INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73132, 2007, 'bio', 'PEAKS: identification of regulatory motifs by their position in DNA sequences', 'Bellora, Nicolás|Farré, Domènec|Mar Albà, M', 'Research Unit on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona 08003, Spain.|Research Unit on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona 08003, Spain.|Research Unit on Biomedical Informatics, Universitat Pompeu Fabra, Barcelona 08003, Spain.', 'Spain|Spain|Spain', 12, 'Algorithms|Base Sequence|Chromosome Mapping|DNA|Molecular Sequence Data|Pattern Recognition, Automated|Regulatory Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Software|Transcriptional Activation', 'Journal Article', '10.1093/bioinformatics/btl568', '17098773', 'Many DNA functional motifs tend to accumulate or cluster at specific gene locations. These locations can be detected, in a group of gene sequences, as high frequency peaks with respect to a reference position, such as the transcription start site (TSS). We have developed a web tool for the identification of regions containing significant motif peaks. We show, by using different yeast gene datasets, that peak regions are strongly enriched in experimentally-validated motifs and contain potentially important novel motifs.'),
(73133, 2007, 'bio', 'Using GOstats to test gene lists for GO term association', 'Falcon, S|Gentleman, R', 'Fred Hutchison Cancer Research Center, Program Computational Biology,1100 Fairview Avenue North P. O. Box 19024, Seattle, WA 98109, USA. sfalcon@fhcrc.org|Fred Hutchison Cancer Research Center, Program Computational Biology,1100 Fairview Avenue North P. O. Box 19024, Seattle, WA 98109, USA. sfalcon@fhcrc.org', 'United States|United States', 0, 'Algorithms|Data Interpretation, Statistical|Database Management Systems|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Proteins|Software|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/btl567', '17098774', 'Functional analyses based on the association of Gene Ontology (GO) terms to genes in a selected gene list are useful bioinformatic tools and the GOstats package has been widely used to perform such computations. In this paper we report significant improvements and extensions such as support for conditional testing.'),
(73134, 2007, 'bio', 'Predicting transcription factor affinities to DNA from a biophysical model', 'Roider, Helge G|Kanhere, Aditi|Manke, Thomas|Vingron, Martin', 'Max-Planck-Institute for Molecular Genetics Ihnestrasse 73, 14195 Berlin, Germany.|Max-Planck-Institute for Molecular Genetics Ihnestrasse 73, 14195 Berlin, Germany.|Max-Planck-Institute for Molecular Genetics Ihnestrasse 73, 14195 Berlin, Germany.|Max-Planck-Institute for Molecular Genetics Ihnestrasse 73, 14195 Berlin, Germany.', 'Germany|Germany|Germany|Germany', 134, 'Algorithms|Binding Sites|Biophysics|Computer Simulation|DNA|Models, Biological|Models, Chemical|Protein Binding|Sequence Analysis, DNA|Transcription Factors|Transcription, Genetic', 'Evaluation Studies', '10.1093/bioinformatics/btl565', '17098775', 'Theoretical efforts to understand the regulation of gene expression are traditionally centered around the identification of transcription factor binding sites at specific DNA positions. More recently these efforts have been supplemented by experimental data for relative binding affinities of proteins to longer intergenic sequences. The question arises to what extent these two approaches converge. In this paper, we adopt a physical binding model to predict the relative binding affinity of a transcription factor for a given sequence.'),
(73135, 2007, 'bio', 'Interpretation of ANOVA models for microarray data using PCA', 'de Haan, J R|Wehrens, R|Bauerschmidt, S|Piek, E|van Schaik, R C|Buydens, L M C', 'Institute for Molecules and Materials, Analytical Chemistry, Radboud University Nijmegen Toernooiveld 1, 6525 ED, Nijmegen, The Netherlands.|Institute for Molecules and Materials, Analytical Chemistry, Radboud University Nijmegen Toernooiveld 1, 6525 ED, Nijmegen, The Netherlands.|Institute for Molecules and Materials, Analytical Chemistry, Radboud University Nijmegen Toernooiveld 1, 6525 ED, Nijmegen, The Netherlands.|Institute for Molecules and Materials, Analytical Chemistry, Radboud University Nijmegen Toernooiveld 1, 6525 ED, Nijmegen, The Netherlands.|Institute for Molecules and Materials, Analytical Chemistry, Radboud University Nijmegen Toernooiveld 1, 6525 ED, Nijmegen, The Netherlands.|Institute for Molecules and Materials, Analytical Chemistry, Radboud University Nijmegen Toernooiveld 1, 6525 ED, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 51, 'Algorithms|Analysis of Variance|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btl572', '17105717', 'ANOVA is a technique, which is frequently used in the analysis of microarray data, e.g. to assess the significance of treatment effects, and to select interesting genes based on P-values. However, it does not give information about what exactly is causing the effect. Our purpose is to improve the interpretation of the results from ANOVA on large microarray datasets, by applying PCA on the individual variance components. Interaction effects can be visualized by biplots, showing genes and variables in one plot, providing insight in the effect of e.g. treatment or time on gene expression. Because ANOVA has removed uninteresting sources of variance, the results are much more interpretable than without ANOVA. Moreover, the combination of ANOVA and PCA provides a simple way to select genes, based on the interactions of interest.'),
(73136, 2007, 'bio', 'Reliable prediction of Drosha processing sites improves microRNA gene prediction', 'Helvik, Snorre A|Snøve, Ola|Saetrom, Pål', 'Department of Computer and Information Science, Norwegian University of Science and Technology, NO-7052 Trondheim, Norway.|Department of Computer and Information Science, Norwegian University of Science and Technology, NO-7052 Trondheim, Norway.|Department of Computer and Information Science, Norwegian University of Science and Technology, NO-7052 Trondheim, Norway.', 'Norway|Norway|Norway', 81, 'Artificial Intelligence|Base Sequence|Binding Sites|MicroRNAs|Molecular Sequence Data|Protein Binding|RNA Processing, Post-Transcriptional|Ribonuclease III|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btl570', '17105718', 'Mature microRNAs (miRNAs) are processed from long hairpin transcripts. Even though it is only the first of several steps, the initial Drosha processing defines the mature product and is characteristic for all miRNA genes. Methods that can separate between true and false processing sites are therefore essential to miRNA gene discovery.'),
(73137, 2007, 'bio', 'Detecting protein dissimilarities in multiple alignments using Bayesian variable selection', 'Kim, Sinae|Tsai, Jerry|Kagiampakis, Ioannis|LiWang, Patricia|Vannucci, Marina', 'Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.|Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.|Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.|Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.|Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA.', 'United States|United States|United States|United States|United States', 2, 'Algorithms|Amino Acid Sequence|Bayes Theorem|Conserved Sequence|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/btl566', '17105719', 'We present an application of Bayesian variable selection to the novel detection of sequence elements that confer negative design to protein structure and function. As an illustration, we analyze the different dimer interfaces between the CXCL8 chemokine family with the CCL4 and CCL2 chemokine families to discover the changes that disfavor CXCL8 of quaternary structure.'),
(73138, 2007, 'bio', 'Complementary intron sequence motifs associated with human exon repetition: a role for intragenic, inter-transcript interactions in gene expression', 'Dixon, Richard J|Eperon, Ian C|Samani, Nilesh J', 'Department of Cardiovascular Sciences Leicester, LE3 9Q, UK. rd67@le.ac.uk|Department of Cardiovascular Sciences Leicester, LE3 9Q, UK. rd67@le.ac.uk|Department of Cardiovascular Sciences Leicester, LE3 9Q, UK. rd67@le.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 23, 'Chromosome Mapping|Conserved Sequence|DNA, Complementary|Exons|Gene Expression|Genome, Human|Humans|Introns|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btl575', '17105720', 'Exon repetition describes the presence of tandemly repeated exons in mRNA in the absence of duplications in the genome. The regulation of this process is not fully understood. We therefore investigated the entire flanking intronic sequences of exons involved in exon repetition for common sequence elements.'),
(73139, 2007, 'bio', 'Striped Smith-Waterman speeds database searches six times over other SIMD implementations', 'Farrar, Michael', 'farrar.michael@gmail.com', '-', 0, 'Algorithms|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis|Time Factors', 'Comparative Study', '10.1093/bioinformatics/btl582', '17110365', 'The only algorithm guaranteed to find the optimal local alignment is the Smith-Waterman. It is also one of the slowest due to the number of computations required for the search. To speed up the algorithm, Single-Instruction Multiple-Data (SIMD) instructions have been used to parallelize the algorithm at the instruction level.'),
(73140, 2007, 'bio', 'Network neighborhood analysis with the multi-node topological overlap measure', 'Li, Ai|Horvath, Steve', 'Department of Biostatistics, School of Public Health, University of California, Los Angeles, CA 90095-1772, USA.|Department of Biostatistics, School of Public Health, University of California, Los Angeles, CA 90095-1772, USA.', 'United States|United States', 90, 'Algorithms|Biomarkers, Tumor|Brain Neoplasms|Computer Simulation|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Models, Biological|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btl581', '17110366', 'The goal of neighborhood analysis is to find a set of genes (the neighborhood) that is similar to an initial seed set of genes. Neighborhood analysis methods for network data are important in systems biology. If individual network connections are susceptible to noise, it can be advantageous to define neighborhoods on the basis of a robust interconnectedness measure, e.g. the topological overlap measure. Since the use of multiple nodes in the seed set may lead to more informative neighborhoods, it can be advantageous to define multi-node similarity measures.'),
(73141, 2006, 'bio', 'GARD: a genetic algorithm for recombination detection', 'Kosakovsky Pond, Sergei L|Posada, David|Gravenor, Michael B|Woelk, Christopher H|Frost, Simon D W', 'Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA. spond@ucsd.edu|Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA. spond@ucsd.edu|Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA. spond@ucsd.edu|Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA. spond@ucsd.edu|Department of Pathology, University of California San Diego, La Jolla, CA 92093, USA. spond@ucsd.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Simulation|Conserved Sequence|Evolution, Molecular|Models, Genetic|Molecular Sequence Data|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btl474', '17110367', 'Phylogenetic and evolutionary inference can be severely misled if recombination is not accounted for, hence screening for it should be an essential component of nearly every comparative study. The evolution of recombinant sequences can not be properly explained by a single phylogenetic tree, but several phylogenies may be used to correctly model the evolution of non-recombinant fragments.'),
(73142, 2007, 'bio', 'SAGA: a subgraph matching tool for biological graphs', 'Tian, Yuanyuan|McEachin, Richard C|Santos, Carlos|States, David J|Patel, Jignesh M', 'Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States|United States|United States|United States', 150, 'Algorithms|Computer Graphics|Computer Simulation|Database Management Systems|Databases, Protein|Models, Biological|Pattern Recognition, Automated|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl571', '17110368', 'With the rapid increase in the availability of biological graph datasets, there is a growing need for effective and efficient graph querying methods. Due to the noisy and incomplete characteristics of these datasets, exact graph matching methods have limited use and approximate graph matching methods are required. Unfortunately, existing graph matching methods are too restrictive as they only allow exact or near exact graph matching. This paper presents a novel approximate graph matching technique called SAGA. This technique employs a flexible model for computing graph similarity, which allows for node gaps, node mismatches and graph structural differences. SAGA employs an indexing technique that allows it to efficiently evaluate queries even against large graph datasets.'),
