bluuebunny/crossref_metadata_2025_split huggingface dataset:
On the significance of sequence alignments when using multiple scoring matrices
Authors: Frommlet Florian , Futschik Andreas , Bogdan Małgorzata 
Published: March 2004

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.