bluuebunny/crossref_metadata_2025 huggingface dataset:
CompuCell, a multi-model framework for simulation of morphogenesis
Authors: Izaguirre J. A. , Chaturvedi R. , Huang C. , Cickovski T. , Coffland J. , Thomas G. , Forgacs G. , Alber M. , Hentschel G. , Newman S. A. , Glazier J. A.
Published: March 2004

Motivation: CompuCell is a multi-model software framework for simulation of the development of multicellular organisms known as morphogenesis. It models the interaction of the gene regulatory network with generic cellular mechanisms, such as cell adhesion, division, haptotaxis and chemotaxis. A combination of a state automaton with stochastic local rules and a set of differential equations, including subcellular ordinary differential equations and extracellular reaction–diffusion partial differential equations, model gene regulation. This automaton in turn controls the differentiation of the cells, and cell–cell and cell–extracellular matrix interactions that give rise to cell rearrangements and pattern formation, e.g. mesenchymal condensation. The cellular Potts model, a stochastic model that accurately reproduces cell movement and rearrangement, models cell dynamics. All these models couple in a controllable way, resulting in a powerful and flexible computational environment for morphogenesis, which allows for simultaneous incorporation of growth and spatial patterning.

Results: We use CompuCell to simulate the formation of the skeletal architecture in the avian limb bud.

Availability: Binaries and source code for Microsoft Windows, Linux and Solaris are available for download from http://sourceforge.net/projects/compucell/
AmpliBASE MT™: a Mycobacterium tuberculosis diversity knowledgebase
Authors: Majeed Ahmed A. , Ahmed Niyaz , Rao K. Rajender , Ghousunnissa S. , Kauser Farhana , Bose Buddhaditta , Nagarajaram H. A. , Katoch V. M. , Cousins Debby V. , Sechi Leonardo A. , Gilman Robert H. , Hasnain Seyed E.
Published: March 2004

Summary:  AmpliBASE MT™ is an online databank of high-resolution DNA fingerprints representing fluorescent amplified fragment length polymorphism (FAFLP) profiles or amplitypes developed for the Mycobacterium tuberculosis complex strains from 48 different countries. AmpliBASE MT™ is based on a relational database management system that is hyperlinked to visualize genotyping results in the form of DNA fingerprint images for individual strains. A flexible search system based on systematic comparisons of fragment sizes in base pairs allows inter-laboratory comparison of FAFLP profiles. Besides this, the database also displays previously published data on IS6110 profiles, spoligotypes, MIRU-VNTRs and large sequence polymorphisms along with the FAFLP records that will give the overall comparisons. Being the first of its kind, AmpliBASE MT™ is expected to be a very helpful tool in strengthening the concept of ‘geographic genomics’ and will be very helpful to molecular epidemiologists and those interested in diagnostic development for tuberculosis.

Availability:  http://210.212.212.4/index.html
ChromoViz: multimodal visualization of gene expression data onto chromosomes using scalable vector graphics
Authors: Kim Jihoon , Chung Hee-Joon , Park Chan Hee , Park Woong-Yang , Kim Ju Han
Published: March 2004

Summary: ChromoViz is an R package for the visualization of microarray gene expression data, cross-species and cross-platform comparisons, as well as non-expression genomic data obtained from public databases onto chromosomes. Chromosomal visualization format is proposed for the clear decoupling of the data layer from the procedure layer and the combined visualization of genomic data from heterogeneous data sources. Visualization with Javascript-enabled scalable vector graphics enables interactive visualization and navigation of data objects on the Web.

Availability:  http://www.snubi.org/software/ChromoViz/
Large-scale co-evolution analysis of protein structural interlogues using the global protein structural interactome map (PSIMAP)
Authors: Kim Wan K. , Bolser Dan M. , Park Jong H.
Published: March 2004

Motivation: Interacting pairs of proteins should co-evolve to maintain functional and structural complementarity. Consequently, such a pair of protein families shows similarity between their phylogenetic trees. Although the tendency of co-evolution has been known for various ligand–receptor pairs, it has not been studied systematically in the widest possible scope. We investigated the degree of co-evolution for more than 900 family pairs in a global protein structural interactome map (PSIMAP—a map of all the structural domain–domain interactions in the PDB).

Results: There was significant correlation in 45% of the total SCOPs Family level pairs, rising to 78% in 454 reliable family interactions. Expectedly, the intra-molecular interactions between protein families showed stronger co-evolution than inter-molecular interactions. However, both types of interaction have a fundamentally similar pattern of co-evolution except for cases where different interfaces are involved. These results validate the use of co-evolution analysis with predictive methods such as PSIMAP to improve the accuracy of prediction based on ‘homologous interaction’. The tendency of co-evolution enabled a nearly 5-fold enrichment in the identification of true interactions among the potential interlogues in PSIMAP. The estimated sensitivity was 79.2%, and the specificity was 78.6%.