(73143, 2007, 'bio', 'Tree and rate estimation by local evaluation of heterochronous nucleotide data', 'Yang, Zhu|OBrien, John D|Zheng, Xiaobin|Zhu, Huai-Qiu|She, Zhen-Su', 'State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.|State Key Lab for Turbulence and Complex Systems and Center for Theoretical Biology, Peking University, Beijing 100871, China.', 'China|China|China|China|China', 0, 'Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|Kinetics|Models, Genetic|Nucleotides|Phylogeny|Sequence Analysis, DNA|Time Factors', 'Journal Article', '10.1093/bioinformatics/btl577', '17110369', 'Heterochronous gene sequence data is important for characterizing the evolutionary processes of fast-evolving organisms such as RNA viruses. A limited set of algorithms exists for estimating the rate of nucleotide substitution and inferring phylogenetic trees from such data. The authors here present a new method, Tree and Rate Estimation by Local Evaluation (TREBLE) that robustly calculates the rate of nucleotide substitution and phylogeny with several orders of magnitude improvement in computational time.'),
(73144, 2007, 'bio', 'Indelign: a probabilistic framework for annotation of insertions and deletions in a multiple alignment', 'Kim, Jaebum|Sinha, Saurabh', 'Department of Computer Science, University of Illinois, Urbana-Champaign, Urbana, IL, USA.|Department of Computer Science, University of Illinois, Urbana-Champaign, Urbana, IL, USA.', 'United States|United States', 27, 'Algorithms|Base Sequence|Computer Simulation|DNA Mutational Analysis|DNA Transposable Elements|Data Interpretation, Statistical|Evolution, Molecular|Models, Genetic|Models, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Deletion|Software', 'Journal Article', '10.1093/bioinformatics/btl578', '17110370', 'A quantitative study of molecular evolutionary events such as substitutions, insertions and deletions from closely related genomes requires (1) an accurate multiple sequence alignment program and (2) a method to annotate the insertions and deletions that explain the gaps in the alignment. Although the former requirement has been extensively addressed, the latter problem has received little attention, especially in a comprehensive probabilistic framework.'),
(73145, 2007, 'bio', 'NvMap: automated analysis of NMR chemical shift perturbation data', 'Fukui, Lisa|Chen, Yuan', 'Division of Immunology, Beckman Research Institute of the City of Hope, 1450 East Duarte Road, Duarte, CA 91010, USA.|Division of Immunology, Beckman Research Institute of the City of Hope, 1450 East Duarte Road, Duarte, CA 91010, USA.', 'United States|United States', 7, 'Algorithms|Binding Sites|Biopolymers|Magnetic Resonance Spectroscopy|Protein Interaction Mapping|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl585', '17118956', 'NMR chemical shift perturbation experiments are widely used to define binding sites in biomolecular complexes. Especially in the case of high throughput screening of ligands, rapid analysis of NMR spectra is essential. NvMap extends NMRViewJ and provides a means for rapid assignments and book-keeping of NMR titration spectra. Our module offers options to analyze multiple titration spectra both separately and sequentially, where the sequential spectra are analyzed either two at a time or all simultaneously. The first option is suitable for slow or intermediate exchange rates between free and bound proteins. The latter option is particularly useful for fast exchange situations and can compensate for the lack of indicators for overlapped peaks. Our module also provides a simple user interface to automate the analysis process from dataset to peak list. We demonstrate the effectiveness of our program using NMR spectra of SUMO in complexes with three different peptides.'),
(73146, 2007, 'bio', 'A framework for gene expression analysis', 'Schreiber, Andreas W|Baumann, Ute', 'Australian Centre for Plant Functional Genomics, Hartley Grove, PMB 1 Waite Campus, The University of Adelaide Glen Osmond 5064, Australia. andreas.schreiber@adelaide.edu.au|Australian Centre for Plant Functional Genomics, Hartley Grove, PMB 1 Waite Campus, The University of Adelaide Glen Osmond 5064, Australia. andreas.schreiber@adelaide.edu.au', 'Australia|Australia', 0, 'Algorithms|Arabidopsis|Arabidopsis Proteins|Computer Simulation|Gene Expression|Gene Expression Profiling|Gene Expression Regulation, Plant|Models, Biological|Oligonucleotide Array Sequence Analysis|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btl591', '17118957', 'Global gene expression measurements as obtained, for example, in microarray experiments can provide important clues to the underlying transcriptional control mechanisms and network structure of a biological cell. In the absence of a detailed understanding of this gene regulation, current attempts at classification of expression data rely on clustering and pattern recognition techniques employing ad-hoc similarity criteria. To improve this situation, a better understanding of the expected relationships between expression profiles of genes associated by biological function is required.'),
(73147, 2007, 'bio', 'PartTree: an algorithm to build an approximate tree from a large number of unaligned sequences', 'Katoh, Kazutaka|Toh, Hiroyuki', 'Digital Medicine Initiative, Kyushu University, Fukuoka 812-8582, Japan. katoh@bioreg.kyushu-u.ac.jp|Digital Medicine Initiative, Kyushu University, Fukuoka 812-8582, Japan. katoh@bioreg.kyushu-u.ac.jp', 'Japan|Japan', 0, 'Algorithms|Conserved Sequence|Sequence Alignment|Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btl592', '17118958', 'To construct a multiple sequence alignment (MSA) of a large number (> approximately 10,000) of sequences, the calculation of a guide tree with a complexity of O(N2) to O(N3), where N is the number of sequences, is the most time-consuming process.'),
(73148, 2007, 'bio', 'WHAP: haplotype-based association analysis', 'Purcell, Shaun|Daly, Mark J|Sham, Pak C', 'Center for Human Genetic Research, MGH, Boston, MA, USA. shaun@pngu.mgh.harvard.edu|Center for Human Genetic Research, MGH, Boston, MA, USA. shaun@pngu.mgh.harvard.edu|Center for Human Genetic Research, MGH, Boston, MA, USA. shaun@pngu.mgh.harvard.edu', 'United States|United States|United States', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Genetic Markers|Genetic Variation|Genetics, Population|Haplotypes|Linkage Disequilibrium|Molecular Sequence Data|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Sequence Alignment|Sequence Analysis, DNA|Software|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btl580', '17118959', 'We describe a software tool to perform haplotype-based association analysis, for quantitative and qualitative traits, in population and family samples, using single nucleotide polymorphism or multiallelic marker data. A range of tests is offered: omnibus and haplotype-specific tests, prospective and retrospective likelihoods, covariates and moderators, sliding window analyses, permutation P-values. We focus on the ability to flexibly impose constraints on haplotype effects, which allows for a range of conditional haplotype-based likelihood ratio tests: for example, whether an allele has an effect independent of its haplotypic background, or whether a single variant can explain the overall association at a locus. We illustrate using these tests to dissect a multi-locus association.'),
(73149, 2007, 'bio', 'PrepMS: TOF MS data graphical preprocessing tool', 'Karpievitch, Yuliya V|Hill, Elizabeth G|Smolka, Adam J|Morris, Jeffrey S|Coombes, Kevin R|Baggerly, Keith A|Almeida, Jonas S', 'Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. ykarpi@mdanderson.org|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. ykarpi@mdanderson.org|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. ykarpi@mdanderson.org|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. ykarpi@mdanderson.org|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. ykarpi@mdanderson.org|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. ykarpi@mdanderson.org|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. ykarpi@mdanderson.org', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Mass Spectrometry|Peptide Mapping|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl583', '17121773', 'We introduce a simple-to-use graphical tool that enables researchers to easily prepare time-of-flight mass spectrometry data for analysis. For ease of use, the graphical executable provides default parameter settings, experimentally determined to work well in most situations. These values, if desired, can be changed by the user. PrepMS is a stand-alone application made freely available (open source), and is under the General Public License (GPL). Its graphical user interface, default parameter settings, and display plots allow PrepMS to be used effectively for data preprocessing, peak detection and visual data quality assessment.'),
(73150, 2007, 'bio', 'Qualitatively modelling and analysing genetic regulatory networks: a Petri net approach', 'Steggles, L Jason|Banks, Richard|Shaw, Oliver|Wipat, Anil', 'School of Computing Science, University of Newcastle, Newcastle upon Tyne, UK. L.J.Steggles@ncl.ac.uk|School of Computing Science, University of Newcastle, Newcastle upon Tyne, UK. L.J.Steggles@ncl.ac.uk|School of Computing Science, University of Newcastle, Newcastle upon Tyne, UK. L.J.Steggles@ncl.ac.uk|School of Computing Science, University of Newcastle, Newcastle upon Tyne, UK. L.J.Steggles@ncl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 88, 'Algorithms|Cell Physiological Phenomena|Gene Expression Profiling|Gene Expression Regulation|Logistic Models|Models, Biological|Neural Networks (Computer)|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btl596', '17121774', 'New developments in post-genomic technology now provide researchers with the data necessary to study regulatory processes in a holistic fashion at multiple levels of biological organization. One of the major challenges for the biologist is to integrate and interpret these vast data resources to gain a greater understanding of the structure and function of the molecular processes that mediate adaptive and cell cycle driven changes in gene expression. In order to achieve this biologists require new tools and techniques to allow pathway related data to be modelled and analysed as network structures, providing valuable insights which can then be validated and investigated in the laboratory.'),
(73151, 2007, 'bio', 'SNP2NMD: a database of human single nucleotide polymorphisms causing nonsense-mediated mRNA decay', 'Han, Areum|Kim, Woo-Yeon|Park, Seong-Min', 'Korean Bioinformation Center, KRIBB, Daejeon 305-806, Korea.|Korean Bioinformation Center, KRIBB, Daejeon 305-806, Korea.|Korean Bioinformation Center, KRIBB, Daejeon 305-806, Korea.', '-|-|-', 12, 'Chromosome Mapping|Codon, Nonsense|DNA Mutational Analysis|Database Management Systems|Databases, Genetic|Genome, Human|Humans|Information Storage and Retrieval|Internet|Polymorphism, Single Nucleotide|RNA Stability', 'Journal Article', '10.1093/bioinformatics/btl593', '17121775', 'Elucidating the effects of genetic polymorphisms on genes and gene networks is an important step in disease association studies. We developed the SNP2NMD database for human SNPs (single nucleotide polymorphisms) that result in PTCs (premature termination codons) and trigger nonsense-mediated mRNA decay (NMD). The SNP2NMD Web interfaces provide extensive genetic information on and graphical views of the queried SNP, gene, and disease terms.'),
(73152, 2007, 'bio', 'ProteomeCommonsorg IO Framework: reading and writing multiple proteomics data formats', 'Falkner, J A|Falkner, J W|Andrews, P C', 'Department of Biochemistry, Program in Bioinformatics, Ann Arbor, MI 48109, USA. jfalkner@umich.edu|Department of Biochemistry, Program in Bioinformatics, Ann Arbor, MI 48109, USA. jfalkner@umich.edu|Department of Biochemistry, Program in Bioinformatics, Ann Arbor, MI 48109, USA. jfalkner@umich.edu', 'United States|United States|United States', 0, 'Algorithms|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Mass Spectrometry|Peptide Mapping|Proteome|Proteomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl573', '17121776', 'Effective use of proteomics data, specifically mass spectrometry data, relies on the ability to read and write the many mass spectrometer file formats. Even with mass spectrometer vendor-specific libraries and vendor-neutral file formats, such as mzXML and mzData it can be difficult to extract raw data files in a form suitable for batch processing and basic research. Introduced here are the ProteomeCommons.org Input and Output Framework, abbreviated to IO Framework, which is designed to abstractly represent mass spectrometry data. This project is a public, open-source, free-to-use framework that supports most of the mass spectrometry data formats, including current formats, legacy formats and proprietary formats that require a vendor-specific library in order to operate. The IO Framework includes an on-line tool for non-programmers and a set of libraries that developers may use to convert between various proteomics file formats.'),
