring bioinformatics applications on a Linux cluster
Authors: Stocker Gernot , Rieder Dietmar , Trajanoski Zlatko
Published: March 2004

Summary: ClusterControl is a web interface to simplify distributing and monitoring bioinformatics applications on Linux cluster systems. We have developed a modular concept that enables integration of command line oriented program into the application framework of ClusterControl. The systems facilitate integration of different applications accessed through one interface and executed on a distributed cluster system. The package is based on freely available technologies like Apache as web server, PHP as server-side scripting language and OpenPBS as queuing system and is available free of charge for academic and non-profit institutions.

Availability:  http://genome.tugraz.at/Software/ClusterControl
Identification of optimal classification functions for biological sample and state discrimination from metabolic profiling data
Authors: Lee Kyongbum , Hwang Daehee , Yokoyama Tadaaki , Stephanopoulos George , Stephanopoulos Gregory N. , Yarmush Martin L.
Published: March 2004

Motivations: Classification of biological samples for diagnostic purposes is a difficult task because of the many decisions involved on the number, type and functional manipulations of the input variables. This study presents a generally applicable strategy for systematic formulation of optimal diagnostic indexes. To this end, we develop a novel set of computational tools by integrating regression optimization, stepwise variable selection and cross-validation algorithms.

Results: The proposed discrimination methodology was applied to plasma and tissue (liver) metabolic profiling data describing the time progression of liver dysfunction in a rat model of acute hepatic failure generated by d-galactosamine (GalN) injection. From the plasma data, our methodology identified seven (out of a total of 23) metabolites, and the corresponding transform functions, as the best inputs to the optimal diagnostic index. This index showed better time resolution and increased noise robustness compared with an existing metabolic index, Fischer's BCAA/AAA molar ratio, as well as indexes generated using other commonly used discriminant analysis tools. Comparison of plasma and liver indexes found two consensus metabolites, lactate and glucose, which implicate glycolysis and/or gluconeogenesis in mediating the metabolic effects of GalN.
Database model and specification of GermOnline Release 2.0, a cross-species community annotation knowledgebase on germ cell differentiation
Authors: Wiederkehr C. , Basavaraj R. , de Menthière C. Sarrauste , Koch R. , Schlecht U. , Hermida L. , Masdoua B. , Ishii R. , Cassen V. , Yamamoto M. , Lane C. , Cherry M. , Lamb N. , Primig M.
Published: March 2004

Summary: GermOnline is a web-accessible relational database that enables life scientists to make a significant and sustained contribution to the annotation of genes relevant for the fields of mitosis, meiosis, germ line development and gametogenesis across species. This novel approach to genome annotation includes a platform for knowledge submission and curation as well as microarray data storage and visualization hosted by a global network of servers.

Availability: The database is accessible at http://www.germonline.org/. For convenient world-wide access we have set up a network of servers in Europe (http://germonline.unibas.ch/; http://germonline.igh.cnrs.fr/), Japan (http://germonline.biochem.s.u-tokyo.ac.jp/) and USA (http://germonline.yeastgenome.org/).

Supplementary information: Extended documentation of the database is available through the link ‘About GermOnline’ at the websites.
Measuring the similarity of protein structures by means of the universal similarity metric
Authors: Krasnogor N. , Pelta D. A.
Published: March 2004

Motivation: As an increasing number of protein structures become available, the need for algorithms that can quantify the similarity between protein structures increases as well. Thus, the comparison of proteins' structures, and their clustering accordingly to a given similarity measure, is at the core of today's biomedical research. In this paper, we show how an algorithmic information theory inspired Universal Similarity Metric (USM) can be used to calculate similarities between protein pairs. The method, besides being theoretically supported, is surprisingly simple to implement and computationally efficient.

Results: Structural similarity between proteins in four different datasets was measured using the USM. The sample employed represented alpha, beta, alpha–beta, tim–barrel, globins and serpine protein types. The use of the proposed metric allows for a correct measurement of similarity and classification of the proteins in the four datasets.

Availability: All the scripts and programs used for the preparation of this paper are available at http://www.cs.nott.ac.uk/~nxk/USM/protocol.html. In that web-page the reader will find a brief description on how to use the various scripts and programs.