Availability: The results of co-evolution analysis are available online at http://www.biointeraction.org
Predicting subcellular localization of proteins in a hybridization space
Authors: Cai Yu-Dong , Chou Kuo-Chen
Published: March 2004

Motivation: The localization of a protein in a cell is closely correlated with its biological function. With the number of sequences entering into databanks rapidly increasing, the importance of developing a powerful high-throughput tool to determine protein subcellular location has become self-evident. In view of this, the Nearest Neighbour Algorithm was developed for predicting the protein subcellular location using the strategy of hybridizing the information derived from the recent development in gene ontology with that from the functional domain composition as well as the pseudo amino acid composition.

Results: As a showcase, the same plant and non-plant protein datasets as investigated by the previous investigators were used for demonstration. The overall success rate of the jackknife test for the plant protein dataset was 86%, and that for the non-plant protein dataset 91.2%. These are the highest success rates achieved so far for the two datasets by following a rigorous cross-validation test procedure, suggesting that such a hybrid approach (particularly by incorporating the knowledge of gene ontology) may become a very useful high-throughput tool in the area of bioinformatics, proteomics, as well as molecular cell biology.

Availability: The software would be made available on sending a request to the authors.
Multiple sequence alignment in parallel on a workstation cluster
Authors: Ebedes Justin , Datta Amitava
Published: March 2004

Summary: Multiple sequence alignment is the NP-hard problem of aligning three or more DNA or amino acid sequences in an optimal way so as to match as many characters as possible from the set of sequences. The popular sequence alignment program ClustalW uses the classical method of approximating a sequence alignment, by first computing a distance matrix and then constructing a guide tree to show the evolutionary relationship of the sequences. We show that parallelizing the ClustalW algorithm can result in significant speedup. We used a cluster of workstations using C and message passing interface for our implementation. Experimental results show that speedup of over 5.5 on six processors is obtainable for most inputs.

Availability: The software is available upon request from the second author.
CLENCH: a program for calculating Cluster ENriCHment using the Gene Ontology
Authors: Shah N.H. , Fedoroff N.V.
Published: March 2004

Summary: Analysis of microarray data most often produces lists of genes with similar expression patterns, which are then subdivided into functional categories for biological interpretation. Such functional categorization is most commonly accomplished using Gene Ontology (GO) categories. Although there are several programs that identify and analyze functional categories for human, mouse and yeast genes, none of them accept Arabidopsis thaliana data. In order to address this need for A.thaliana community, we have developed a program that retrieves GO annotations for A.thaliana genes and performs functional category analysis for lists of genes selected by the user.

Availability:  http://www.personal.psu.edu/nhs109/Clench
Cluster Analyzer for Transcription Sites (CATS): a C++-based program for identifying clustered transcription factor binding sites
Authors: Yu Han , Yoo Andrew S. , Greenwald Iva
Published: March 2004

Summary: We have developed a program, Cluster Analyzer for Transcription Sites (CATS), which identifies clusters of transcription factor binding sites in any genome sequence. The program searches for clusters of the consensus sequence for DNA binding within a window (length of DNA). The window size and the cluster size (number of consensus sequences within a given window) can be varied. CATS can be used for single or multiple transcription factors for which consensus sequences have been deduced based on biochemical and mutational analysis, or by comparative genomics. The use of CATS for clusters of different transcription factor binding sites may facilitate the identification of genes that are co-regulated in a cell type-specific or developmental stage-specific manner. CATS is simple to install and use on computers running any Windows NT-platforms.

Availability:  http://www.healthsciences.columbia.edu/dept/greenwaldlab/links.html
Gene structure prediction from consensus spliced alignment of multiple ESTs matching the same genomic locus
Authors: Brendel Volker , Xing Liqun , Zhu Wei
Published: March 2004

Motivation: Accurate gene structure annotation is a challenging computational problem in genomics. The best results are achieved with spliced alignment of full-length cDNAs or multiple expressed sequence tags (ESTs) with sufficient overlap to cover the entire gene. For most species, cDNA and EST collections are far from comprehensive. We sought to overcome this bottleneck by exploring the possibility of using combined EST resources from fairly diverged species that still share a common gene space. Previous spliced alignment tools were found inadequate for this task because they rely on very high sequence similarity between the ESTs and the genomic DNA.

Results: We have developed a computer program, GeneSeqer, which is capable of aligning thousands of ESTs with a long genomic sequence in a reasonable amount of time. The algorithm is uniquely designed to tolerate a high percentage of mismatches and insertions or deletions in the EST relative to the genomic template. This feature allows use of non-cognate ESTs for gene structure prediction, including ESTs derived from duplicated genes and homologous genes from related species. The increased gene prediction sensitivity results in part from novel splice site prediction models that are also available as a stand-alone splice site prediction tool. We assessed GeneSeqer performance relative to a standard Arabidopsis thaliana gene set and demonstrate its utility for plant genome annotation. In particular, we propose that this method provides a timely tool for the annotation of the rice genome, using abundant ESTs from other cereals and plants.