(73153, 2007, 'bio', 'ARIA2: automated NOE assignment and data integration in NMR structure calculation', 'Rieping, Wolfgang|Habeck, Michael|Bardiaux, Benjamin|Bernard, Aymeric|Malliavin, Thérèse E|Nilges, Michael', 'Unité de Bioinformatique structurale, CNRS URA 2185, Institut Pasteur, 25-28 rue du docteur Roux, 75015 Paris, France.|Unité de Bioinformatique structurale, CNRS URA 2185, Institut Pasteur, 25-28 rue du docteur Roux, 75015 Paris, France.|Unité de Bioinformatique structurale, CNRS URA 2185, Institut Pasteur, 25-28 rue du docteur Roux, 75015 Paris, France.|Unité de Bioinformatique structurale, CNRS URA 2185, Institut Pasteur, 25-28 rue du docteur Roux, 75015 Paris, France.|Unité de Bioinformatique structurale, CNRS URA 2185, Institut Pasteur, 25-28 rue du docteur Roux, 75015 Paris, France.|Unité de Bioinformatique structurale, CNRS URA 2185, Institut Pasteur, 25-28 rue du docteur Roux, 75015 Paris, France.', 'France|France|France|France|France|France', 353, 'Algorithms|Biopolymers|Computer Graphics|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Magnetic Resonance Spectroscopy|Molecular Conformation|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl589', '17121777', 'Modern structural genomics projects demand for integrated methods for the interpretation and storage of nuclear magnetic resonance (NMR) data. Here we present version 2.1 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and NMR structure calculation. We report on recent developments, most notably a graphical user interface, and the incorporation of the object-oriented data model of the Collaborative Computing Project for NMR (CCPN). The CCPN data model defines a storage model for NMR data, which greatly facilitates the transfer of data between different NMR software packages.'),
(73154, 2007, 'bio', 'QOMA: quasi-optimal multiple alignment of protein sequences', 'Zhang, Xu|Kahveci, Tamer', 'Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA.|Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA.', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btl590', '17121778', 'We consider the problem of multiple alignment of protein sequences with the goal of achieving a large SP (Sum-of-Pairs) score.'),
(73155, 2007, 'bio', 'A predictive model for identifying proteins by a single peptide match', 'Higdon, Roger|Kolker, Eugene', 'The BIATECH Institute, Bothell, WA 98011, USA.|The BIATECH Institute, Bothell, WA 98011, USA.', 'United States|United States', 43, 'Algorithms|Amino Acid Sequence|Computer Simulation|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Logistic Models|Mass Spectrometry|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Peptide Mapping|Proteins|Regression Analysis|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btl595', '17121779', 'Tandem mass-spectrometry of trypsin digests, followed by database searching, is one of the most popular approaches in high-throughput proteomics studies. Peptides are considered identified if they pass certain scoring thresholds. To avoid false positive protein identification, > or = 2 unique peptides identified within a single protein are generally recommended. Still, in a typical high-throughput experiment, hundreds of proteins are identified only by a single peptide. We introduce here a method for distinguishing between true and false identifications among single-hit proteins. The approach is based on randomized database searching and usage of logistic regression models with cross-validation. This approach is implemented to analyze three bacterial samples enabling recovery 68-98% of the correct single-hit proteins with an error rate of < 2%. This results in a 22-65% increase in number of identified proteins. Identifying true single-hit proteins will lead to discovering many crucial regulators, biomarkers and other low abundance proteins.'),
(73156, 2007, 'bio', 'Extensions to gene set enrichment', 'Jiang, Zhen|Gentleman, Robert', 'Computational Biology, 1100 Fairview Avenue. N. M2-B876, PO Box 19024, Seattle, WA 98109-1024, USA. zjiang@fhcrc.org|Computational Biology, 1100 Fairview Avenue. N. M2-B876, PO Box 19024, Seattle, WA 98109-1024, USA. zjiang@fhcrc.org', 'United States|United States', 156, 'Algorithms|Cell Physiological Phenomena|Gene Expression|Gene Expression Profiling|Gene Expression Regulation|Oligonucleotide Array Sequence Analysis|Proteome', 'Journal Article', '10.1093/bioinformatics/btl599', '17127676', 'Gene Set Enrichment Analysis (GSEA) has been developed recently to capture changes in the expression of pre-defined sets of genes. We propose number of extensions to GSEA, including the use of different statistics to describe the association between genes and phenotypes of interest. We make use of dimension reduction procedures, such as principle component analysis, to identify gene sets with correlated expression. We also address issues that arise when gene sets overlap.'),
(73157, 2007, 'bio', 'Mosclust: a software library for discovering significant structures in bio-molecular data', 'Valentini, Giorgio', 'DSI, Dipartimento di Scienze dellInformazione, Università degli Studi di Milano, Via Comelico 39, Italy. valentini@dsi.unimi.it', 'Italy', 3, 'Algorithms|Artificial Intelligence|Cluster Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Programming Languages|Proteome|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btl600', '17127677', 'The R package mosclust (model order selection for clustering problems) implements algorithms based on the concept of stability for discovering significant structures in bio-molecular data. The software library provides stability indices obtained through different data perturbations methods (resampling, random projections, noise injection), as well as statistical tests to assess the significance of multi-level structures singled out from the data.'),
(73158, 2007, 'bio', 'GOlorize: a Cytoscape plug-in for network visualization with Gene Ontology-based layout and coloring', 'Garcia, Olivier|Saveanu, Cosmin|Cline, Melissa|Fromont-Racine, Micheline|Jacquier, Alain|Schwikowski, Benno|Aittokallio, Tero', 'Systems Biology Unit, Institut Pasteur, 75724 Paris Cedex 15, France.|Systems Biology Unit, Institut Pasteur, 75724 Paris Cedex 15, France.|Systems Biology Unit, Institut Pasteur, 75724 Paris Cedex 15, France.|Systems Biology Unit, Institut Pasteur, 75724 Paris Cedex 15, France.|Systems Biology Unit, Institut Pasteur, 75724 Paris Cedex 15, France.|Systems Biology Unit, Institut Pasteur, 75724 Paris Cedex 15, France.|Systems Biology Unit, Institut Pasteur, 75724 Paris Cedex 15, France.', 'France|France|France|France|France|France|France', 0, 'Algorithms|Color|Computer Graphics|Computer Simulation|Databases, Protein|Information Storage and Retrieval|Models, Biological|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl605', '17127678', 'We have implemented a graph layout algorithm that exposes Gene Ontology (GO) class structure on the network nodes. It can be used in conjunction with BiNGO plug-in to Cytoscape, which finds the GO categories over-represented in a given network. Our plug-in, named GOlorize, first highlights the class members with category-specific color-coding and then constructs an enhanced visualization of the network using a class-directed layout algorithm.'),
(73159, 2007, 'bio', 'QSCOP--SCOP quantified by structural relationships', 'Suhrer, Stefan J|Wiederstein, Markus|Sippl, Manfred J', 'Center of Applied Molecular Engineering, Department of Bioinformatics, Division of Molecular Biology, University of Salzburg, 5020 Salzburg, Austria.|Center of Applied Molecular Engineering, Department of Bioinformatics, Division of Molecular Biology, University of Salzburg, 5020 Salzburg, Austria.|Center of Applied Molecular Engineering, Department of Bioinformatics, Division of Molecular Biology, University of Salzburg, 5020 Salzburg, Austria.', 'Austria|Austria|Austria', 15, 'Computer Simulation|Databases, Protein|Models, Chemical|Models, Molecular|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btl594', '17127679', 'The database SCOP (Structural Classification Of Proteins) has become a major resource in bioinformatics and protein science. A particular strength of SCOP is the flexibility of its rules enabling the preservation of the many details spotted by experts in the classification process. Here we endow classic SCOP Families with quantified structural information and comment on the structural diversity found in the SCOP hierarchy.'),
(73160, 2007, 'bio', 'Mclip: motif detection based on cliques of gapped local profile-to-profile alignments', 'Frickey, Tancred|Weiller, Georg', 'ARC Centre of Excellence for Integrative Legume Research and Bioinformatics Laboratory, Genomic Interactions Group, Research School of Biological Sciences, Australian National University, GPO Box 475, Canberra, ACT 2601, Australia.|ARC Centre of Excellence for Integrative Legume Research and Bioinformatics Laboratory, Genomic Interactions Group, Research School of Biological Sciences, Australian National University, GPO Box 475, Canberra, ACT 2601, Australia.', 'Australia|Australia', 6, 'Algorithms|Base Sequence|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btl601', '17127680', 'A multitude of motif-finding tools have been published, which can generally be assigned to one of three classes: expectation-maximization, Gibbs-sampling or enumeration. Irrespective of this grouping, most motif detection tools only take into account similarities across ungapped sequence regions, possibly causing short motifs located peripherally and in varying distance to a core motif to be missed. We present a new method, adding to the set of expectation-maximization approaches, that permits the use of gapped alignments for motif elucidation.'),
(73161, 2007, 'bio', 'Integrating transcription factor binding site information with gene expression datasets', 'Jeffery, Ian B|Madden, Stephen F|McGettigan, Paul A|Perrière, Guy|Culhane, Aedín C|Higgins, Desmond G', 'UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Ian.Jeffery@ucd.ie|UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Ian.Jeffery@ucd.ie|UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Ian.Jeffery@ucd.ie|UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Ian.Jeffery@ucd.ie|UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Ian.Jeffery@ucd.ie|UCD Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Ian.Jeffery@ucd.ie', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 0, 'Algorithms|Binding Sites|Biomarkers, Tumor|DNA, Neoplasm|Databases, Protein|Gene Expression Profiling|Genetic Testing|Humans|Male|Neoplasm Proteins|Prostatic Neoplasms|Protein Binding|Systems Integration|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btl597', '17127681', 'Microarrays are widely used to measure gene expression differences between sets of biological samples. Many of these differences will be due to differences in the activities of transcription factors. In principle, these differences can be detected by associating motifs in promoters with differences in gene expression levels between the groups. In practice, this is hard to do.'),
(73162, 2007, 'bio', 'Improved breast cancer prognosis through the combination of clinical and genetic markers', 'Sun, Yijun|Goodison, Steve|Li, Jian|Liu, Li|Farmerie, William', 'Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL 32611, USA.|Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL 32611, USA.|Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL 32611, USA.|Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL 32611, USA.|Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL 32611, USA.', 'United States|United States|United States|United States|United States', 109, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Computational Biology|Female|Genetic Markers|Humans|Models, Biological|Neoplasm Metastasis|Neoplasm Recurrence, Local|Odds Ratio|Oligonucleotide Array Sequence Analysis|Predictive Value of Tests|Prognosis|ROC Curve|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btl543', '17130137', 'Accurate prognosis of breast cancer can spare a significant number of breast cancer patients from receiving unnecessary adjuvant systemic treatment and its related expensive medical costs. Recent studies have demonstrated the potential value of gene expression signatures in assessing the risk of post-surgical disease recurrence. However, these studies all attempt to develop genetic marker-based prognostic systems to replace the existing clinical criteria, while ignoring the rich information contained in established clinical markers. Given the complexity of breast cancer prognosis, a more practical strategy would be to utilize both clinical and genetic marker information that may be complementary.'),
