bluuebunny/crossref_metadata_2025_split huggingface dataset:
eF-site and PDBjViewer: database and viewer for protein functional sites
Authors: Kinoshita Kengo , Nakamura Haruki 
Published: March 2004

Abstract
Summary: The electrostatic-surface of functional site (eF-site) is a database for the molecular surfaces of protein functional sites. To enable browsing of each molecular surface along with the atomic model, we have developed a new three-dimensional interactive viewer, PDBjViewer, that can be used both as an applet and as a stand-alone program.
Availability: The eF-site database and PDBjViewer are freely available from http://www.pdbj.org/eF-site/
Open source clustering software
Authors: de Hoon M.J.L. , Imoto S. , Nolan J. , Miyano S. 
Published: March 2004

Abstract
Summary: We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C.
Availability: The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.
Automated ordering of fingerprinted clones
Authors: Flibotte Stephane , Chiu Readman , Fjell Chris , Krzywinski Martin , Schein Jacqueline E. , Shin Heesun , Marra Marco A. 
Published: March 2004

Abstract
Motivation: A considerable amount of human intervention is currently required to produce high-quality fingerprint-based physical maps for genomic studies.
Results: An algorithm has been developed and implemented to automatically order fingerprinted clones within contigs. The resulting software, named CORAL (Clone ORdering ALgorithm), has been tested on maps that have previously been manually edited and on maps derived from in silico simulations. The fingerprint map and DNA sequence of the human genome has provided an additional test to CORAL. Measurements suggest that CORAL performs significantly better than the software currently used by most laboratories to order fingerprinted clones at throughputs far exceeding those that can be achieved manually.
Availability: Available on request from the authors.
GeneAnnot: comprehensive two-way linking between oligonucleotide array probesets and GeneCards genes
Authors: Chalifa-Caspi Vered , Yanai Itai , Ophir Ron , Rosen Naomi , Shmoish Michael , Benjamin-Rodrig Hila , Shklar Maxim , Stein Tsippi Iny , Shmueli Orit , Safran Marilyn , Lancet Doron 
Published: March 2004

Abstract
Motivation: High density oligonucleotide arrays are usually annotated in a one-to-one fashion, with each probeset assigned to one gene. However, in reality, subsets of oligonucleotides in a probeset may match sequences within more than one gene, potentially leading to misinterpretations. Moreover, a gene is often represented by more than one probeset, and analyzing probe matches at the mRNA level can help one deduce whether these probesets are derived from the same or different splice variants.
Results: The GeneAnnot system comprehensively documents the many-to-many relationship between oligonucleotide array probesets and annotated genes in GeneCards™. It performs pairwise alignments between the probe sequences and gene transcripts, and assigns sensitivity and specificity scores to each probeset/gene pair.
Availability: http://genecards.weizmann.ac.il/geneannot/
Supplementary information: Program description and statistics http://genecards.weizmann.ac.il/geneannot/DOC/index.html
RAG: RNA-As-Graphs database—concepts, analysis, and features
Authors: Gan Hin Hark , Fera Daniela , Zorn Julie , Shiffeldrim Nahum , Tang Michael , Laserson Uri , Kim Namhee , Schlick Tamar 
Published: March 2004

Abstract
Motivation: Understanding RNA's structural diversity is vital for identifying novel RNA structures and pursuing RNA genomics initiatives. By classifying RNA secondary motifs based on correlations between conserved RNA secondary structures and functional properties, we offer an avenue for predicting novel motifs. Although several RNA databases exist, no comprehensive schemes are available for cataloguing the range and diversity of RNA's structural repertoire.
Results: Our RNA-As-Graphs (RAG) database describes and ranks all mathematically possible (including existing and candidate) RNA secondary motifs on the basis of graphical enumeration techniques. We represent RNA secondary structures as two-dimensional graphs (networks), specifying the connectivity between RNA secondary structural elements, such as loops, bulges, stems and junctions. We archive RNA tree motifs as ‘tree graphs’ and other RNAs, including pseudoknots, as general ‘dual graphs’. All RNA motifs are catalogued by graph vertex number (a measure of sequence length) and ranked by topological complexity. The RAG inventory immediately suggests candidates for novel RNA motifs, either naturally occurring or synthetic, and thereby might stimulate the prediction and design of novel RNA motifs.
Availability: The database is accessible on the web at http://monod.biomath.nyu.edu/rna
Automatic prediction of protein domains from sequence information using a hybrid learning system
Authors: Nagarajan Niranjan , Yona Golan 
Published: March 2004

