bluuebunny/crossref_metadata_2025_split huggingface dataset:
I-Band Titin in Cardiac Muscle Is a Three-Element Molecular Spring and Is Critical for Maintaining Thin Filament Structure
Authors: Linke Wolfgang A. , Rudy Diane E. , Centner Thomas , Gautel Mathias , Witt Christian , Labeit Siegfried , Gregorio Carol C. 
Published: July 2002

In cardiac muscle, the giant protein titin exists in different length isoforms expressed in the molecule's I-band region. Both isoforms, termed N2-A and N2-B, comprise stretches of Ig-like modules separated by the PEVK domain. Central I-band titin also contains isoform-specific Ig-motifs and nonmodular sequences, notably a longer insertion in N2-B. We investigated the elastic behavior of the I-band isoforms by using single-myofibril mechanics, immunofluorescence microscopy, and immunoelectron microscopy of rabbit cardiac sarcomeres stained with sequence-assigned antibodies. Moreover, we overexpressed constructs from the N2-B region in chick cardiac cells to search for possible structural properties of this cardiac-specific segment.
We found that cardiac titin contains three distinct elastic elements: poly-Ig regions, the PEVK domain, and the N2-B sequence insertion, which extends ∼60 nm at high physiological stretch. Recruitment of all three elements allows cardiac titin to extend fully reversibly at physiological sarcomere lengths, without the need to unfold Ig domains. Overexpressing the entire N2-B region or its NH2 terminus in cardiac myocytes greatly disrupted thin filament, but not thick filament structure. Our results strongly suggest that the NH2-terminal N2-B domains are necessary to stabilize thin filament integrity. N2-B–titin emerges as a unique region critical for both reversible extensibility and structural maintenance of cardiac myofibrils.
Profilin Enhances Cdc42-Induced Nucleation of Actin Polymerization
Authors: Yang Changsong , Huang Minzhou , DeBiasio John , Pring Martin , Joyce Michael , Miki Hiroaki , Takenawa Tadaomi , Zigmond Sally H. 
Published: July 2002

We find that profilin contributes in several ways to Cdc42-induced nucleation of actin filaments in high speed supernatant of lysed neutrophils. Depletion of profilin inhibited Cdc42-induced nucleation; re-addition of profilin restored much of the activity. Mutant profilins with a decreased affinity for either actin or poly-l-proline were less effective at restoring activity. Whereas Cdc42 must activate Wiskott-Aldrich Syndrome protein (WASP) to stimulate nucleation by the Arp2/3 complex, VCA (verpolin homology, cofilin, and acidic domain contained in the COOH-terminal fragment of N-WASP) constitutively activates the Arp2/3 complex. Nucleation by VCA was not inhibited by profilin depletion. With purified N-WASP and Arp2/3 complex, Cdc42-induced nucleation did not require profilin but was enhanced by profilin, wild-type profilin being more effective than mutant profilin with reduced affinity for poly-l-proline.
Nucleation by the Arp2/3 complex is a function of the free G-actin concentration. Thus, when profilin addition decreased the free G-actin concentration, it inhibited Cdc42- and VCA-induced nucleation. However, when profilin was added with G-actin in a ratio that maintained the initial free G-actin concentration, it increased the rate of both Cdc42- and VCA-induced nucleation. This enhancement, also seen with purified proteins, was greatest when the free G-actin concentration was low. These data suggest that under conditions present in intact cells, profilin enhances nucleation by activated Arp2/3 complex.
DIVCLUS: an automatic method in the GEANFAMMER package that finds homologous domains in single- and multi-domain proteins.
Authors: Park J , Teichmann S A 
Published: July 2002