(73163, 2007, 'bio', 'K-Fold: a tool for the prediction of the protein folding kinetic order and rate', 'Capriotti, E|Casadio, R', 'Biocomputing Group, CIRB/Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. emidio@biocomp.unibo.it|Biocomputing Group, CIRB/Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. emidio@biocomp.unibo.it', 'Italy|Italy', 51, 'Algorithms|Computer Graphics|Computer Simulation|Kinetics|Models, Chemical|Models, Molecular|Protein Conformation|Protein Folding|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl610', '17138584', 'K-Fold is a tool for the automatic prediction of the protein folding kinetic order and rate. The tool is based on a support vector machine (SVM) that was trained on a data set of 63 proteins, whose 3D structure and folding mechanism are known from experiments already described in the literature. The method predicts whether a protein of known atomic structure folds according to a two-state or a multi-state kinetics and correctly classifies 81% of the folding mechanisms when tested over the training set of the 63 proteins. It also predicts as a further option the logarithm of the folding rate. To the best of our knowledge, the tool discriminates for the first time whether a protein is characterized by a two state or a multiple state kinetics, during the folding process, and concomitantly estimates also the value of the constant rate of the process. When used to predict the logarithm of the folding rate, K-Fold scores with a correlation value to the experimental data of 0.74 (with a SE of 1.2).'),
(73164, 2007, 'bio', 'BioNetBuilder: automatic integration of biological networks', 'Avila-Campillo, Iliana|Drew, Kevin|Lin, John|Reiss, David J|Bonneau, Richard', 'Department of Biology, New York University, New York, NY, USA. iliana_avila-campillo@merck.com|Department of Biology, New York University, New York, NY, USA. iliana_avila-campillo@merck.com|Department of Biology, New York University, New York, NY, USA. iliana_avila-campillo@merck.com|Department of Biology, New York University, New York, NY, USA. iliana_avila-campillo@merck.com|Department of Biology, New York University, New York, NY, USA. iliana_avila-campillo@merck.com', 'United States|United States|United States|United States|United States', 49, 'Algorithms|Computer Graphics|Computer Simulation|Database Management Systems|Information Storage and Retrieval|Internet|Models, Biological|Proteome|Signal Transduction|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl604', '17138585', 'BioNetBuilder is an open-source client-server Cytoscape plugin that offers a user-friendly interface to create biological networks integrated from several databases. Users can create networks for approximately 1500 organisms, including common model organisms and human. Currently supported databases include: DIP, BIND, Prolinks, KEGG, HPRD, The BioGrid and GO, among others. The BioNetBuilder plugin client is available as a Java Webstart, providing a platform-independent network interface to these public databases.'),
(73165, 2007, 'bio', 'Flexible empirical Bayes models for differential gene expression', 'Lo, Kenneth|Gottardo, Raphael', 'Department of Statistics, University of British Columbia, 333-6356 Agricultural Road, Vancouver, BC, Canada V6T 1Z2. c.lo@stat.ubc.ca|Department of Statistics, University of British Columbia, 333-6356 Agricultural Road, Vancouver, BC, Canada V6T 1Z2. c.lo@stat.ubc.ca', 'Canada|Canada', 38, 'Algorithms|Bayes Theorem|Data Interpretation, Statistical|Gene Expression Profiling|Logistic Models|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btl612', '17138586', 'Inference about differential expression is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increasingly popular for this type of problem. The two most common hierarchical models are the hierarchical Gamma-Gamma (GG) and Lognormal-Normal (LNN) models. However, to facilitate inference, some unrealistic assumptions have been made. One such assumption is that of a common coefficient of variation across genes, which can adversely affect the resulting inference.'),
(73166, 2007, 'bio', 'Prophet, a web-based tool for class prediction using microarray data', 'Medina, Ignacio|Montaner, David|Tárraga, Joaquín|Dopazo, Joaquín', 'Department of Bioinformatics, Centro de Investigación Príncipe Felipe, Valencia, E46013, Spain.|Department of Bioinformatics, Centro de Investigación Príncipe Felipe, Valencia, E46013, Spain.|Department of Bioinformatics, Centro de Investigación Príncipe Felipe, Valencia, E46013, Spain.|Department of Bioinformatics, Centro de Investigación Príncipe Felipe, Valencia, E46013, Spain.', 'Spain|Spain|Spain|Spain', 26, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Internet|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteins|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btl602', '17138587', 'Sample classification and class prediction is the aim of many gene expression studies. We present a web-based application, Prophet, which builds prediction rules and allows using them for further sample classification. Prophet automatically chooses the best classifier, along with the optimal selection of genes, using a strategy that renders unbiased cross-validated errors. Prophet is linked to different microarray data analysis modules, and includes a unique feature: the possibility of performing the functional interpretation of the molecular signature found.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73167, 2007, 'bio', 'Crystallographic protein model-building on the web', 'Gopal, Kreshna|McKee, Erik|Romo, Tod|Pai, Reetal|Smith, Jacob|Sacchettini, James|Ioerger, Thomas', 'Department of Computer Science, Texas A&M University, 301 H.R. Bright Building, College Station, TX 77843-3112, USA. textal@tamu.edu|Department of Computer Science, Texas A&M University, 301 H.R. Bright Building, College Station, TX 77843-3112, USA. textal@tamu.edu|Department of Computer Science, Texas A&M University, 301 H.R. Bright Building, College Station, TX 77843-3112, USA. textal@tamu.edu|Department of Computer Science, Texas A&M University, 301 H.R. Bright Building, College Station, TX 77843-3112, USA. textal@tamu.edu|Department of Computer Science, Texas A&M University, 301 H.R. Bright Building, College Station, TX 77843-3112, USA. textal@tamu.edu|Department of Computer Science, Texas A&M University, 301 H.R. Bright Building, College Station, TX 77843-3112, USA. textal@tamu.edu|Department of Computer Science, Texas A&M University, 301 H.R. Bright Building, College Station, TX 77843-3112, USA. textal@tamu.edu', 'United States|United States|United States|United States|United States|United States|United States', 3, 'Algorithms|Computer Simulation|Crystallography|Internet|Models, Chemical|Models, Molecular|Protein Conformation|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btl584', '17138588', 'X-ray crystallography is the most widely used method to determine the 3D structure of protein molecules. One of the most difficult steps in protein crystallography is model-building, which consists of constructing a backbone and then amino acid side chains into an electron density map. Interpretation of electron density maps represents a major bottleneck in protein structure determination pipelines, and thus, automated techniques to interpret maps can greatly improve the throughput. We have developed WebTex, a simple and yet powerful web interface to TEXTAL, a program that automates this process of fitting atoms into electron density maps. TEXTAL can also be downloaded for local installation.'),
(73168, 2007, 'bio', 'Visualization of genomic aberrations using Affymetrix SNP arrays', 'Müller, André|Holzmann, Karlheinz|Kestler, Hans A', 'Internal Medicine I, University of Ulm, D-89069 Ulm, Germany.|Internal Medicine I, University of Ulm, D-89069 Ulm, Germany.|Internal Medicine I, University of Ulm, D-89069 Ulm, Germany.', 'Germany|Germany|Germany', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Graphics|DNA Mutational Analysis|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Molecular Sequence Data|Mutation|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sequence Alignment|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl608', '17138589', 'DNA copy number aberrations are frequently found in different types of cancer. Recent developments of microarray-based approaches have broadened the knowledge on number and structure of such aberrations. High-density single nucleotide polymorphism (SNP) microarrays provide an extremely high resolution with up to 500,000 SNPs per genome. Owing to the enormous amount of data the detection of common aberrations in large datasets is a great challenge. We describe a novel open source software tool--IdeogramBrowser--which was specifically designed for use with the Affymetrix SNP arrays. It provides an interactive karyotypic visualization of multiple aberration profiles and direct links to GeneCards. Visualization of consensus regions together with gene representation allows the explorative assessment of the data.'),
(73169, 2007, 'bio', 'MotifScorer: using a compendium of microarrays to identify regulatory motifs', 'Brilli, Matteo|Fani, Renato|Lió, Pietro', 'Dipartimento di Biologia Animale e Genetica, via Romana 17, 50125 Firenze, Italy.|Dipartimento di Biologia Animale e Genetica, via Romana 17, 50125 Firenze, Italy.|Dipartimento di Biologia Animale e Genetica, via Romana 17, 50125 Firenze, Italy.', 'Italy|Italy|Italy', 5, 'Algorithms|Chromosome Mapping|Databases, Genetic|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Regulatory Sequences, Nucleic Acid|Sequence Analysis|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btl607', '17138590', 'We describe MotifScorer, a program for systematic genome-wide identification of transcription sites. The program uses a compendium of gene expression microarrays and implements state-of-art partial least squares (PLSs) based regression and stepwise regression procedures. Candidate motifs from the upstream sequences of groups of co-regulated genes are identified and assigned a score using genomic background models and available motif finding tools. The use of a large library of expression data allows statistical comparative analysis of the specificity of motifs identified in different conditions.'),
(73170, 2007, 'bio', 'RelEx--relation extraction using dependency parse trees', 'Fundel, Katrin|Küffner, Robert|Zimmer, Ralf', 'Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. katrin.fundel@bio.ifi.lmu.de|Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. katrin.fundel@bio.ifi.lmu.de|Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. katrin.fundel@bio.ifi.lmu.de', 'Germany|Germany|Germany', 321, 'Algorithms|Database Management Systems|Gene Expression|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Protein Interaction Mapping|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btl616', '17142812', 'The discovery of regulatory pathways, signal cascades, metabolic processes or disease models requires knowledge on individual relations like e.g. physical or regulatory interactions between genes and proteins. Most interactions mentioned in the free text of biomedical publications are not yet contained in structured databases.'),
(73171, 2007, 'bio', 'Exploiting large scale computing to construct high resolution linkage disequilibrium maps of the human genome', 'Lau, Winston|Kuo, Tai-Yue|Tapper, William|Cox, Simon|Collins, Andrew', 'Human Genetics Division, Duthie Building (Mailpoint 808), Southampton General Hospital, Tremona Road, Southampton SO16 6YD, UK.|Human Genetics Division, Duthie Building (Mailpoint 808), Southampton General Hospital, Tremona Road, Southampton SO16 6YD, UK.|Human Genetics Division, Duthie Building (Mailpoint 808), Southampton General Hospital, Tremona Road, Southampton SO16 6YD, UK.|Human Genetics Division, Duthie Building (Mailpoint 808), Southampton General Hospital, Tremona Road, Southampton SO16 6YD, UK.|Human Genetics Division, Duthie Building (Mailpoint 808), Southampton General Hospital, Tremona Road, Southampton SO16 6YD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 14, 'Algorithms|Chromosome Mapping|Cluster Analysis|Computing Methodologies|Genetic Markers|Genetics, Population|Genome, Human|Humans|Linkage Disequilibrium|Sensitivity and Specificity|Software', 'Journal Article', '10.1093/bioinformatics/btl615', '17142813', 'Linkage disequilibrium (LD) maps increase power and precision in association mapping, define optimal marker spacing and identify recombination hot-spots and regions influenced by natural selection. Phase II of HapMap provides approximately 2.8-fold more single nucleotide polymorphisms (SNPs) than phase I for constructing higher resolution maps. LDMAP-cluster, is a parallel program for rapid map construction in a Linux environment used here to construct genome-wide LD maps with >8.2 million SNPs from the phase II data.'),
(73172, 2007, 'bio', 'The automation of Nested Clade Phylogeographic Analysis', 'Panchal, Mahesh', 'School of Biological Sciences, University of Reading, Whiteknights, PO Box 228, Reading RG6 6AJ, UK. m.panchal@rdg.ac.uk', 'United Kingdom', 120, 'Algorithms|Base Sequence|Demography|Evolution, Molecular|Genetics, Population|Molecular Sequence Data|Phylogeny|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btl614', '17142814', 'ANeCA is a fully automated implementation of Nested Clade Phylogeographic Analysis. This was originally developed by Templeton and colleagues, and has been used to infer, from the pattern of gene sequence polymorphisms in a geographically structured population, the historical demographic processes that have shaped its evolution. Until now it has been necessary to perform large parts of the procedure manually. We provide a program that will take data in Nexus sequential format, and directly output a set of inferences. The software also includes TCS v1.18 and GeoDis v2.2 as part of automation.'),