Abstract
Motivation: We describe a novel method for detecting the domain structure of a protein from sequence information alone. The method is based on analyzing multiple sequence alignments that are derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence and are combined into a single predictor using a neural network. The output is further smoothed and post-processed using a probabilistic model to predict the most likely transition positions between domains.
Results: The method was assessed using the domain definitions in SCOP and CATH for proteins of known structure and was compared with several other existing methods. Our method performs well both in terms of accuracy and sensitivity. It improves significantly over the best methods available, even some of the semi-manual ones, while being fully automatic. Our method can also be used to suggest and verify domain partitions based on structural data. A few examples of predicted domain definitions and alternative partitions, as suggested by our method, are also discussed.
Availability: An online domain-prediction server is available at http://biozon.org/tools/domains/
ACID: a database for microarray clone information
Authors: Ringnér Markus , Veerla Srinivas , Andersson Samuel , Staaf Johan , Häkkinen Jari 
Published: March 2004

Abstract
Summary: Array Close Information Database is an online database for information about microarray cDNA clones. For each clone, the database contents include assigned UniGene cluster(s), location in the full-length transcript, assigned gene ontology terms and position in the genome assembly.
Availability: http://bioinfo.thep.lu.se/acid.html
A comparison of scoring functions for protein sequence profile alignment
Authors: Edgar Robert C. , Sjölander Kimmen 
Published: March 2004

Abstract
Motivation:In recent years, several methods have been proposed for aligning two protein sequence profiles, with reported improvements in alignment accuracy and homolog discrimination versus sequence–sequence methods (e.g. BLAST) and profile–sequence methods (e.g. PSI-BLAST). Profile–profile alignment is also the iterated step in progressive multiple sequence alignment algorithms such as CLUSTALW. However, little is known about the relative performance of different profile–profile scoring functions. In this work, we evaluate the alignment accuracy of 23 different profile–profile scoring functions by comparing alignments of 488 pairs of sequences with identity ≤30% against structural alignments. We optimize parameters for all scoring functions on the same training set and use profiles of alignments from both PSI-BLAST and SAM-T99. Structural alignments are constructed from a consensus between the FSSP database and CE structural aligner. We compare the results with sequence–sequence and sequence–profile methods, including BLAST and PSI-BLAST.
Results: We find that profile–profile alignment gives an average improvement over our test set of typically 2–3% over profile–sequence alignment and ∼40% over sequence–sequence alignment. No statistically significant difference is seen in the relative performance of most of the scoring functions tested. Significantly better results are obtained with profiles constructed from SAM-T99 alignments than from PSI-BLAST alignments.
Availability: Source code, reference alignments and more detailed results are freely available at http://phylogenomics.berkeley.edu/profilealignment/
COACH: profile–profile alignment of protein families using hidden Markov models
Authors: Edgar Robert C. , Sjölander Kimmen 
Published: March 2004

Abstract
Motivation: Alignments of two multiple-sequence alignments, or statistical models of such alignments (profiles), have important applications in computational biology. The increased amount of information in a profile versus a single sequence can lead to more accurate alignments and more sensitive homolog detection in database searches. Several profile–profile alignment methods have been proposed and have been shown to improve sensitivity and alignment quality compared with sequence–sequence methods (such as BLAST) and profile–sequence methods (e.g. PSI-BLAST). Here we present a new approach to profile–profile alignment we call Comparison of Alignments by Constructing Hidden Markov Models (HMMs) (COACH). COACH aligns two multiple sequence alignments by constructing a profile HMM from one alignment and aligning the other to that HMM.
Results: We compare the alignment accuracy of COACH with two recently published methods: Yona and Levitt's prof_sim and Sadreyev and Grishin's COMPASS. On two sets of reference alignments selected from the FSSP database, we find that COACH is able, on average, to produce alignments giving the best coverage or the fewest errors, depending on the chosen parameter settings.
Availability: COACH is freely available from www.drive5.com/lobster
Site2genome: locating short DNA sequences in whole genomes
Authors: Frith Martin C. , Halees Anason S. , Hansen Ulla , Weng Zhiping 
Published: March 2004

Abstract
Summary: Many biological papers describe short, functional DNA sites without specifying their exact positions in the genome. We have developed a Web server that automates the tedious task of locating such sites in eukaryotic genomes, thus giving access to the context of rich annotations that are increasingly available for genome sequences.
Availability: http://zlab.bu.edu/site2genome/
A hint to search for metalloproteins in gene banks
Authors: Andreini Claudia , Bertini Ivano , Rosato Antonio 
Published: March 2004