Availability: The source code is available for download at http://bioinformatics.iastate.edu/bioinformatics2go/gs/download.html. Web servers for Arabidopsis and other plant species are accessible at http://www.plantgdb.org/cgi-bin/AtGeneSeqer.cgi and http://www.plantgdb.org/cgi-bin/GeneSeqer.cgi, respectively. For non-plant species, use http://bioinformatics.iastate.edu/cgi-bin/gs.cgi. The splice site prediction tool (SplicePredictor) is distributed with the GeneSeqer code. A SplicePredictor web server is available at http://bioinformatics.iastate.edu/cgi-bin/sp.cgi

Supplementary information:  http://www.plantgdb.org/AtGDB/prj/BXZ03B
An evaluation of new criteria for CpG islands in the human genome as gene markers
Authors: Wang Yong , Leung Frederick C.C.
Published: March 2004

Motivation: Recently, more stringent criteria for CpG islands have been introduced to exclude Alu repeats, thereby enabling a higher proportion of CpG islands associating with genes to be identified. Using these new criteria, several types of associations between CpG islands and genes were investigated to further establish the importance of CpG islands as gene markers.

Results: The CpG islands were searched by CpGIE, a java software program developed for CpG island identification. CpGIE was advanced in identification accuracy compared with other tools. According to our results, about 70% of the identified CpG islands were associating with the human genes and over half of them are in the promoters. Furthermore, the investigation of genes in the confirmed gene model showed that 56% of them had a CpG island overlapping the transcription start sites. In comparison, the new criteria were found capable of filtering a large fraction of Alu repeats that was identified as CpG islands by the generally accepted criteria within the genes, but very few CpG islands associating with the promoters were affected. The genes in the predicted gene model were not obviously associated with CpG islands, suggesting that CpG islands can be used to evaluate the accuracy of gene annotation.

Availability:  http://bioinfo.hku.hk/cpgieintro
Recognizing names in biomedical texts: a machine learning approach
Authors: Zhou GuoDong , Zhang Jie , Su Jian , Shen Dan , Tan ChewLim
Published: March 2004

Motivation: With an overwhelming amount of textual information in molecular biology and biomedicine, there is a need for effective and efficient literature mining and knowledge discovery that can help biologists to gather and make use of the knowledge encoded in text documents. In order to make organized and structured information available, automatically recognizing biomedical entity names becomes critical and is important for information retrieval, information extraction and automated knowledge acquisition.

Results: In this paper, we present a named entity recognition system in the biomedical domain, called PowerBioNE. In order to deal with the special phenomena of naming conventions in the biomedical domain, we propose various evidential features: (1) word formation pattern; (2) morphological pattern, such as prefix and suffix; (3) part-of-speech; (4) head noun trigger; (5) special verb trigger and (6) name alias feature. All the features are integrated effectively and efficiently through a hidden Markov model (HMM) and a HMM-based named entity recognizer. In addition, a k-Nearest Neighbor (k-NN) algorithm is proposed to resolve the data sparseness problem in our system. Finally, we present a pattern-based post-processing to automatically extract rules from the training data to deal with the cascaded entity name phenomenon. From our best knowledge, PowerBioNE is the first system which deals with the cascaded entity name phenomenon. Evaluation shows that our system achieves the F-measure of 66.6 and 62.2 on the 23 classes of GENIA V3.0 and V1.1, respectively. In particular, our system achieves the F-measure of 75.8 on the ‘protein’ class of GENIA V3.0. For comparison, our system outperforms the best published result by 7.8 on GENIA V1.1, without help of any dictionaries. It also shows that our HMM and the k-NN algorithm outperform other models, such as back-off HMM, linear interpolated HMM, support vector machines, C4.5, C4.5 rules and RIPPER, by effectively capturing the local context dependency and resolving the data sparseness problem. Moreover, evaluation on GENIA V3.0 shows that the post-processing for the cascaded entity name phenomenon improves the F-measure by 3.9. Finally, error analysis shows that about half of the errors are caused by the strict annotation scheme and the annotation inconsistency in the GENIA corpus. This suggests that our system achieves an acceptable F-measure of 83.6 on the 23 classes of GENIA V3.0 and in particular 86.2 on the ‘protein’ class, without help of any dictionaries. We think that a F-measure of 90 on the 23 classes of GENIA V3.0 and in particular 92 on the ‘protein’ class, can be achieved through refining of the annotation scheme in the GENIA corpus, such as flexible annotation scheme and annotation consistency, and inclusion of a reasonable biomedical dictionary.