(73173, 2007, 'bio', 'Dynamic exploration and editing of KEGG pathway diagrams', 'Klukas, Christian|Schreiber, Falk', 'Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany.|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany.', 'Germany|Germany', 0, 'Algorithms|Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Genetic|Documentation|Information Storage and Retrieval|Models, Biological|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl611', '17142815', 'The Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway database is a very valuable information resource for researchers in the fields of life sciences. It contains metabolic and regulatory processes in the form of wiring diagrams, which can be used for browsing and information retrieval as well as a base for modeling and simulation. Thus it helps in understanding biological processes and higher-order functions of biological systems. Currently the KEGG website uses semi-static visualizations for the presentation and navigation of its pathway information. While this visualization style offers a good pathway presentation and navigation, it does not provide some of the possibilities related to dynamic visualizations, most importantly, the creation and visualization of user-specific pathways.'),
(73174, 2006, 'bio', 'Bioinformatics in the human interactome project', 'Ideker, Trey|Valencia, Alfonso', 'Department of Bioengineering, University of California San Diego (UCSD), USA.|Department of Bioengineering, University of California San Diego (UCSD), USA.', 'United States|United States', 10, 'Computational Biology|Human Genome Project|Humans|Protein Interaction Mapping|Proteome', 'Journal Article', '10.1093/bioinformatics/btl579', '17142816', '-'),
(73175, 2007, 'bio', 'cBrother: relaxing parental tree assumptions for Bayesian recombination detection', 'Fang, Fang|Ding, Jing|Minin, Vladimir N|Suchard, Marc A|Dorman, Karin S', 'Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA 50011, USA.', 'United States|United States|United States|United States|United States', 11, 'Algorithms|Amino Acid Sequence|Bayes Theorem|Computer Simulation|Evolution, Molecular|Models, Genetic|Molecular Sequence Data|Recombination, Genetic|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btl613', '17145740', 'Bayesian multiple change-point models accurately detect recombination in molecular sequence data. Previous Java-based implementations assume a fixed topology for the representative parental data. cBrother is a novel C language implementation that capitalizes on reduced computational time to relax the fixed tree assumption. We show that cBrother is 19 times faster than its predecessor and the fixed tree assumption can influence estimates of recombination in a medically-relevant dataset.'),
(73176, 2007, 'bio', 'AutoGRAPH: an interactive web server for automating and visualizing comparative genome maps', 'Derrien, Thomas|André, Catherine|Galibert, Francis|Hitte, Christophe', 'CNRS UMR6061 Génétique et Développement, Université de Rennes1, IFR140, 2 Av du Pr. Léon Bernard, CS 34317, 35043, France.|CNRS UMR6061 Génétique et Développement, Université de Rennes1, IFR140, 2 Av du Pr. Léon Bernard, CS 34317, 35043, France.|CNRS UMR6061 Génétique et Développement, Université de Rennes1, IFR140, 2 Av du Pr. Léon Bernard, CS 34317, 35043, France.|CNRS UMR6061 Génétique et Développement, Université de Rennes1, IFR140, 2 Av du Pr. Léon Bernard, CS 34317, 35043, France.', 'France|France|France|France', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl618', '17145741', 'AutoGRAPH is an interactive web server for automatic multi-species comparative genomics analyses based on personal datasets or pre-inserted public datasets. This program automatically identifies conserved segments (CS) and breakpoint regions, assesses the conservation of marker/gene order between organisms, constructs synteny maps for two to three species and generates high-quality, interactive displays facilitating the identification of chromosomal rearrangements. AutoGRAPH can also be used for the integration and comparison of several types of genomic resources (meiotic maps, radiation hybrid maps and genome sequences) for a single species, making AutoGRAPH a versatile tool for comparative genomics analysis.'),
(73177, 2007, 'bio', 'A distribution free summarization method for Affymetrix GeneChip arrays', 'Chen, Zhongxue|McGee, Monnie|Liu, Qingzhong|Scheuermann, Richard H', 'Department of Statistical Science, Southern Methodist University, Dallas, TX 75275, USA.|Department of Statistical Science, Southern Methodist University, Dallas, TX 75275, USA.|Department of Statistical Science, Southern Methodist University, Dallas, TX 75275, USA.|Department of Statistical Science, Southern Methodist University, Dallas, TX 75275, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Statistical Distributions', 'Journal Article', '10.1093/bioinformatics/btl609', '17148508', 'Affymetrix GeneChip arrays require summarization in order to combine the probe-level intensities into one value representing the expression level of a gene. However, probe intensity measurements are expected to be affected by different levels of non-specific- and cross-hybridization to non-specific transcripts. Here, we present a new summarization technique, the Distribution Free Weighted method (DFW), which uses information about the variability in probe behavior to estimate the extent of non-specific and cross-hybridization for each probe. The contribution of the probe is weighted accordingly during summarization, without making any distributional assumptions for the probe-level data.'),
(73178, 2007, 'bio', 'In silico identification of putative metal binding motifs', 'Thilakaraj, Richard|Raghunathan, Krishnan|Anishetty, Sharmila|Pennathur, Gautam', 'Centre for Biotechnology, Anna University, Chennai, 600 025, India.|Centre for Biotechnology, Anna University, Chennai, 600 025, India.|Centre for Biotechnology, Anna University, Chennai, 600 025, India.|Centre for Biotechnology, Anna University, Chennai, 600 025, India.', 'India|India|India|India', 0, 'Amino Acid Motifs|Amino Acid Sequence|Bacterial Proteins|Binding Sites|Databases, Protein|Metalloproteins|Metals|Molecular Sequence Data|Protein Binding|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btl617', '17148509', 'Metal ion binding domains are found in proteins that mediate transport, buffering or detoxification of metal ions. In this study, we have performed an in silico analysis of metal binding proteins and have identified putative metal binding motifs for the ions of cadmium, cobalt, zinc, arsenic, mercury, magnesium, manganese, molybdenum and nickel. A pattern search against the UniProtKB/Swiss-Prot and UniProtKB/TrEMBL databases yielded true positives in each case showing the high-specificity of the motifs. Motifs were also validated against PDB structures and site directed mutagenesis studies.'),
(73179, 2007, 'bio', 'LdCompare: rapid computation of single- and multiple-marker r2 and genetic coverage', 'Hao, K|Di, X|Cawley, S', 'Algorithm and Data Analysis, Affymetrix Inc. 3420 Central Expressway, Santa Clara, California, USA. ke_hao@affymetrix.com|Algorithm and Data Analysis, Affymetrix Inc. 3420 Central Expressway, Santa Clara, California, USA. ke_hao@affymetrix.com|Algorithm and Data Analysis, Affymetrix Inc. 3420 Central Expressway, Santa Clara, California, USA. ke_hao@affymetrix.com', 'United States|United States|United States', 24, 'Algorithms|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Genetic Markers|Genetic Variation|Linkage Disequilibrium|Molecular Sequence Data|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btl574', '17148510', 'The scale of genetic-variation datasets has increased enormously and the linkage equilibrium (LD) structure of these polymorphisms, particularly in whole-genome association studies, is of great interest. The significant computational complexity of calculating single- and multiple-marker correlations at a genome-wide scale remains challenging. We have developed a program that efficiently characterizes whole-genome LD structure on large number of SNPs in terms of single- and multiple-marker correlations.'),
(73180, 2007, 'bio', 'Genomic sweeping for hypermethylated genes', 'Goh, Liang|Murphy, Susan K|Muhkerjee, Sayan|Furey, Terrence S', 'Institute for Genome Sciences Policy, Duke University, USA.|Institute for Genome Sciences Policy, Duke University, USA.|Institute for Genome Sciences Policy, Duke University, USA.|Institute for Genome Sciences Policy, Duke University, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|Biomarkers, Tumor|Chromosome Mapping|CpG Islands|DNA Methylation|DNA, Neoplasm|Female|Genetic Testing|Humans|Molecular Sequence Data|Ovarian Neoplasms|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btl620', '17148511', 'Genes silenced by the aberrent methylation of nearby CpG islands can contribute to the onset or progression of cancer and represent potential biomarkers for diagnosis and prognosis. Relatively few have thus far been validated as hypermethylated in cancer among over 14,000 candidates with promoter region CpG islands. A descriptive set of genes known to be unmethylated in cancer does not exist. This lack of a negative set and a large number of candidates necessitated the development of a new approach to identify novel genes hypermethylated in cancer.'),
(73181, 2007, 'bio', 'ADP_EM: fast exhaustive multi-resolution docking for high-throughput coverage', 'Garzón, José Ignacio|Kovacs, Julio|Abagyan, Ruben|Chacón, Pablo', 'Centro de Investigaciones Biológicas, CSIC Ramiro de Maeztu 9, 28040 Madrid, Spain.|Centro de Investigaciones Biológicas, CSIC Ramiro de Maeztu 9, 28040 Madrid, Spain.|Centro de Investigaciones Biológicas, CSIC Ramiro de Maeztu 9, 28040 Madrid, Spain.|Centro de Investigaciones Biológicas, CSIC Ramiro de Maeztu 9, 28040 Madrid, Spain.', 'Spain|Spain|Spain|Spain', 76, 'Algorithms|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btl625', '17150992', 'Efficient fitting tools are needed to take advantage of a fast growth of atomic models of protein domains from crystallography or comparative modeling, and low-resolution density maps of larger molecular assemblies. Here, we report a novel fitting algorithm for the exhaustive and fast overlay of partial high-resolution models into a low-resolution density map. The method incorporates a fast rotational search based on spherical harmonics (SH) combined with a simple translational scanning.'),
(73182, 2007, 'bio', 'Protein solubility: sequence based prediction and experimental verification', 'Smialowski, Pawel|Martin-Galiano, Antonio J|Mikolajka, Aleksandra|Girschick, Tobias|Holak, Tad A|Frishman, Dmitrij', 'Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Models, Chemical|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Solubility|Solvents', 'Journal Article', '10.1093/bioinformatics/btl623', '17150993', 'Obtaining soluble proteins in sufficient concentrations is a recurring limiting factor in various experimental studies. Solubility is an individual trait of proteins which, under a given set of experimental conditions, is determined by their amino acid sequence. Accurate theoretical prediction of solubility from sequence is instrumental for setting priorities on targets in large-scale proteomics projects.'),
(73183, 2007, 'bio', 'Markers improve clustering of CGH data', 'Liu, Jun|Ranka, Sanjay|Kahveci, Tamer', 'Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA. juliu@cise.ufl.edu|Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA. juliu@cise.ufl.edu|Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA. juliu@cise.ufl.edu', 'United States|United States|United States', 0, 'Biomarkers, Tumor|Chromosome Mapping|Cluster Analysis|Gene Expression Profiling|Genetic Markers|Humans|In Situ Hybridization|Multigene Family|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btl624', '17150994', 'We consider the problem of clustering a population of Comparative Genomic Hybridization (CGH) data samples using similarity based clustering methods. A key requirement for clustering is to avoid using the noisy aberrations in the CGH samples.'),
(73184, 2007, 'bio', 'msHOT: modifying Hudsons ms simulator to incorporate crossover and gene conversion hotspots', 'Hellenthal, Garrett|Stephens, Matthew', 'Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. hellenth@stats.ox.ac.uk|Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. hellenth@stats.ox.ac.uk', 'United Kingdom|United Kingdom', 64, 'Algorithms|Chromosome Mapping|Crossing Over, Genetic|Gene Conversion|Genetic Variation|Genetics, Population|Models, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btl622', '17150995', 'We have incorporated both crossover and gene conversion hotspots into an existing coalescent-based program for simulating genetic variation data for a sample of chromosomes from a population.'),