Abstract
Motivation: With the advent of genome sequencing, a huge database of protein primary sequences has been accumulating. In parallel, a number of tools to investigate and expand upon this information, e.g. reconstructing and building relationships between protein families and superfamilies, have been developed. Metalloproteins are proteins capable of binding one or more metal ions, which are required for their biological function or for regulation of their activities or for structural purposes. Sometimes, metal binding can be observed in vitro but not be physiologically relevant. At present, there is a lack of specific tools to address the matter of the identification of metalloproteins in databases of gene sequences.
Results: In the present work, an approach exploiting metal-binding patterns (MBPs) of metalloproteins present in the Protein Data Bank to search gene banks for new metalloproteins is presented and applied to copper proteins. Nearly 100 different MBPs have been identified and then used for subsequent applications. The ensemble of sequences of the whole PDB is used to assess the potentiality and limits of the method and to identify levels of confidence for the predictions output by the search. It appears that copper-binding capabilities are identified with a confidence &gt;90% when the percentage of identical amino acids aligned around the MBP by PHI-BLAST is at least 20% with respect to the entire protein domain length. If this percentage is between 10% and 20%, the level of confidence is ∼50%. Application of the methodology to the entire genome sequences of Pyrococcus furiosus, Escherichia coli, Drosophila melanogaster and Homo sapiens suggests some differentiation between prokaryotes and eukaryotes.
Supplementary information: A table reporting statistics on the MBP identified; a list of all hits retrieved for the four organisms considered; a figure showing the number of hits for the four organisms as a function of IdGlobal.
PartiGene—constructing partial genomes
Authors: Parkinson John , Anthony Alasdair , Wasmuth James , Schmid Ralf , Hedley Ann , Blaxter Mark 
Published: March 2004

Abstract
Expressed sequence tags (ESTs) offer a low-cost approach to gene discovery and are being used by an increasing number of laboratories to obtain sequence information for a wide variety of organisms. The challenge lies in processing and organizing this data within a genomic context to facilitate large scale analyses. Here we present PartiGene, an integrated sequence analysis suite that uses freely available public domain software to (1) process raw trace chromatograms into sequence objects suitable for submission to dbEST; (2) place these sequences within a genomic context; (3) perform customizable first-pass annotation of the data; and (4) present the data as HTML tables and an SQL database resource. PartiGene has been used to create a number of non-model organism database resources including NEMBASE (http://www.nematodes.org) and LumbriBase (http://www.earthworms.org/). The packages are readily portable, freely available and can be run on simple Linux-based workstations.
Availability: PartiGene is available from http://www.nematodes.org/PartiGene and also forms part of the EST analysis software, associated with the Natural Environmental Research Council (UK) Bio-Linux project (http://envgen.nox.ac.uk/biolinux.html).
Simple sequence repeat marker loci discovery using SSR primer
Authors: Robinson Andrew J. , Love Christopher G. , Batley Jacqueline , Barker Gary , Edwards David 
Published: March 2004

Abstract
Summary: Simple sequence repeats (SSRs) have become important molecular markers for a broad range of applications, such as genome mapping and characterization, phenotype mapping, marker assisted selection of crop plants and a range of molecular ecology and diversity studies. With the increase in the availability of DNA sequence information, an automated process to identify and design PCR primers for amplification of SSR loci would be a useful tool in plant breeding programs. We report an application that integrates SPUTNIK, an SSR repeat finder, with Primer3, a PCR primer design program, into one pipeline tool, SSR Primer. On submission of multiple FASTA formatted sequences, the script screens each sequence for SSRs using SPUTNIK. The results are parsed to Primer3 for locus-specific primer design. The script makes use of a Web-based interface, enabling remote use.
Availability: This program has been written in PERL and is freely available for non-commercial users by request from the authors. The Web-based version may be accessed at http://hornbill.cspp.latrobe.edu.au/
Align-m—a new algorithm for multiple alignment of highly divergent sequences
Authors: Van Walle Ivo , Lasters Ignace , Wyns Lode 
Published: March 2004

Abstract
Motivation: Multiple alignment of highly divergent sequences is a challenging problem for which available programs tend to show poor performance. Generally, this is due to a scoring function that does not describe biological reality accurately enough or a heuristic that cannot explore solution space efficiently enough. In this respect, we present a new program, Align-m, that uses a non-progressive local approach to guide a global alignment.
Results: Two large test sets were used that represent the entire SCOP classification and cover sequence similarities between 0 and 50% identity. Performance was compared with the publicly available algorithms ClustalW, T-Coffee and DiAlign. In general, Align-m has comparable or slightly higher accuracy in terms of correctly aligned residues, especially for distantly related sequences. Importantly, it aligns much fewer residues incorrectly, with average differences of over 15% compared with some of the other algorithms.
Availability: Align-m and the test sets are available at http://bioinformatics.vub.ac.be
VARAN: a web server for Variability Analysis of DNA microarray experiments
Authors: Golfier G. , Dang M. Tran , Dauphinot L. , Graison E. , Rossier J. , Potier M.-C. 
Published: March 2004