Abstract
MOTIVATION: Large-scale determination of relationships between the proteins produced by genome sequences is now common. All protein sequences are matched and those that have high match scores are clustered into families. In cases where the proteins are built of several domains or duplication modules, this can lead to misleading results. Consider the very simple example of three proteins: 1, formed by duplication modules A and B; 2, formed by duplication modules B' and C; and 3, formed by duplication modules C' and D. Duplication modules B and B' are homologous, as are C and C'. Matching the sequences of 1, 2 and 3 followed by simple single-linkage clustering would put all three in the same family, even though proteins 1 and 3 are not related. This is because the different parts of 2 match 1 and 3. This paper describes a procedure, DIVCLUS, that divides such complex clusters of partially related sequences into simple clusters that contain only related duplication modules. In the example just given, it would produce two groups of sequences: the first with domains B of sequence 1 and B of sequence 2, and the second with domain C of sequence 2 and C of sequence 3. DIVCLUS is part of a package called GEANFAMMER, for GEnome ANalysis and protein FAMily MakER. The package automates the detection of families of duplication modules from a protein sequence database. RESULTS: DIVCLUS has been applied to the division of single-linkage clusters generated from the protein sequences of six completely sequenced bacterial genomes. Out of 12 013 genes in these six genomes, 4563 single- and multi-domain sequences formed 1071 complex clusters. Application of the DIVCLUS program resolved these clusters into 2113 clusters corresponding to single duplication modules. AVAILABILITY: The perl5 program and its documentation are available at the following address: http://www.mrc-lmb.cam.ac.uk/genomes/ and by anonymous ftp at ftp.mrc-lmb.cam.ac.uk in the directory /pub/genomes/Software/. CONTACT: sat@mrc-lmb.cam.ac.uk; jong@mrc-lmb. cam.ac.uk
Statistics of large-scale sequence searching.
Authors: Spang R , Vingron M 
Published: July 2002

Abstract
MOTIVATION: Database search programs such as FASTA, BLAST or a rigorous Smith-Waterman algorithm produce lists of database entries, which are assumed to be related to the query. The computation of statistical significance of similarity scores is well established for single pairs of sequences and using purely random models. However, the multi-trial context of a database search poses new problems. The credibility of a certain score obtained in a database search decreases with the amount of data that is compared. To improve p-value computation for database search experiments, statistical properties of the databases, such as the distribution of sequence length and effects induced by frequently repeated sequence patterns, need to be taken into account. RESULTS: We investigated the SWISS-PROT protein database Release 31.0 running extensive simulations of database searches. A discrepancy is observed between the theoretical predictions and the empirical distribution. To correct for this, we evaluate the statistical significance of scores in the context of a database search by a contrasting semi-random model. This model enhances purely random models by one additional parameter reflecting individual statistical properties of real databases. We call this parameter the effective size of the database. CONTACT: r.spang@dkfz-heidelberg.de;m.vingron@dkfz-hei del berg.de
An RNA folding method capable of identifying pseudoknots and base triples.
Authors: Tabaska J E , Cary R B , Gabow H N , Stormo G D 
Published: July 2002

Abstract
MOTIVATION: Recently, we described a Maximum Weighted Matching (MWM) method for RNA structure prediction. The MWM method is capable of detecting pseudoknots and other tertiary base-pairing interactions in a computationally efficient manner (Cary and Stormo, Proceedings of the Third International Conference on Intelligent Systems for Molecular Biology, pp. 75-80, 1995). Here we report on the results of our efforts to improve the MWM method's predictive accuracy, and show how the method can be extended to detect base interactions formerly inaccessible to automated RNA modeling techniques. RESULTS: Improved performance in MWM structure prediction was achieved in two ways. First, new ways of calculating base pair likelihoods have been developed. These allow experimental data and combined statistical and thermodynamic information to be used by the program. Second, accuracy was improved by developing techniques for filtering out spurious base pairs predicted by the MWM program. We also demonstrate here a means by which the MWM folding method may be used to detect the presence of base triples in RNAs. AVAILABILITY: http://www.cshl.org/mzhanglab/tabaska/j axpage. html CONTACT: tabaska@cshl.org
BAliBASE: a benchmark alignment database for the evaluation of multiple alignment programs.
Authors: Thompson J D , Plewniak F , Poch O 
Published: July 2002