(73185, 2007, 'bio', 'AllerTool: a web server for predicting allergenicity and allergic cross-reactivity in proteins', 'Zhang, Zong Hong|Koh, Judice L Y|Zhang, Guang Lan|Choo, Khar Heng|Tammi, Martti T|Tong, Joo Chuan', 'Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhzhang@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhzhang@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhzhang@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhzhang@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhzhang@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhzhang@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 4, 'Algorithms|Allergens|Amino Acid Sequence|Cross Reactions|Databases, Protein|Molecular Sequence Data|Proteins|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl621', '17150996', 'Assessment of potential allergenicity and patterns of cross-reactivity is necessary whenever novel proteins are introduced into human food chain. Current bioinformatic methods in allergology focus mainly on the prediction of allergenic proteins, with no information on cross-reactivity patterns among known allergens. In this study, we present AllerTool, a web server with essential tools for the assessment of predicted as well as published cross-reactivity patterns of allergens. The analysis tools include graphical representation of allergen cross-reactivity information, a local sequence comparison tool that displays information of known cross-reactive allergens, a sequence similarity search tool for assessment of cross-reactivity in accordance to FAO/WHO Codex alimentarius guidelines, and a method based on support vector machine (SVM). A 10-fold cross-validation results showed that the area under the receiver operating curve (A(ROC)) of SVM models is 0.90 with 86.00% sensitivity (SE) at specificity (SP) of 86.00%.'),
(73186, 2007, 'bio', 'Bayesian-based selection of metabolic objective functions', 'Knorr, Andrea L|Jain, Rishi|Srivastava, Ranjan', 'Department of Chemical, Materials and Biomolecular Engineering, University of Connecticut, 191 Auditorium Road U3222, Storrs, CT 06269-3222, USA.|Department of Chemical, Materials and Biomolecular Engineering, University of Connecticut, 191 Auditorium Road U3222, Storrs, CT 06269-3222, USA.|Department of Chemical, Materials and Biomolecular Engineering, University of Connecticut, 191 Auditorium Road U3222, Storrs, CT 06269-3222, USA.', 'United States|United States|United States', 63, 'Algorithms|Bayes Theorem|Cell Proliferation|Computer Simulation|Discriminant Analysis|Energy Metabolism|Escherichia coli|Escherichia coli Proteins|Models, Biological|Signal Transduction|Succinic Acid', 'Journal Article', '10.1093/bioinformatics/btl619', '17150997', 'A critical component of in silico analysis of underdetermined metabolic systems is the identification of the appropriate objective function. A common assumption is that the objective of the cell is to maximize growth. This objective function has been shown to be consistent in a few limited experimental cases, but may not be universally appropriate. Here a method is presented to quantitatively determine the most probable objective function.'),
(73187, 2007, 'bio', 'GGtools: analysis of genetics of gene expression in bioconductor', 'Carey, Vincent J|Morgan, Martin|Falcon, Seth|Lazarus, Ross|Gentleman, Robert', 'Channing Laboratory, Brigham and Womens Hospital, 75 Francis Street, Boston 02115, USA. stvjc@channing.harvard.edu|Channing Laboratory, Brigham and Womens Hospital, 75 Francis Street, Boston 02115, USA. stvjc@channing.harvard.edu|Channing Laboratory, Brigham and Womens Hospital, 75 Francis Street, Boston 02115, USA. stvjc@channing.harvard.edu|Channing Laboratory, Brigham and Womens Hospital, 75 Francis Street, Boston 02115, USA. stvjc@channing.harvard.edu|Channing Laboratory, Brigham and Womens Hospital, 75 Francis Street, Boston 02115, USA. stvjc@channing.harvard.edu', 'United States|United States|United States|United States|United States', 4, 'Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Gene Expression Profiling|Genetic Variation|Genetics, Population|Models, Genetic|Polymorphism, Single Nucleotide|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl628', '17158513', 'This paper reviews the central concepts and implementation of data structures and methods for studying genetics of gene expression with the GGtools package of Bioconductor. Illustration with a HapMap+expression dataset is provided.'),
(73188, 2007, 'bio', 'Assembling millions of short DNA sequences using SSAKE', 'Warren, René L|Sutton, Granger G|Jones, Steven J M|Holt, Robert A', 'British Columbia Cancer Agency, Genome Sciences Centre, 675 West 10th Avenue, Vancouver, BC V5Z 1L3, Canada. rwarren@bcgsc.ca|British Columbia Cancer Agency, Genome Sciences Centre, 675 West 10th Avenue, Vancouver, BC V5Z 1L3, Canada. rwarren@bcgsc.ca|British Columbia Cancer Agency, Genome Sciences Centre, 675 West 10th Avenue, Vancouver, BC V5Z 1L3, Canada. rwarren@bcgsc.ca|British Columbia Cancer Agency, Genome Sciences Centre, 675 West 10th Avenue, Vancouver, BC V5Z 1L3, Canada. rwarren@bcgsc.ca', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Contig Mapping|Molecular Sequence Data|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btl629', '17158514', 'Novel DNA sequencing technologies with the potential for up to three orders magnitude more sequence throughput than conventional Sanger sequencing are emerging. The instrument now available from Solexa Ltd, produces millions of short DNA sequences of 25 nt each. Due to ubiquitous repeats in large genomes and the inability of short sequences to uniquely and unambiguously characterize them, the short read length limits applicability for de novo sequencing. However, given the sequencing depth and the throughput of this instrument, stringent assembly of highly identical sequences can be achieved. We describe SSAKE, a tool for aggressively assembling millions of short nucleotide sequences by progressively searching through a prefix tree for the longest possible overlap between any two sequences. SSAKE is designed to help leverage the information from short sequence reads by stringently assembling them into contiguous sequences that can be used to characterize novel sequencing targets.'),
(73189, 2007, 'bio', 'Quantitative performance metrics for robustness in circadian rhythms', 'Bagheri, Neda|Stelling, Jörg|Doyle, Francis J', 'Department of Electrical and Computer Engineering, University of California in Santa Barbara, CA 93106-9560, USA.|Department of Electrical and Computer Engineering, University of California in Santa Barbara, CA 93106-9560, USA.|Department of Electrical and Computer Engineering, University of California in Santa Barbara, CA 93106-9560, USA.', 'United States|United States|United States', 0, 'Animals|Biological Clocks|Circadian Rhythm|Computer Simulation|Drosophila|Feedback|Mice|Models, Biological|Reproducibility of Results|Sensitivity and Specificity|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btl627', '17158515', 'Sensitivity analysis provides key measures that aid in unraveling the design principles responsible for the robust performance of biological networks. Such metrics allow researchers to investigate comprehensively model performance, to develop more realistic models, and to design informative experiments. However, sensitivity analysis of oscillatory systems focuses on period and amplitude characteristics, while biologically relevant effects on phase are neglected.'),
(73190, 2007, 'bio', 'Causality and pathway search in microarray time series experiment', 'Mukhopadhyay, Nitai D|Chatterjee, Snigdhansu', 'Eli Lilly and Co. nitai@lilly.com|Eli Lilly and Co. nitai@lilly.com', '-|-', 95, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction|Time Factors', 'Journal Article', '10.1093/bioinformatics/btl598', '17158516', 'Interaction among time series can be explored in many ways. All the approach has the usual problem of low power and high dimensional model. Here we attempted to build a causality network among a set of time series. The causality has been established by Granger causality, and then constructing the pathway has been implemented by finding the Minimal Spanning Tree within each connected component of the inferred network. False discovery rate measurement has been used to identify the most significant causalities.'),
(73191, 2007, 'bio', 'Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data', 'Lerman, Gilad|McQuown, Joseph|Blais, Alexandre|Dynlacht, Brian D|Chen, Guangliang|Mishra, Bud', 'Department of Mathematics, University of Minnesota, 127 Vincent Hall, 206 Church St. S.E., Minneapolis, MN 55455, USA. lerman@umn.edu|Department of Mathematics, University of Minnesota, 127 Vincent Hall, 206 Church St. S.E., Minneapolis, MN 55455, USA. lerman@umn.edu|Department of Mathematics, University of Minnesota, 127 Vincent Hall, 206 Church St. S.E., Minneapolis, MN 55455, USA. lerman@umn.edu|Department of Mathematics, University of Minnesota, 127 Vincent Hall, 206 Church St. S.E., Minneapolis, MN 55455, USA. lerman@umn.edu|Department of Mathematics, University of Minnesota, 127 Vincent Hall, 206 Church St. S.E., Minneapolis, MN 55455, USA. lerman@umn.edu|Department of Mathematics, University of Minnesota, 127 Vincent Hall, 206 Church St. S.E., Minneapolis, MN 55455, USA. lerman@umn.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Chromatin Immunoprecipitation|Chromosome Mapping|Gene Expression Profiling|Multivariate Analysis|Oligonucleotide Array Sequence Analysis|Proteome', 'Journal Article', '10.1093/bioinformatics/btl606', '17164284', 'We present a fast, versatile and adaptive-multiscale algorithm for analyzing a wide-variety of DNA microarray data. Its primary application is in normalization of array data as well as subsequent identification of enriched targets, e.g. differentially expressed genes in expression profiling arrays and enriched sites in ChIP-on-chip experimental data. We show how to accommodate the unique characteristics of ChIP-on-chip data, where the set of enriched targets is large, asymmetric and whose proportion to the whole data varies locally.'),
(73192, 2007, 'bio', 'Segmentation and intensity estimation of microarray images using a gamma-t mixture model', 'Baek, Jangsun|Son, Young Sook|McLachlan, Geoffrey J', 'Department of Statistics, Chonnam National University, Gwangju 500-757, South Korea. jbaek@chonnam.ac.kr|Department of Statistics, Chonnam National University, Gwangju 500-757, South Korea. jbaek@chonnam.ac.kr|Department of Statistics, Chonnam National University, Gwangju 500-757, South Korea. jbaek@chonnam.ac.kr', '-|-|-', 0, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Image Interpretation, Computer-Assisted|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence|Models, Statistical|Oligonucleotide Array Sequence Analysis|Photometry|Spectrometry, Fluorescence', 'Journal Article', '10.1093/bioinformatics/btl630', '17166856', 'We present a new approach to the analysis of images for complementary DNA microarray experiments. The image segmentation and intensity estimation are performed simultaneously by adopting a two-component mixture model. One component of this mixture corresponds to the distribution of the background intensity, while the other corresponds to the distribution of the foreground intensity. The intensity measurement is a bivariate vector consisting of red and green intensities. The background intensity component is modeled by the bivariate gamma distribution, whose marginal densities for the red and green intensities are independent three-parameter gamma distributions with different parameters. The foreground intensity component is taken to be the bivariate t distribution, with the constraint that the mean of the foreground is greater than that of the background for each of the two colors. The degrees of freedom of this t distribution are inferred from the data but they could be specified in advance to reduce the computation time. Also, the covariance matrix is not restricted to being diagonal and so it allows for nonzero correlation between R and G foreground intensities. This gamma-t mixture model is fitted by maximum likelihood via the EM algorithm. A final step is executed whereby nonparametric (kernel) smoothing is undertaken of the posterior probabilities of component membership. The main advantages of this approach are: (1) it enjoys the well-known strengths of a mixture model, namely flexibility and adaptability to the data, (2) it considers the segmentation and intensity simultaneously and not separately as in commonly used existing software, and it also works with the red and green intensities in a bivariate framework as opposed to their separate estimation via univariate methods, (3) the use of the three-parameter gamma distribution for the background red and green intensities provides a much better fit than the normal (log normal) or t distributions, (4) the use of the bivariate t distribution for the foreground intensity provides a model that is less sensitive to extreme observations, (5) as a consequence of the aforementioned properties, it allows segmentation to be undertaken for a wide range of spot shapes, including doughnut, sickle shape and artifacts.'),