Abstract
Summary: Here, we describe a tool for VARiability Analysis of DNA microarrays experiments (VARAN), a freely available Web server that performs a signal intensity based analysis of the log2 expression ratio variability deduced from DNA microarray data (one or two channels). Two modules are proposed: VARAN generator to compute a sliding windows analysis of the experimental variability (mean and SD) and VARAN analyzer to compare experimental data with an asymptotic variability model previously built with the generator module from control experiments. Both modules provide normalized intensity signals with five possible methods, log ratio values and a list of genes showing significant variations between conditions.
Availability: http://www.bionet.espci.fr/varan/
Supplementary information: http://www.bionet.espci.fr/varan/help.html
Evaluation and optimization of clustering in gene expression data analysis
Authors: Famili A. Fazel , Liu Ganming , Liu Ziying 
Published: March 2004

Abstract
Motivation: A measurement of cluster quality is needed to choose potential clusters of genes that contain biologically relevant patterns of gene expression. This is strongly desirable when a large number of gene expression profiles have to be analyzed and proper clusters of genes need to be identified for further analysis, such as the search for meaningful patterns, identification of gene functions or gene response analysis.
Results: We propose a new cluster quality method, called stability, by which unsupervised learning of gene expression data can be performed efficiently. The method takes into account a cluster's stability on partition. We evaluate this method and demonstrate its performance using four independent, real gene expression and three simulated datasets. We demonstrate that our method outperforms other techniques listed in the literature. The method has applications in evaluating clustering validity as well as identifying stable clusters.
Availability: Please contact the first author.
A perturbation-based method for calculating explicit likelihood of evolutionary co-variance in multiple sequence alignments
Authors: Dekker John P. , Fodor Anthony , Aldrich Richard W. , Yellen Gary 
Published: March 2004

Abstract
Motivation: The constituent amino acids of a protein work together to define its structure and to facilitate its function. Their interdependence should be apparent in the evolutionary record of each protein family: positions in the sequence of a protein family that are intimately associated in space or in function should co-vary in evolution. A recent approach by Ranganathan and colleagues proposes to look at subsets of a protein family, selected for their sequence at one position, to see how this affects variation at other positions.
Results: We present a quantitative algorithm for assessing covariation with this approach, based on explicit likelihood calculations. By applying our algorithm to 138 Pfam families with at least one member of known structure, we demonstrate that our method has improved power in finding physically close residues in crystal structures, compared to that of Ranganathan and colleagues.
Supplementary information: www.afodor.net/bioinfosup.html
A graph theoretical approach for predicting common RNA secondary structure motifs including pseudoknots in unaligned sequences
Authors: Ji Yongmei , Xu Xing , Stormo Gary D. 
Published: March 2004

Abstract
Motivation: RNA structure motifs contained in mRNAs have been found to play important roles in regulating gene expression. However, identification of novel RNA regulatory motifs using computational methods has not been widely explored. Effective tools for predicting novel RNA regulatory motifs based on genomic sequences are needed.
Results: We present a new method for predicting common RNA secondary structure motifs in a set of functionally or evolutionarily related RNA sequences. This method is based on comparison of stems (palindromic helices) between sequences and is implemented by applying graph-theoretical approaches. It first finds all possible stable stems in each sequence and compares stems pairwise between sequences by some defined features to find stems conserved across any two sequences. Then by applying a maximum clique finding algorithm, it finds all significant stems conserved across at least k sequences. Finally, it assembles in topological order all possible compatible conserved stems shared by at least k sequences and reports a number of the best assembled stem sets as the best candidate common structure motifs. This method does not require prior structural alignment of the sequences and is able to detect pseudoknot structures. We have tested this approach on some RNA sequences with known secondary structures, in which it is capable of detecting the real structures completely or partially correctly and outperforms other existing programs for similar purposes.
Availability: The algorithm has been implemented in C++ in a program called comRNA, which is available at http://ural.wustl.edu/softwares.html
Protein secondary structure: entropy, correlations and prediction
Authors: Crooks Gavin E. , Brenner Steven E. 
Published: March 2004

Abstract
Motivation: Is protein secondary structure primarily determined by local interactions between residues closely spaced along the amino acid backbone or by non-local tertiary interactions? To answer this question, we measure the entropy densities of primary and secondary structure sequences, and the local inter-sequence mutual information density.
Results: We find that the important inter-sequence interactions are short ranged, that correlations between neighboring amino acids are essentially uninformative and that only one-fourth of the total information needed to determine the secondary structure is available from local inter-sequence correlations. These observations support the view that the majority of most proteins fold via a cooperative process where secondary and tertiary structure form concurrently. Moreover, existing single-sequence secondary structure prediction algorithms are almost optimal, and we should not expect a dramatic improvement in prediction accuracy.
Availability: Both the data sets and analysis code are freely available from our Web site at http://compbio.berkeley.edu/