Availability: A demo system is available at http://textmining.i2r.a-star.edu.sg/NLS/demo.htm. Technology license is available upon the bilateral agreement.
Probabilistic inference of molecular networks from noisy data sources
Authors: Iossifov Ivan , Krauthammer Michael , Friedman Carol , Hatzivassiloglou Vasileios , Bader Joel S. , White Kevin P. , Rzhetsky Andrey
Published: March 2004

Summary: Information on molecular networks, such as networks of interacting proteins, comes from diverse sources that contain remarkable differences in distribution and quantity of errors. Here, we introduce a probabilistic model useful for predicting protein interactions from heterogeneous data sources. The model describes stochastic generation of protein–protein interaction networks with real-world properties, as well as generation of two heterogeneous sources of protein-interaction information: research results automatically extracted from the literature and yeast two-hybrid experiments. Based on the domain composition of proteins, we use the model to predict protein interactions for pairs of proteins for which no experimental data are available. We further explore the prediction limits, given experimental data that cover only part of the underlying protein networks. This approach can be extended naturally to include other types of biological data sources.
A metric model of amino acid substitution
Authors: Xu Weijia , Miranker Daniel P.
Published: March 2004

Motivation: We address the question of whether there exists an effective evolutionary model of amino-acid substitution that forms a metric-distance function. There is always a trade-off between speed and sensitivity among competing computational methods of determining sequence homology. A metric model of evolution is a prerequisite for the development of an entire class of fast sequence analysis algorithms that are both scalable, O(log n) and sensitive.

Results: We have reworked the mathematics of the point accepted mutation model (PAM) by calculating the expected time between accepted mutations in lieu of calculating log-odds probabilities. The resulting substitution matrix (mPAM) forms a metric. We validate the application of the mPAM evolutionary model for sequence homology by executing sequence queries from a controlled yeast protein homology search benchmark. We compare the accuracy of the results of mPAM and PAM similarity matrices as well as three prior metric models. The experiment shows that mPAM significantly outperforms the other three metrics and sufficiently approaches the sensitivity of PAM250 to make it applicable to the management of protein sequence databases.
Protein isoelectric point as a predictor for increased crystallization screening efficiency
Authors: Kantardjieff Katherine A. , Rupp Bernhard
Published: March 2004

Motivation: Increased efficiency in initial crystallization screening reduces cost and material requirements in structural genomics. Because pH is one of the few consistently reported parameters in the Protein Data Bank (PDB), the isoelectric point (pI) of a protein has been explored as a useful indirect predictor for the optimal choice of range and distribution of the pH sampling in crystallization trials.

Results: We have analyzed 9596 unique protein crystal forms from the August 2003 PDB and have found a significant relationship between the calculated pI of successfully crystallized proteins and the difference between pI and reported pH at which they were crystallized. These preferences provide strong prior information for the design of crystallization screening experiments with significantly increased efficiency and corresponding reduction in material requirements, leading to potential cost savings of millions of US$ for structural genomics projects involving high-throughput crystallographic structure determination.

Availability: A prototype example of a screen design and efficiency estimator program, CrysPred, is available at http://www-structure.llnl.gov/cryspred/
ConSeq: the identification of functionally and structurally important residues in protein sequences
Authors: Berezin Carine , Glaser Fabian , Rosenberg Josef , Paz Inbal , Pupko Tal , Fariselli Piero , Casadio Rita , Ben-Tal Nir
Published: March 2004

Motivation: ConSeq is a web server for the identification of biologically important residues in protein sequences. Functionally important residues that take part, e.g. in ligand binding and protein–protein interactions, are often evolutionarily conserved and are most likely to be solvent-accessible, whereas conserved residues within the protein core most probably have an important structural role in maintaining the protein's fold. Thus, estimated evolutionary rates, as well as relative solvent accessibility predictions, are assigned to each amino acid in the sequence; both are subsequently used to indicate residues that have potential structural or functional importance.

Availability: The ConSeq web server is available at http://conseq.bioinfo.tau.ac.il/

Supplementary information: The ConSeq methodology, a description of its performance in a set of five well-documented proteins, a comparison to other methods, and the outcome of its application to a set of 111 proteins of unknown function, are presented at http://conseq.bioinfo.tau.ac.il/ under ‘OVERVIEW’, ‘VALIDATION’, ‘COMPARISON’ and ‘PREDICTIONS’, respectively.
2LD, GENECOUNTING and HAP: computer programs for linkage disequilibrium analysis
Authors: Zhao Jing Hua
Published: March 2004

Summary: Computer programs are introduced which calculate pair-wise linkage disequilibrium statistics and conduct haplotype frequency estimation, including X chromosome data, and using a heuristic algorithm to handle multiple genetic markers and missing data.

Availability: Programs 2LD, GENECOUNTING and HAP are available on Internet from http://www.hgmp.mrc.ac.uk/~jzhao and http://www.iop.kcl.ac.uk/IoP/Departments/PsychMed/GEpiBSt/software.shtml
CVD: the intestinal crypt/villus in situ hybridization database
Authors: Olsen Line , Hansen Morten , Ekstrøm Claus T. , Troelsen Jesper T. , Olsen Jørgen
Published: March 2004

Summary: The intestinal crypt/villus in situ hybridization database (CVD) query interface is a web-based tool to search for genes with similar relative expression patterns along the crypt/villus axis of the mammalian intestine. The CVD is an online database holding information for relative gene expression patterns in the mammalian intestine and is based on the scoring of in situ hybridization experiments reported in the literature. CVD contains expression data for 88 different genes collected from 156 different in situ hybridization profiles. The web-based query interface allows execution of both single gene queries and pattern searches. The query results provide links to the most relevant public gene databases.