Abstract
SUMMARY: BAliBASE is a database of manually refined multiple sequence alignments categorized by core blocks of conservation sequence length, similarity, and the presence of insertions and N/C-terminal extensions. AVAILABILITY: From http://www-igbmc. u-strasbg.fr/BioInfo/BAliBASE/index.html
USAGE: a web-based approach towards the analysis of SAGE data
Authors: van Kampen A. H. C. , van Schaik B. D. C. , Pauws E. , Michiels E. M. C. , Ruijter J. M. , Caron H. N. , Versteeg R. , Heisterkamp S. H. , Leunissen J. A. M. , Baas F. , van der Mee M. 
Published: July 2002

Abstract
Motivation: SAGE enables the determination of genome-wide mRNA expression profiles. A comprehensive analysis of SAGE data requires software, which integrates (statistical) data analysis methods with a database system. Furthermore, to facilitate data sharing between users, the application should reside on a central server and be accessed via the internet. Since such an application was not available we developed the USAGE package.
Results: USAGE is a web-based application that comprises an integrated set of tools, which offers many functions for analysing and comparing SAGE data. Additionally, USAGE includes a statistical method for the planning of new SAGE experiments. USAGE is available in a multi-user environment giving users the option of sharing data. USAGE is interfaced to a relational database to store data and analysis results. The USAGE query editor allows the composition of queries for searching this database. Several database functions have been included which enable the selection and combination of data. USAGE provides the biologist increased functionality and flexibility for analysing SAGE data.
Availability: USAGE is freely accessible for academic institutions at http://www.cmbi.kun.nl/usage/. The source code of USAGE is freely available for academic institutions on request from the first author.
Contact: a.h.vankampen@amc.uva.nl
To whom correspondence should be addressed.
Finding pathogenicity islands and gene transfer events in
genome data
Authors: Liò Pietro , Vannucci Marina 
Published: July 2002

Abstract
Motivation: There is a growing literature on wavelet theory and wavelet methods showing improvements on more classical techniques, especially in the contexts of smoothing and extraction of fundamental components of signals. G+Cpatterns occur at different lengths (scales) and, for this reason, G+Cplots are usually difficult to interpret. Current methods for genome analysis choose a window size and compute a \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \({\chi}^{2}\) \end{document}statistics of the average value for each window with respect to the whole genome.
Results: Firstly, wavelets are used to smooth G+Cprofiles to locate characteristic patterns in genome sequences. The method we use is based on performing a \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \({\chi}^{2}\) \end{document}statistics on the wavelet coefficients of a profile; thus we do not need to choose a fixed window size, in that the smoothing occurs at a set of different scales. Secondly, a wavelet scalogram is used as a measure for sequence profile comparison; this tool is very general and can be applied to other sequence profiles commonly used in genome analysis. We show applications to the analysis of Deinococcus radiodurans chromosome I, of two strains of Helicobacter pylori (26695, J99) and two of Neisseria meningitidis (serogroup B strain MC58 and serogroup A strain Z2491). We report a list of loci that have different G+Ccontent with respect to the nearby regions; the analysis of N. meningitidis serogroup B shows two new large regions with low G+Ccontent that are putative pathogenicity islands.
Availability: Software and numerical results (profiles, scalograms, high and low frequency components) for all the genome sequences analyzed are available upon request from the authors.
Contact: p.lio@zoo.cam.ac.uk
To whom correspondence should be addressed.
Homology-based gene structure prediction: simplified matching
algorithm using a translated codon (tron) and improved accuracy by
allowing for long gaps
Authors: Gotoh Osamu 
Published: July 2002

Abstract
Motivation: Locating protein-coding exons (CDSs) on a eukaryotic genomic DNA sequence is the initial and an essential step in predicting the functions of the genes embedded in that part of the genome. Accurate prediction of CDSs may be achieved by directly matching the DNA sequence with a known protein sequence or profile of a homologous family member(s).
Results: A new convention for encoding a DNA sequence into a series of 23 possible letters (translated codon or tron code) was devised to improve this type of analysis. Using this convention, a dynamic programming algorithm was developed to align a DNA sequence and a protein sequence or profile so that the spliced and translated sequence optimally matches the reference the same as the standard protein sequence alignment allowing for long gaps. The objective function also takes account of frameshift errors, coding potentials, and translational initiation, termination and splicing signals. This method was tested on Caenorhabditis elegans genes of known structures. The accuracy of prediction measured in terms of a correlation coefficient (CC) was about 95% at the nucleotide level for the 288 genes tested, and 97.0% for the 170 genes whose product and closest homologue share more than 30% identical amino acids. We also propose a strategy to improve the accuracy of prediction for a set of paralogous genes by means of iterative gene prediction and reconstruction of the reference profile derived from the predicted sequences.
Availability: The source codes for the program ‘aln’ written in ANSI-C and the test data will be available via anonymous FTP at ftp.genome.ad.jp/pub/genomenet/saitama-cc.
Contact: gotoh@cancer-c.pref.saitama.jp
Automatic discovery of regulatory patterns in promoter regions
based on whole cell expression data and functional annotation
Authors: Juhl Jensen Lars , Knudsen Steen 
Published: July 2002