Supplementary information: The protein datasets used are collected in http://www.cs.nott.ac.uk/~nxk/USM/datasets.html. The calculated similarity values for the proteins used in this paper can be found in http://www.cs.nott.ac.uk/~nxk/USM/similar.html. The clustering of the dataset based on these similarity values can be found in http://www.cs.nott.ac.uk/~nxk/USM/clustering.html
Ontologizing gene-expression microarray data: characterizing clusters with Gene Ontology
Authors: Robinson Peter N. , Wollstein Andreas , Böhme Ulrike , Beattie Brad
Published: March 2004

Summary: An XML-based Java application is described that provides a function-oriented overview of the results of cluster analysis of gene-expression microarray data based on Gene Ontology terms and associations. The application generates one HTML page with listings of the frequencies of explicit and implicit Gene Ontology annotations for each cluster, and separate, linked pages with listings of explicit annotations for each gene in a cluster.

Availability:  http://www.charite.de/ch/medgen/ontologizer
Preference of simple sequence repeats in coding and non-coding regions of Arabidopsis thaliana
Authors: Zhang Lida , Yuan Dejun , Yu Shunwu , Li Zhugang , Cao Youfang , Miao Zhiqi , Qian Hongmei , Tang Kexuan
Published: March 2004

Motivation: Simple sequence repeats or microsatellites have been found abundantly in many genomes. However, the significance of distribution preference has not been completely understood. Completion of the Arabidopsis genome sequencing allows us to better understand and characterize microsatellites.

Results: Microsatellite distribution was more abundant in 5′-flanking regions of genes compared with that expected in the whole genome, with an over-representation of AG and AAG repeats; there were clear differences from distributions in 3′-flanks and coding fractions, where triplet frequencies evidently corresponded to codon usage. We identified 1140 full-length genes that contained at least one locus of AG or AAG repeats in their upstream sequences, and whose functional characteristics were significantly associated with the repeats. This observation indicates that selective pressure markedly differed in the three transcribed regions, with positive selection of AG and AAG repeats in 5′-flanks close to those genes whose products are preferentially involved in transcription.
NvAssign: protein NMR spectral assignment with NMRView
Authors: Kirby Nigel I. , DeRose Eugene F. , London Robert E. , Mueller Geoffrey A.
Published: March 2004

Motivation: Nuclear magnetic resonance (NMR) protein studies rely on the accurate assignment of resonances. The general procedure is to (1) pick peaks, (2) cluster data from various experiments or spectra, (3) assign peaks to the sequence and (4) verify the assignments with the spectra. Many algorithms already exist for automating the assignment process (step 3). What is lacking is a flexible interface to help a spectroscopist easily move from clustering (step 2) to assignment algorithms (step 3) and back to verification of the algorithm output with spectral analysis (step 4).

Results: A software module, NvAssign, was written for use with NMRView. It is a significant extension of the previous CBCA module. The module provides a flexible interface to cluster data and interact with the existing assignment algorithms. Further, the software module is able to read the results of other algorithms so that the data can be easily verified by spectral analysis. The generalized interface is demonstrated by connecting the clustered data with the assignment algorithms PACES and MONTE using previously assigned data for the lyase domain of DNA polymerase λ. The spectral analysis program NMRView is now able to read the output of these programs for simplified analysis and verification.

Availability: NvAssign is available from http://dir.niehs.nih.gov/dirnmr/nvassign

Supplementary information: Extensive manual pages with installation instructions, procedures and screen shots can also found at http://dir.niehs.nih.gov/dirnmr/nvassign
Cellware—a multi-algorithmic software for computational systems biology
Authors: Dhar Pawan , Meng Tan Chee , Somani Sandeep , Ye Li , Sairam Anand , Chitre Mandar , Hao Zhu , Sakharkar Kishore
Published: March 2004

Summary: The intracellular environment of a cell hosts a wide variety of enzymatic reactions, diffusion events, molecular binding, polymerization and metabolic channeling. To transform these biological events into a computational framework, distinct modeling strategies are required. While currently no tool is capable of capturing all these events, progress is being made to create an integrated environment for the modeling community. To address this niche requirement, Cellware has been developed to offer a multi-algorithmic environment for modeling and simulating both deterministic and stochastic events in the cell.

Availability: The software is available for free and can be downloaded from http://www.bii.a-star.edu.sg/sbg/cellware
Bayesian mixture model based clustering of replicated microarray data
Authors: Medvedovic M. , Yeung K.Y. , Bumgarner R.E.
Published: March 2004

Motivation: Identifying patterns of co-expression in microarray data by cluster analysis has been a productive approach to uncovering molecular mechanisms underlying biological processes under investigation. Using experimental replicates can generally improve the precision of the cluster analysis by reducing the experimental variability of measurements. In such situations, Bayesian mixtures allow for an efficient use of information by precisely modeling between-replicates variability.