Availability:  http://pc113.imbg.ku.dk/ps/
Growing genetic regulatory networks from seed genes
Authors: Hashimoto Ronaldo F. , Kim Seungchan , Shmulevich Ilya , Zhang Wei , Bittner Michael L. , Dougherty Edward R.
Published: March 2004

Motivation: A number of models have been proposed for genetic regulatory networks. In principle, a network may contain any number of genes, so long as data are available to make inferences about their relationships. Nevertheless, there are two important reasons why the size of a constructed network should be limited. Computationally and mathematically, it is more feasible to model and simulate a network with a small number of genes. In addition, it is more likely that a small set of genes maintains a specific core regulatory mechanism.

Results: Subnetworks are constructed in the context of a directed graph by beginning with a seed consisting of one or more genes believed to participate in a viable subnetwork. Functionalities and regulatory relationships among seed genes may be partially known or they may simply be of interest. Given the seed, we iteratively adjoin new genes in a manner that enhances subnetwork autonomy. The algorithm is applied using both the coefficient of determination and the Boolean-function influence among genes, and it is illustrated using a glioma gene-expression dataset.

Availability: Software for the seed-growing algorithm will be available at the website for Probabilistic Boolean Networks: http://www2.mdanderson.org/app/ilya/PBN/PBN.htm
Poorly conserved ORFs in the genome of the archaea Halobacterium sp. NRC-1 correspond to expressed proteins
Authors: Shmuely H. , Dinitz E. , Dahan I. , Eichler J. , Fischer D. , Shaanan B.
Published: March 2004

Motivation: A large fraction of open reading frames (ORFs) identified as ‘hypothetical’ proteins correspond to either ‘conserved hypothetical’ proteins, representing sequences homologous to ORFs of unknown function from other organisms, or to hypothetical proteins lacking any significant sequence similarity to other ORFs in the databases. Elucidating the functions and three-dimensional structures of such orphan ORFs, termed ORFans or poorly conserved ORFs (PCOs), is essential for understanding biodiversity. However, it has been claimed that many ORFans may not encode for expressed proteins.

Results: A genome-wide experimental study of ‘paralogous PCOs’ in the halophilic archaea Halobacterium sp. NRC-1 was conducted. Paralogous PCOs are ORFs with at least one homolog in the same organism, but with no clear homologs in other organisms. The results reveal that mRNA is synthesized for a majority of the Halobacterium sp. NRC-1 paralogous PCO families, including those comprising relatively short proteins, strongly suggesting that these Halobacterium sp. NRC-1 paralogous PCOs correspond to true, expressed proteins. Hence, further computational and experimental studies aimed at characterizing PCOs in this and other organisms are merited. Such efforts could shed light on PCOs' functions and origins, thereby serving to elucidate the vast diversity observed in the genetic material.
WebVar: a resource for the rapid estimation of relative site variability from multiple sequence alignments
Authors: Mignone Flavio , Horner David S. , Pesole Graziano
Published: March 2004

Summary: WebVar is an online resource that provides estimates of relative site variability from multiple alignments of homologous protein or nucleic acid sequences. WebVar provides a variety of graphic and textual representations of estimates, designed to assist in phylogenetic analysis.

Availability: The WebVar server is located at http://www.pesolelab.it/Tools/WebVar.html
Correction of sequence-based artifacts in serial analysis of gene expression
Authors: Akmaev Viatcheslav R. , Wang Clarence J.
Published: March 2004

Motivation: Serial Analysis of Gene Expression (SAGE) is a powerful technology for measuring global gene expression, through rapid generation of large numbers of transcript tags. Beyond their intrinsic value in differential gene expression analysis, SAGE tag collections afford abundant information on the size and shape of the sample transcriptome and can accelerate novel gene discovery. These latter SAGE applications are facilitated by the enhanced method of Long SAGE. A characteristic of sequencing-based methods, such as SAGE and Long SAGE is the unavoidable occurrence of artifact sequences resulting from sequencing errors. By virtue of their low-random incidence, such tag errors have minimal impact on differential expression analysis. However, to fully exploit the value of large SAGE tag datasets, it is desirable to account for and correct tag artifacts.

Results: We present estimates for occurrences of tag errors, and an efficient error correction algorithm. Error rate estimates are based on a stochastic model that includes the Polymerase chain reaction and sequencing error contributions. The correction algorithm, SAGEScreen, is a multi-step procedure that addresses ditag processing, estimation of empirical error rates from highly abundant tags, grouping of similar-sequence tags and statistical testing of observed counts. We apply SAGEScreen to Long SAGE libraries and compare error rates for several processing scenarios. Results with simulated tag collections indicate that SAGEScreen corrects 78% of recoverable tag errors and reduces the occurrences of singleton tags.

Availability: The SAGEScreen software is available for academic users from the first author.
CNplot: visualizing pre-clustered networks
Authors: Batada Nizar N.
Published: March 2004

Summary: CNplot is a simple technique for the visualization of global connectivity within pre-clustered network data. CNplot is easy to implement and in most cases produces informative and satisfactory summary of the data.