(73193, 2007, 'bio', 'Enrichment or depletion of a GO category within a class of genes: which test?', 'Rivals, Isabelle|Personnaz, Léon|Taing, Lieng|Potier, Marie-Claude', 'Equipe de Statistique Appliquée, 10 rue Vauquelin, 75005 Paris, France. isabelle.rivals@espci.fr|Equipe de Statistique Appliquée, 10 rue Vauquelin, 75005 Paris, France. isabelle.rivals@espci.fr|Equipe de Statistique Appliquée, 10 rue Vauquelin, 75005 Paris, France. isabelle.rivals@espci.fr|Equipe de Statistique Appliquée, 10 rue Vauquelin, 75005 Paris, France. isabelle.rivals@espci.fr', 'France|France|France|France', 389, 'Data Interpretation, Statistical|Database Management Systems|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Multigene Family|Oligonucleotide Array Sequence Analysis|Proteins', 'Evaluation Studies', '10.1093/bioinformatics/btl633', '17182697', 'A number of available program packages determine the significant enrichments and/or depletions of GO categories among a class of genes of interest. Whereas a correct formulation of the problem leads to a single exact null distribution, these GO tools use a large variety of statistical tests whose denominations often do not clarify the underlying P-value computations.'),
(73194, 2007, 'bio', 'Robust prediction of consensus secondary structures using averaged base pairing probability matrices', 'Kiryu, Hisanori|Kin, Taishin|Asai, Kiyoshi', 'Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-42 Aomi, Koto-ku, Tokyo, 135-0064, Japan. kiryu-h@aist.go.jp|Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-42 Aomi, Koto-ku, Tokyo, 135-0064, Japan. kiryu-h@aist.go.jp|Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology, 2-42 Aomi, Koto-ku, Tokyo, 135-0064, Japan. kiryu-h@aist.go.jp', 'Japan|Japan|Japan', 0, 'Algorithms|Base Pair Mismatch|Base Pairing|Computer Simulation|Consensus Sequence|Models, Genetic|Models, Statistical|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btl636', '17182698', 'Recent transcriptomic studies have revealed the existence of a considerable number of non-protein-coding RNA transcripts in higher eukaryotic cells. To investigate the functional roles of these transcripts, it is of great interest to find conserved secondary structures from multiple alignments on a genomic scale. Since multiple alignments are often created using alignment programs that neglect the special conservation patterns of RNA secondary structures for computational efficiency, alignment failures can cause potential risks of overlooking conserved stem structures.'),
(73195, 2007, 'bio', 'URec: a system for unrooted reconciliation', 'Górecki, Pawel|Tiuryn, Jerzy', 'Institute of Informatics, Warsaw University, Banacha 2, 02-678 Warsaw, Poland. gorecki@mimuw.edu.pl|Institute of Informatics, Warsaw University, Banacha 2, 02-678 Warsaw, Poland. gorecki@mimuw.edu.pl', 'Poland|Poland', 0, 'Algorithms|Biological Evolution|Computer Simulation|Genetic Variation|Genetics, Population|Models, Genetic|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btl634', '17182699', 'URec is a software based on a concept of unrooted reconciliation. It can be used to reconcile a set of unrooted gene trees with a rooted species tree or a set of rooted species trees. Moreover, it computes detailed distribution of gene duplications and gene losses in a species tree. It can be used to infer optimal species phylogenies for a given set of gene trees. URec is implemented in C++ and can be easily compiled under Unix and Windows systems.'),
(73196, 2007, 'bio', 'Clustering threshold gradient descent regularization: with applications to microarray studies', 'Ma, Shuangge|Huang, Jian', 'Department of Epidemiology and Public Health, Yale University, New Haven, CT, USA. shuangge.ma@yale.edu|Department of Epidemiology and Public Health, Yale University, New Haven, CT, USA. shuangge.ma@yale.edu', 'United States|United States', 20, 'Algorithms|Biomarkers, Tumor|Cluster Analysis|Gene Expression Profiling|Humans|Multigene Family|Neoplasm Proteins|Neoplasms|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btl632', '17182700', 'An important goal of microarray studies is to discover genes that are associated with clinical outcomes, such as disease status and patient survival. While a typical experiment surveys gene expressions on a global scale, there may be only a small number of genes that have significant influence on a clinical outcome. Moreover, expression data have cluster structures and the genes within a cluster have correlated expressions and coordinated functions, but the effects of individual genes in the same cluster may be different. Accordingly, we seek to build statistical models with the following properties. First, the model is sparse in the sense that only a subset of the parameter vector is non-zero. Second, the cluster structures of gene expressions are properly accounted for.'),
(73197, 2007, 'bio', 'The discovery of transcriptional modules by a two-stage matrix decomposition approach', 'Li, Huai|Sun, Yu|Zhan, Ming', 'Bioinformatics Unit, Branch of Research Resources, National Institute on Aging, NIH, Baltimore, MD 21224, USA.|Bioinformatics Unit, Branch of Research Resources, National Institute on Aging, NIH, Baltimore, MD 21224, USA.|Bioinformatics Unit, Branch of Research Resources, National Institute on Aging, NIH, Baltimore, MD 21224, USA.', 'United States|United States|United States', 0, 'Algorithms|Gene Expression|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Signal Transduction|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btl640', '17189296', 'We address the problem of identifying gene transcriptional modules from gene expression data by proposing a new approach. Genes mostly interact with each other to form transcriptional modules for context-specific cellular activities or functions. Unraveling such transcriptional modules is important for understanding biological network, deciphering regulatory mechanisms and identifying biomarkers.'),
(73198, 2007, 'bio', 'SNPchip: R classes and methods for SNP array data', 'Scharpf, Robert B|Ting, Jason C|Pevsner, Jonathan|Ruczinski, Ingo', 'Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.', 'United States|United States|United States|United States', 8, 'Models, Statistical|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btl638', '17204461', 'High-density single nucleotide polymorphism microarrays (SNP chips) provide information on a subjects genome, such as copy number and genotype (heterozygosity/homozygosity) at a SNP. While fluorescence in situ hybridization and karyotyping reveal many abnormalities, SNP chips provide a higher resolution map of the human genome that can be used to detect, e.g., aneuploidies, microdeletions, microduplications and loss of heterozygosity (LOH). As a variety of diseases are linked to such chromosomal abnormalities, SNP chips promise new insights for these diseases by aiding in the discovery of such regions, and may suggest targets for intervention. The R package SNPchip contains classes and methods useful for storing, visualizing and analyzing high density SNP data. Originally developed from the SNPscan web-tool, SNPchip utilizes S4 classes and extends other open source R tools available at Bioconductor. This has numerous advantages, including the ability to build statistical models for SNP-level data that operate on instances of the class, and to communicate with other R packages that add additional functionality.'),
(73199, 2007, 'bio', 'Oligonucleotide microarray identification of Bacillus anthracis strains using support vector machines', 'Doran, M|Raicu, D S|Furst, J D|Settimi, R|Schipma, M|Chandler, D P', 'Intelligent Multimedia Processing Laboratory, School of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago, USA. doran_michael@msn.com|Intelligent Multimedia Processing Laboratory, School of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago, USA. doran_michael@msn.com|Intelligent Multimedia Processing Laboratory, School of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago, USA. doran_michael@msn.com|Intelligent Multimedia Processing Laboratory, School of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago, USA. doran_michael@msn.com|Intelligent Multimedia Processing Laboratory, School of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago, USA. doran_michael@msn.com|Intelligent Multimedia Processing Laboratory, School of Computer Science, Telecommunications and Information Systems, DePaul University, Chicago, USA. doran_michael@msn.com', 'United States|United States|United States|United States|United States|United States', 12, 'Algorithms|Artificial Intelligence|Bacillus anthracis|Chromosome Mapping|DNA Fingerprinting|DNA, Bacterial|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btl626', '17204462', 'The capability of a custom microarray to discriminate between closely related DNA samples is demonstrated using a set of Bacillus anthracis strains. The microarray was developed as a universal fingerprint device consisting of 390 genome-independent 9mer probes. The genomes of B. anthracis strains are monomorphic and therefore, typically difficult to distinguish using conventional molecular biology tools or microarray data clustering techniques. Using support vector machines (SVMs) as a supervised learning technique, we show that a low-density fingerprint microarray contains enough information to discriminate between B. anthracis strains with 90% sensitivity using a reference library constructed from six replicate arrays and three replicates for new isolates.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73200, 2007, 'bio', 'MinSet: a general approach to derive maximally representative database subsets by using fragment dictionaries and its application to the SCOP database', 'Pandini, Alessandro|Bonati, Laura|Fraternali, Franca|Kleinjung, Jens', 'Dipartimento di Scienze dellAmbiente e del Territorio, Università degli Studi di Milano-Bicocca, Milano, Italy.|Dipartimento di Scienze dellAmbiente e del Territorio, Università degli Studi di Milano-Bicocca, Milano, Italy.|Dipartimento di Scienze dellAmbiente e del Territorio, Università degli Studi di Milano-Bicocca, Milano, Italy.|Dipartimento di Scienze dellAmbiente e del Territorio, Università degli Studi di Milano-Bicocca, Milano, Italy.', 'Italy|Italy|Italy|Italy', 12, 'Algorithms|Data Compression|Database Management Systems|Databases, Protein|Dictionaries, Chemical as Topic|Peptide Fragments|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btl637', '17204463', 'The size of current protein databases is a challenge for many Bioinformatics applications, both in terms of processing speed and information redundancy. It may be therefore desirable to efficiently reduce the database of interest to a maximally representative subset.'),
(73201, 2007, 'bio', 'SChiSM2: creating interactive web page annotations of molecular structure models using Jmol', 'Cammer, Stephen', 'Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA. cammer@vbi.vt.edu', 'United States', 11, 'Algorithms|Biopolymers|Computer Graphics|Computer Simulation|Databases, Factual|Documentation|Information Storage and Retrieval|Internet|Models, Chemical|Models, Molecular|Molecular Conformation|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl603', '17204464', 'SChiSM2 is a web server-based program for creating web pages that include interactive molecular graphics using the freely-available applet, Jmol, for illustration. The program works with Internet Explorer and Firefox on Windows, Safari and Firefox on Mac OSX and Firefox on Linux.'),
(73202, 2007, 'bio', 'In search of the small ones: improved prediction of short exons in vertebrates, plants, fungi and protists', 'Saeys, Yvan|Rouzé, Pierre|Van de Peer, Yves', 'Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Ghent, Belgium. yvan.saeys@psb.ugent.be|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Ghent, Belgium. yvan.saeys@psb.ugent.be|Department of Plant Systems Biology, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Ghent, Belgium. yvan.saeys@psb.ugent.be', 'Belgium|Belgium|Belgium', 37, 'Algorithms|Animals|Artificial Intelligence|Base Sequence|DNA, Bacterial|DNA, Fungal|DNA, Plant|Exons|Molecular Sequence Data|Open Reading Frames|Pattern Recognition, Automated|Sequence Analysis, DNA|Vertebrates', 'Journal Article', '10.1093/bioinformatics/btl639', '17204465', 'Prediction of the coding potential for stretches of DNA is crucial in gene calling and genome annotation, where it is used to identify potential exons and to position their boundaries in conjunction with functional sites, such as splice sites and translation initiation sites. The ability to discriminate between coding and non-coding sequences relates to the structure of coding sequences, which are organized in codons, and by their biased usage. For statistical reasons, the longer the sequences, the easier it is to detect this codon bias. However, in many eukaryotic genomes, where genes harbour many introns, both introns and exons might be small and hard to distinguish based on coding potential.'),