Results: We developed different variants of Bayesian mixture based clustering procedures for clustering gene expression data with experimental replicates. In this approach, the statistical distribution of microarray data is described by a Bayesian mixture model. Clusters of co-expressed genes are created from the posterior distribution of clusterings, which is estimated by a Gibbs sampler. We define infinite and finite Bayesian mixture models with different between-replicates variance structures and investigate their utility by analyzing synthetic and the real-world datasets. Results of our analyses demonstrate that (1) improvements in precision achieved by performing only two experimental replicates can be dramatic when the between-replicates variability is high, (2) precise modeling of intra-gene variability is important for accurate identification of co-expressed genes and (3) the infinite mixture model with the ‘elliptical’ between-replicates variance structure performed overall better than any other method tested. We also introduce a heuristic modification to the Gibbs sampler based on the ‘reverse annealing’ principle. This modification effectively overcomes the tendency of the Gibbs sampler to converge to different modes of the posterior distribution when started from different initial positions. Finally, we demonstrate that the Bayesian infinite mixture model with ‘elliptical’ variance structure is capable of identifying the underlying structure of the data without knowing the ‘correct’ number of clusters.

Availability: The MS Windows™ based program named Gaussian Infinite Mixture Modeling (GIMM) implementing the Gibbs sampler and corresponding C++ code are available at http://homepages.uc.edu/~medvedm/GIMM.htm

Supplemental information:  http://expression.microslu.washington.edu/expression/kayee/medvedovic2003/medvedovic_bioinf2003.html
dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data
Authors: Lin Ming , Wei Lee-Jen , Sellers William R. , Lieberfarb Marshall , Wong Wing Hung , Li Cheng
Published: March 2004

Motivation: Oligonucleotide microarrays allow genotyping of thousands of single-nucleotide polymorphisms (SNPs) in parallel. Recently, this technology has been applied to loss-of-heterozygosity (LOH) analysis of paired normal and tumor samples. However, methods and software for analyzing such data are not fully developed.

Result: Here, we report automated methods for pooling SNP array replicates to make LOH calls, visualizing SNP and LOH data along chromosomes in the context of genes and cytobands, making statistical inference to identify shared LOH regions, clustering samples based on LOH profiles and correlating the clustering results to clinical variables. Application of these methods to prostate and breast cancer datasets generates biologically important results.

Availability: The software module dChipSNP implementing these methods is available at http://biosun1.harvard.edu/complab/dchip/snp/

Supplementary information: The breast cancer data are provided by Andrea L. Richardson, Zhigang C. Wang and James D. Iglehart.
eF-site and PDBjViewer: database and viewer for protein functional sites
Authors: Kinoshita Kengo , Nakamura Haruki
Published: March 2004

Summary: The electrostatic-surface of functional site (eF-site) is a database for the molecular surfaces of protein functional sites. To enable browsing of each molecular surface along with the atomic model, we have developed a new three-dimensional interactive viewer, PDBjViewer, that can be used both as an applet and as a stand-alone program.

Availability: The eF-site database and PDBjViewer are freely available from http://www.pdbj.org/eF-site/
Open source clustering software
Authors: de Hoon M.J.L. , Imoto S. , Nolan J. , Miyano S.
Published: March 2004

Summary: We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C.

Availability: The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.
Automated ordering of fingerprinted clones
Authors: Flibotte Stephane , Chiu Readman , Fjell Chris , Krzywinski Martin , Schein Jacqueline E. , Shin Heesun , Marra Marco A.
Published: March 2004

Motivation: A considerable amount of human intervention is currently required to produce high-quality fingerprint-based physical maps for genomic studies.

Results: An algorithm has been developed and implemented to automatically order fingerprinted clones within contigs. The resulting software, named CORAL (Clone ORdering ALgorithm), has been tested on maps that have previously been manually edited and on maps derived from in silico simulations. The fingerprint map and DNA sequence of the human genome has provided an additional test to CORAL. Measurements suggest that CORAL performs significantly better than the software currently used by most laboratories to order fingerprinted clones at throughputs far exceeding those that can be achieved manually.

Availability: Available on request from the authors.