Availability: A Java implementation is available that allows users to modify graphics parameters and produces a LaTeX output. This software is free and is available at http://csb.stanford.edu/nbatada/VCN.html
Analysing microarray data using modular regulation analysis
Authors: Curtis R. Keira , Brand Martin D.
Published: March 2004

Motivation: Microarray experiments measure complex changes in the abundance of many mRNAs under different conditions. Current analysis methods cannot distinguish between direct and indirect effects on expression, or calculate the relative importance of mRNAs in effecting responses.

Results: Application of modular regulation analysis to microarray data reveals and quantifies which mRNA changes are important for cellular responses. The mRNAs are clustered, and then we calculate how perturbations alter each cluster and how strongly those clusters affect an output response. The product of these values quantifies how an input changes a response through each cluster.

Two published datasets are analysed. Two mRNA clusters transmit most of the response of yeast doubling time to galactose; one contains mainly galactose metabolic genes, and the other a regulatory gene. Analysis of the response of yeast relative fitness to 2-deoxy-d-glucose reveals that control is distributed between several mRNA clusters, but experimental error limits statistical significance.
ParSeq: searching motifs with structural and biochemical properties
Authors: Schmollinger M. , Fischer I. , Nerz C. , Pinkenburg S. , Götz F. , Kaufmann M. , Lange K.-J. , Reuter R. , Rosenstiel W. , Zell A.
Published: March 2004

Summary: Searches for variable motifs such as protein-binding sites or promoter regions are more complex than the search for casual motifs. For example, in amino acid sequences comparing motifs alone mostly proves to be insufficient to detect regions that represent proteins with a special function, because the function depends on biochemical properties of individual amino acids (such as polarity or hydrophobicity). Pure string matching programs are not able to find these motifs; hence, we developed ParSeq, a program that combines the search for motifs with certain structural properties, the verification of biochemical properties, an approximate search mechanism and a stepwise creation of the motif description by allowing to search on previously obtained results.

Availability:  http://www-pr.informatik.uni-tuebingen.de/parseq
Prediction of Saccharomyces cerevisiae protein functional class from functional domain composition
Authors: Cai Yu-Dong , Doig Andrew J.
Published: March 2004

Motivation: A key goal of genomics is to assign function to genes, especially for orphan sequences.

Results: We compared the clustered functional domains in the SBASE database to each protein sequence using BLASTP. This representation for a protein is a vector, where each of the non-zero entries in the vector indicates a significant match between the sequence of interest and the SBASE domain. The machine learning methods nearest neighbour algorithm (NNA) and support vector machines are used for predicting protein functional classes from this information. We find that the best results are found using the SBASE-A database and the NNA, namely 72% accuracy for 79% coverage. We tested an assigning function based on searching for InterPro sequence motifs and by taking the most significant BLAST match within the dataset. We applied the functional domain composition method to predict the functional class of 2018 currently unclassified yeast open reading frames.

Availability: A program for the prediction method, that uses NNA called Functional Class Prediction based on Functional Domains (FCPFD) is available and can be obtained by contacting Y.D.Cai at y.cai@umist.ac.uk
NetAffx Gene Ontology Mining Tool: a visual approach for microarray data analysis
Authors: Cheng Jill , Sun Shaw , Tracy Adam , Hubbell Earl , Morris Joseph , Valmeekam Venu , Kimbrough Andrew , Cline Melissa S. , Liu Guoying , Shigeta Ron , Kulp David , Siani-Rose Michael A.
Published: March 2004

Summary: The NetAffx Gene Ontology (GO) Mining Tool is a web-based, interactive tool that permits traversal of the GO graph in the context of microarray data. It accepts a list of Affymetrix probe sets and renders a GO graph as a heat map colored according to significance measurements. The rendered graph is interactive, with nodes linked to public web sites and to lists of the relevant probe sets. The GO Mining Tool provides visualization combining biological annotation with expression data, encompassing thousands of genes in one interactive view.

Availability: GO Mining Tool is freely available at http://www.affymetrix.com/analysis/query/go_analysis.affx
GOstat: find statistically overrepresented Gene Ontologies within a group of genes
Authors: Beißbarth Tim , Speed Terence P.
Published: March 2004

Summary: Modern experimental techniques, as for example DNA microarrays, as a result usually produce a long list of genes, which are potentially interesting in the analyzed process. In order to gain biological understanding from this type of data, it is necessary to analyze the functional annotations of all genes in this list. The Gene-Ontology (GO) database provides a useful tool to annotate and analyze the functions of a large number of genes. Here, we introduce a tool that utilizes this information to obtain an understanding of which annotations are typical for the analyzed list of genes. This program automatically obtains the GO annotations from a database and generates statistics of which annotations are overrepresented in the analyzed list of genes. This results in a list of GO terms sorted by their specificity.

