bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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