Abstract
Motivation: The whole genomes submitted to GenBank contain valuable information about the function of genes as well as the upstream sequences and whole cell expression provides valuable information on gene regulation. To utilize these large amounts of data for a biological understanding of the regulation of gene expression, new automatic methods for pattern finding are needed.
Results: Two word-analysis algorithms for automatic discovery of regulatory sequence elements have been developed. We show that sequence patterns correlated to whole cell expression data can be found using Kolmogorov–Smirnov tests on the raw data, thereby eliminating the need for clustering co-regulated genes. Regulatory elements have also been identified by systematic calculations of the significance of correlations between words found in the functional annotation of genes and DNA words occuring in their promoter regions. Application of these algorithms to the Saccharomyces cerevisiae genome and publicly available DNA array data sets revealed a highly conserved 9-mer occuring in the upstream regions of genes coding for proteasomal subunits. Several other putative and known regulatory elements were also found.
Availability: Upon request.
Contact: steen@cbs.dtu.dk
TrExML: a maximum-likelihood approach for extensive tree-space
exploration
Authors: Wolf Marty J. , Easteal Simon , Kahn Margaret , McKay Brendan D. , Jermiin Lars S. 
Published: July 2002

Abstract
Motivation: Maximum-likelihood analysis of nucleotide and amino acid sequences is a powerful approach for inferring phylogenetic relationships and for comparing evolutionary hypotheses. Because it is a computationally demanding and time-consuming process, most algorithms explore only a minute portion of tree-space, with the emphasis on finding the most likely tree while ignoring the less likely, but not significantly worse, trees. However, when such trees exist, it is equally important to identify them to give due consideration to the phylogenetic uncertainty. Consequently, it is necessary to change the focus of these algorithms such that near optimal trees are also identified.
Results: This paper presents the Advanced Stepwise Addition Algorithmfor exploring tree-space and two algorithms for generating all binary trees on a set of sequences. The Advanced Stepwise Addition Algorithm has been implemented in TrExML, a phylogenetic program for maximum-likelihood analysis of nucleotide sequences. TrExML is shown to be more effective at finding near optimal trees than a similar program, fastDNAml, implying that TrExML offers a better approach to account for phylogenetic uncertainty than has previously been possible. A program, TreeGen, is also described; it generates binary trees on a set of sequences allowing for extensive exploration of tree-space using other programs.
Availability: TreeGen, TrExML, and the sequence data used to test the programs are available from the following two WWW sites: http://whitetail.bemidji.msus.edu/trexml/and http://jcsmr.anu.edu.au/dmm/humgen.html.
Contact: mjwolf@whitetail.bemidji.msus.edu; Simon.Easteal@anu.edu.au; Margaret.Kahn@anu.edu.au; bdm@cs.anu.edu.au; jermiin@angis.usyd.edu.au
NAIL—Network Analysis Interface for Linking HMMER results
Authors: Sánchez-Pulido Luis , Yuan Yan P. , Andrade Miguel A. , Bork Peer 
Published: July 2002

Abstract
Summary: Network Analysis Interface for Linking HMMER results (NAIL) is a web-based tool for the analysis of results from a HMMER protein database-search. NAIL facilitates the selection of protein hits and the creation of an alignment, which can be used for a new sequence similarity search.
Availability: From http://www.bork.embl-heidelberg.de/NAIL/
Contact: sanchez@cnb.uam.es
* To whom correspondence should be addressed.
Selection of optimal DNA oligos for gene expression arrays
Authors: Li Fugen , Stormo Gary D. 
Published: July 2002