Availability: Our program GOstat is accessible via the Internet at http://gostat.wehi.edu.au
TANDEM: matching proteins with tandem mass spectra
Authors: Craig Robertson , Beavis Ronald C.
Published: March 2004

Summary: Tandem mass spectra obtained from fragmenting peptide ions contain some peptide sequence specific information, but often there is not enough information to sequence the original peptide completely. Several proprietary software applications have been developed to attempt to match the spectra with a list of protein sequences that may contain the sequence of the peptide. The application TANDEM was written to provide the proteomics research community with a set of components that can be used to test new methods and algorithms for performing this type of sequence-to-data matching.

Availability: The source code and binaries for this software are available at http://www.proteome.ca/opensource.html, for Windows, Linux and Macintosh OSX. The source code is made available under the Artistic License, from the authors.
Modeling T-cell activation using gene expression profiling and state-space models
Authors: Rangel Claudia , Angus John , Ghahramani Zoubin , Lioumi Maria , Sotheran Elizabeth , Gaiba Alessia , Wild David L. , Falciani Francesco
Published: March 2004

Motivation: We have used state-space models to reverse engineer transcriptional networks from highly replicated gene expression profiling time series data obtained from a well-established model of T-cell activation. State space models are a class of dynamic Bayesian networks that assume that the observed measurements depend on some hidden state variables that evolve according to Markovian dynamics. These hidden variables can capture effects that cannot be measured in a gene expression profiling experiment, e.g. genes that have not been included in the microarray, levels of regulatory proteins, the effects of messenger RNA and protein degradation, etc.

Results: Bootstrap confidence intervals are developed for parameters representing ‘gene–gene’ interactions over time. Our models represent the dynamics of T-cell activation and provide a methodology for the development of rational and experimentally testable hypotheses.

Availability: Supplementary data and Matlab computer source code will be made available on the web at the URL given below.

Supplementary information:  http://public.kgi.edu/~wild/LDS/index.htm
ToPNet—an application for interactive analysis of expression data and biological networks
Authors: Hanisch Daniel , Sohler Florian , Zimmer Ralf
Published: March 2004

Summary: ToPNet is a new tool for the combined visualization and exploration of gene networks and expression data. ToPNet provides various ways of restricting, manipulating and combining biological networks according to annotation data (e.g. Gene Ontology terms) and presents results to the user via different visualization procedures and hyperlinks to the underlying data sources. To easily identify relevant parts of the network, ToPNet provides a method of detecting significant subnetworks with respect to expression measurements. As ToPNet is a pure JAVA application with additional scripting capabilities, it is well-suited as a test-bed for algorithm development and exploratory biological data analysis alike.

Availability: ToPNet is freely available for academic institutions at http://www.biosolveit.de/ToPNet/
QDist—quartet distance between evolutionary trees
Authors: Mailund Thomas , Pedersen Christian N. S.
Published: March 2004

Summary: QDist is a program for computing the quartet distance between two unrooted trees, i.e. the number of quartet topology differences between the trees, where a quartet topology is the topological subtree induced by four species. The program is based on an algorithm with running time O(n log2n), which makes it practical to compare large trees. Available under GNU license.

Availability:  http://www.birc.dk/Software/QDist
Application of the GA/KNN method to SELDI proteomics data
Authors: Li Leping , Umbach David M. , Terry Paul , Taylor Jack A.
Published: March 2004

Summary: Proteomics technology has shown promise in identifying biomarkers for disease, toxicant exposure and stress. We show by example that the genetic algorithm/k-nearest neighbors method, developed for mining high-dimensional microarray gene expression data, is also capable of mining surface enhanced laser desorption/ionization–time-of-flight proteomics data.

Availability: The source code of the program and documentation on how to use it are freely available to non-commercial users at http://dir.niehs.nih.gov/dirbb/lifiles/softlic.htm
Analysis of disturbed images
Authors: Kauer Gerhard , Blöcker Helmut
Published: March 2004

Motivation: Images in cellular and molecular biology (from microscopy, blots, biochips, etc.) are often disturbed, so that the detection and analysis of the respective relevant geometrical objects may be difficult or error-prone. The disturbances are either caused by the detector, usually a CCD camera, or by the experimental setup. Furthermore, microtechnology experiments often require simultaneous multiple-colour stainings. Therefore, the image analysis of such experiments should be colour-sensitive, and colour shadings should not only be detectable but also quantifiable.

Results: Here, we describe a general solution as applied to the analysis of blots and DNA chips as well as to microscopy images of tissues. We decided to use (i) a stochastic filter as used by Wiener for image segmentation as the starting point for object detection, (ii) chaincodes as described by Freeman for object description, (iii) a novel ‘rolling disc algorithm’ to spot the objects to be analysed and (iv) an HSI instead of an RGB colour model for colour analysis. With this combination we succeeded in performing shape detection and colour-based analysis of disturbed images.

Availability: The corresponding modules (C++) are available on request.
Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach
Authors: Nielsen Morten , Lundegaard Claus , Worning Peder , Hvid Christina Sylvester , Lamberth Kasper , Buus Søren , Brunak Søren , Lund Ole
Published: March 2004

Motivation: Prediction of which peptides will bind a specific major histocompatibility complex (MHC) constitutes an important step in identifying potential T-cell epitopes suitable as vaccine candidates. MHC class II binding peptides have a broad length distribution complicating such predictions. Thus, identifying the correct alignment is a crucial part of identifying the core of an MHC class II binding motif. In this context, we wish to describe a novel Gibbs motif sampler method ideally suited for recognizing such weak sequence motifs. The method is based on the Gibbs sampling method, and it incorporates novel features optimized for the task of recognizing the binding motif of MHC classes I and II. The method locates the binding motif in a set of sequences and characterizes the motif in terms of a weight-matrix. Subsequently, the weight-matrix can be applied to identifying effectively potential MHC binding peptides and to guiding the process of rational vaccine design.

Results: We apply the motif sampler method to the complex problem of MHC class II binding. The input to the method is amino acid peptide sequences extracted from the public databases of SYFPEITHI and MHCPEP and known to bind to the MHC class II complex HLA-DR4(B1*0401). Prior identification of information-rich (anchor) positions in the binding motif is shown to improve the predictive performance of the Gibbs sampler. Similarly, a consensus solution obtained from an ensemble average over suboptimal solutions is shown to outperform the use of a single optimal solution. In a large-scale benchmark calculation, the performance is quantified using relative operating characteristics curve (ROC) plots and we make a detailed comparison of the performance with that of both the TEPITOPE method and a weight-matrix derived using the conventional alignment algorithm of ClustalW. The calculation demonstrates that the predictive performance of the Gibbs sampler is higher than that of ClustalW and in most cases also higher than that of the TEPITOPE method.
GeneSyn: a tool for detecting conserved gene order across genomes
Authors: Pavesi G. , Mauri G. , Iannelli F. , Gissi C. , Pesole G.
Published: March 2004

Summary: GeneSyn is a software tool that allows automatic detection of conserved gene order from annotated genomes.

Availability: Available free of charge for Unix/Linux/Cygwin platforms at ftp://159.149.110.11/pub/GeneSyn_1.0/

Supplementary information:  ftp://159.149.110.11/pub/GeneSyn_1.0/
Spectral Repeat Finder (SRF): identification of repetitive sequences using Fourier transformation
Authors: Sharma Deepak , Issac Biju , Raghava G. P. S. , Ramaswamy R.
Published: March 2004

Motivation: Repetitive DNA sequences, besides having a variety of regulatory functions, are one of the principal causes of genomic instability. Understanding their origin and evolution is of fundamental importance for genome studies. The identification of repeats and their units helps in deducing the intra-genomic dynamics as an important feature of comparative genomics. A major difficulty in identification of repeats arises from the fact that the repeat units can be either exact or imperfect, in tandem or dispersed, and of unspecified length.

Results: The Spectral Repeat Finder program circumvents these problems by using a discrete Fourier transformation to identify significant periodicities present in a sequence. The specific regions of the sequence that contribute to a given periodicity are located through a sliding window analysis, and an exact search method is then used to find the repetitive units. Efficient and complete detection of repeats is provided together with interactive and detailed visualization of the spectral analysis of input sequence. We demonstrate the utility of our method with various examples that contain previously unannotated repeats. A Web server has been developed for convenient access to the automated program.

Availability: The Web server is available at http://www.imtech.res.in/raghava/srf and http://www2.imtech.res.in/raghava/srf
Enhanced homology searching through genome reading frame predetermination
Authors: Yuan Jeffrey , Bush Bruce , Elbrecht Alex , Liu Yuan , Zhang Theresa , Zhao Wenqing , Blevins Richard
Published: March 2004

Motivation: Many bioinformatic approaches exist for finding novel genes within genomic sequence data. Traditionally, homology search-based methods are often the first approach employed in determining whether a novel gene exists that is similar to a known gene. Unfortunately, distantly related genes or motifs often are difficult to find using single query-based homology search algorithms against large sequence datasets such as the human genome. Therefore, the motivation behind this work was to develop an approach to enhance the sensitivity of traditional single query-based homology algorithms against genomic data without losing search selectivity.

Results: We demonstrate that by searching against a genome fragmented into all possible reading frames, the sensitivity of homology-based searches is enhanced without degrading its selectivity. Using the ETS-domain, bromodomain and acetyl-CoA acetyltransferase gene as queries, we were able to demonstrate that direct protein–protein searches using BLAST2P or FASTA3 against a human genome segmented among all possible reading frames and translated was substantially more sensitive than traditional protein–DNA searches against a raw genomic sequence using an application such as TBLAST2N. Receiver operating characteristic analysis was employed to demonstrate that the algorithms remained selective, while comparisons of the algorithms showed that the protein–protein searches were more sensitive in identifying hits. Therefore, through the overprediction of reading frames by this method and the increased sensitivity of protein–protein based homology search algorithms, a genome can be deeply mined, potentially finding hits overlooked by protein–DNA searches against raw genomic data.