Abstract
Motivation: High density DNA oligo microarrays are widely used in biomedical research. Selection of optimal DNA oligos that are deposited on the microarrays is critical. Based on sequence information and hybridization free energy, we developed a new algorithm to select optimal short (20–25 bases) or long (50 or 70 bases) oligos from genes or open reading frames (ORFs) and predict their hybridization behavior. Having optimized probes for each gene is valuable for two reasons. By minimizing background hybridization they provide more accurate determinations of true expression levels. Having optimum probes minimizes the number of probes needed per gene, thereby decreasing the cost of each microarray, raising the number of genes on each chip and increasing its usage.
Results: In this paper we describe algorithms to optimize the selection of specific probes for each gene in an entire genome. The criteria for truly optimum probes are easily stated but they are not computable at all levels currently. We have developed an heuristic approach that is efficiently computable at all levels and should provide a good approximation to the true optimum set. We have run the program on the complete genomes for several model organisms and deposited the results in a database that is available on-line (http://ural.wustl.edu/~lif/probe.pl).
Availability: The program is available upon request.
Contact: lif@ural.wustl.edu; stormo@ural.wustl.edu
MELTING, computing the melting temperature of nucleic acid
duplex
Authors: Le
   Novère Nicolas 
Published: July 2002

Abstract
Summary: MELTING computes the enthalpy and entropy of an oligonucleotide duplex helix–coil transition, and then its melting temperature. The program uses the method of nearest-neighbours. The set of thermodynamic parameters can be easily customized. The program provides several correction methods for the concentration of salt. MELTING is a free program, available at no cost and open-source. Perl scripts are provided to show how MELTING can be used to construct more ambitious programs.
Availability: MELTING is available for several platforms (http://www.pasteur.fr/recherche/unites/neubiomol/meltinghome.html) and is accessible via a www server (http://bioweb.pasteur.fr/seqanal/interfaces/melting.html).
Contact: nl223@cus.cam.ac.uk
3Dee: a database of protein structural domains
Authors: Siddiqui Asim S. , Dengler Uwe , Barton Geoffrey J. 
Published: July 2002

Abstract
Summary: The 3Dee database is a repository of protein structural domains. It stores alternative domain definitions for the same protein, organises domains into sequence and structural hierarchies, contains non-redundant set(s) of sequences and structures, multiple structure alignments for families of domains, and allows previous versions of the database to be regenerated.
Availability: 3Dee is accessible on the World Wide Web at the URL http://barton.ebi.ac.uk/servers/3Dee.html
Contact: geoff@ebi.ac.uk; http://barton.ebi.ac.uk
* To whom correspondence should be addressed. Present address: EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
Mining literature for protein–protein interactions
Authors: Marcotte Edward M. , Xenarios Ioannis , Eisenberg David 
Published: July 2002

Abstract
Motivation: A central problem in bioinformatics is how to capture information from the vast current scientific literature in a form suitable for analysis by computer. We address the special case of information on protein–protein interactions, and show that the frequencies of words in Medline abstracts can be used to determine whether or not a given paper discusses protein–protein interactions. For those papers determined to discuss this topic, the relevant information can be captured for the Database of Interacting Proteins. Furthermore, suitable gene annotations can also be captured.
Results: Our Bayesian approach scores Medline abstracts for probability of discussing the topic of interest according to the frequencies of discriminating words found in the abstract. More than 80 discriminating words (e.g. complex, interaction, two-hybrid) were determined from a training set of 260 Medline abstracts corresponding to previously validated entries in the Database of Interacting Proteins. Using these words and a log likelihood scoring function, \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \({\sim}\) \end{document}2000 Medline abstracts were identified as describing interactions between yeast proteins. This approach now forms the basis for the rapid expansion of the Database of Interacting Proteins.
Contact: marcotte@icmb.utexas.edu; ixenario@mbi.ucla.edu; david@mbi.ucla.edu
* These authors contributed equally to this work.