(73203, 2007, 'bio', 'Protein-protein interaction site prediction based on conditional random fields', 'Li, Ming-Hui|Lin, Lei|Wang, Xiao-Long|Liu, Tao', 'Bioinformatics Research Group, ITNLP Lab, Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. mhli@insun.hit.edu.cn|Bioinformatics Research Group, ITNLP Lab, Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. mhli@insun.hit.edu.cn|Bioinformatics Research Group, ITNLP Lab, Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. mhli@insun.hit.edu.cn|Bioinformatics Research Group, ITNLP Lab, Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China. mhli@insun.hit.edu.cn', 'China|China|China|China', 68, 'Algorithms|Binding Sites|Conserved Sequence|Databases, Protein|Models, Molecular|Protein Conformation|Protein Interaction Mapping|Proteins', 'Comparative Study', '10.1093/bioinformatics/btl660', '17234636', 'We are motivated by the fast-growing number of protein structures in the Protein Data Bank with necessary information for prediction of protein-protein interaction sites to develop methods for identification of residues participating in protein-protein interactions. We would like to compare conditional random fields (CRFs)-based method with conventional classification-based methods that omit the relation between two labels of neighboring residues to show the advantages of CRFs-based method in predicting protein-protein interaction sites.'),
(73204, 2007, 'bio', 'snpplotter: an R-based SNP/haplotype association and linkage disequilibrium plotting package', 'Luna, Augustin|Nicodemus, Kristin K', 'GCAP/CBDB, NIMH/NIH, 10 Center Drive, Room 4S-235, Bethesda, MD 20814, USA.|GCAP/CBDB, NIMH/NIH, 10 Center Drive, Room 4S-235, Bethesda, MD 20814, USA.', 'United States|United States', 62, 'Algorithms|Chromosome Mapping|Computer Graphics|DNA Mutational Analysis|Haplotypes|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl657', '17234637', 'snp.plotter is a newly developed R package which produces high-quality plots of results from genetic association studies. The main features of the package include options to display a linkage disequilibrium (LD) plot below the P-value plot using either the r2 or D LD metric, to set the X-axis to equal spacing or to use the physical map of markers, and to specify plot labels, colors, symbols and LD heatmap color scheme. snp.plotter can plot single SNP and/or haplotype data and simultaneously plot multiple sets of results. R is a free software environment for statistical computing and graphics available for most platforms. The proposed package provides a simple way to convey both association and LD information in a single appealing graphic for genetic association studies.'),
(73205, 2007, 'bio', 'A structural alignment kernel for protein structures', 'Qiu, Jian|Hue, Martial|Ben-Hur, Asa|Vert, Jean-Philippe|Noble, William Stafford', 'Department of Genome Sciences, University of Washington, Seattle, WA, USA.|Department of Genome Sciences, University of Washington, Seattle, WA, USA.|Department of Genome Sciences, University of Washington, Seattle, WA, USA.|Department of Genome Sciences, University of Washington, Seattle, WA, USA.|Department of Genome Sciences, University of Washington, Seattle, WA, USA.', 'United States|United States|United States|United States|United States', 32, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btl642', '17234638', 'This work aims to develop computational methods to annotate protein structures in an automated fashion. We employ a support vector machine (SVM) classifier to map from a given class of structures to their corresponding structural (SCOP) or functional (Gene Ontology) annotation. In particular, we build upon recent work describing various kernels for protein structures, where a kernel is a similarity function that the classifier uses to compare pairs of structures.'),
(73206, 2007, 'bio', 'Deleterious SNP prediction: be mindful of your training data!', 'Care, Matthew A|Needham, Chris J|Bulpitt, Andrew J|Westhead, David R', 'Institute of Molecular and Cellular Biology, University of Leeds, Leeds, LS2 9JT, UK and School of Computing, University of Leeds, Leeds, LS2 9JT, UK.|Institute of Molecular and Cellular Biology, University of Leeds, Leeds, LS2 9JT, UK and School of Computing, University of Leeds, Leeds, LS2 9JT, UK.|Institute of Molecular and Cellular Biology, University of Leeds, Leeds, LS2 9JT, UK and School of Computing, University of Leeds, Leeds, LS2 9JT, UK.|Institute of Molecular and Cellular Biology, University of Leeds, Leeds, LS2 9JT, UK and School of Computing, University of Leeds, Leeds, LS2 9JT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 42, 'Algorithms|Artifacts|Artificial Intelligence|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Genetic Variation|Genome, Human|Humans|Molecular Sequence Data|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btl649', '17234639', 'To predict which of the vast number of human single nucleotide polymorphisms (SNPs) are deleterious to gene function or likely to be disease associated is an important problem, and many methods have been reported in the literature. All methods require data sets of mutations classified as deleterious or neutral for training and/or validation. While different workers have used different data sets there has been no study of which is best. Here, the three most commonly used data sets are analysed. We examine their contents and relate this to classifiers, with the aims of revealing the strengths and pitfalls of each data set, and recommending a best approach for future studies.'),
(73207, 2007, 'bio', 'Nested Containment List (NCList): a new algorithm for accelerating interval query of genome alignment and interval databases', 'Alekseyenko, Alexander V|Lee, Christopher J', 'Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095-1570, USA.|Department of Biomathematics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095-1570, USA.', 'United States|United States', 29, 'Algorithms|Base Sequence|Chromosome Mapping|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btl647', '17234640', 'The exponential growth of sequence databases poses a major challenge to bioinformatics tools for querying alignment and annotation databases. There is a pressing need for methods for finding overlapping sequence intervals that are highly scalable to database size, query interval size, result size and construction/updating of the interval database.'),
(73208, 2007, 'bio', 'CoCo: a web application to display, store and curate ChIP-on-chip data integrated with diverse types of gene expression data', 'Girardot, Charles|Sklyar, Oleg|Grosz, Sophie|Huber, Wolfgang|Furlong, Eileen E M', 'European Molecular Biology Laboratory, D-69117 Heidelberg, Germany. charles.girardot@embl.de|European Molecular Biology Laboratory, D-69117 Heidelberg, Germany. charles.girardot@embl.de|European Molecular Biology Laboratory, D-69117 Heidelberg, Germany. charles.girardot@embl.de|European Molecular Biology Laboratory, D-69117 Heidelberg, Germany. charles.girardot@embl.de|European Molecular Biology Laboratory, D-69117 Heidelberg, Germany. charles.girardot@embl.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Chromatin Immunoprecipitation|Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl641', '17234641', 'CoCo, ChIP-on-Chip online, is an open-source web application that supports the annotation and curation of regulatory regions and associated target genes discovered in ChIP-on-chip experiments. CoCo integrates ChIP-on-chip results with diverse types of gene expression data (expression profiling, in situ hybridization) and displays them within a genomic context. Regulatory relationships between the transcription factor-bound regions and putative target genes can be stored and expanded throughout different sessions.'),
(73209, 2007, 'bio', 'TreeQ-VISTA: an interactive tree visualization tool with functional annotation query capabilities', 'Gu, Shengyin|Anderson, Iain|Kunin, Victor|Cipriano, Michael|Minovitsky, Simon|Weber, Gunther|Amenta, Nina|Hamann, Bernd|Dubchak, Inna', 'Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, One Shields Ave., Davis, CA 95616, USA.|Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, One Shields Ave., Davis, CA 95616, USA.|Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, One Shields Ave., Davis, CA 95616, USA.|Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, One Shields Ave., Davis, CA 95616, USA.|Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, One Shields Ave., Davis, CA 95616, USA.|Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, One Shields Ave., Davis, CA 95616, USA.|Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, One Shields Ave., Davis, CA 95616, USA.|Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, One Shields Ave., Davis, CA 95616, USA.|Institute for Data Analysis and Visualization (IDAV), Department of Computer Science, University of California, Davis, One Shields Ave., Davis, CA 95616, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 6, 'Chromosome Mapping|Computer Graphics|Computer Simulation|Database Management Systems|Databases, Genetic|Evolution, Molecular|Information Storage and Retrieval|Models, Genetic|Phylogeny|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btl643', '17234642', 'We describe a general multiplatform exploratory tool called TreeQ-Vista, designed for presenting functional annotations in a phylogenetic context. Traits, such as phenotypic and genomic properties, are interactively queried from a user-provided relational database with a user-friendly interface which provides a set of tools for users with or without SQL knowledge. The query results are projected onto a phylogenetic tree and can be displayed in multiple color groups. A rich set of browsing, grouping and query tools are provided to facilitate trait exploration, comparison and analysis.'),
(73210, 2007, 'bio', 'A faster circular binary segmentation algorithm for the analysis of array CGH data', 'Venkatraman, E S|Olshen, Adam B', 'Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10021, USA. venkatre@mskcc.org|Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, 1275 York Avenue, New York, NY 10021, USA. venkatre@mskcc.org', 'United States|United States', 601, 'Algorithms|Chromosome Mapping|Gene Dosage|Oligonucleotide Array Sequence Analysis|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software|Time Factors', 'Evaluation Studies', '10.1093/bioinformatics/btl646', '17234643', 'Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number. The algorithm tests for change-points using a maximal t-statistic with a permutation reference distribution to obtain the corresponding P-value. The number of computations required for the maximal test statistic is O(N2), where N is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster algorithm.'),
(73211, 2007, 'bio', 'Assessment of phylogenomic and orthology approaches for phylogenetic inference', 'Dutilh, B E|van Noort, V|van der Heijden, R T J M|Boekhout, T|Snel, B|Huynen, M A', 'Center for Molecular and Biomolecular Informatics/Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics/Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics/Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics/Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics/Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Center for Molecular and Biomolecular Informatics/Nijmegen Center for Molecular Life Sciences, Radboud University Nijmegen Medical Center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands. dutilh@cmbi.ru.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 52, 'Algorithms|Base Sequence|Chromosome Mapping|Evolution, Molecular|Genetic Variation|Genome, Fungal|Molecular Sequence Data|Phylogeny|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btm015', '17237036', 'Phylogenomics integrates the vast amount of phylogenetic information contained in complete genome sequences, and is rapidly becoming the standard for reliably inferring species phylogenies. There are, however, fundamental differences between the ways in which phylogenomic approaches like gene content, superalignment, superdistance and supertree integrate the phylogenetic information from separate orthologous groups. Furthermore, they all depend on the method by which the orthologous groups are initially determined. Here, we systematically compare these four phylogenomic approaches, in parallel with three approaches for large-scale orthology determination: pairwise orthology, cluster orthology and tree-based orthology.'),
(73212, 2007, 'bio', 'A new versatile database created for geneticists and breeders to link molecular and phenotypic data in perennial crops: the AppleBreed DataBase', 'Antofie, A|Lateur, M|Oger, R|Patocchi, A|Durel, C E|Van de Weg, W E', 'Walloon Agricultural Research Centre, Gembloux, Liroux 9, B-5030, Belgium.|Walloon Agricultural Research Centre, Gembloux, Liroux 9, B-5030, Belgium.|Walloon Agricultural Research Centre, Gembloux, Liroux 9, B-5030, Belgium.|Walloon Agricultural Research Centre, Gembloux, Liroux 9, B-5030, Belgium.|Walloon Agricultural Research Centre, Gembloux, Liroux 9, B-5030, Belgium.|Walloon Agricultural Research Centre, Gembloux, Liroux 9, B-5030, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 18, 'Breeding|DNA, Plant|Database Management Systems|Databases, Genetic|Genetic Techniques|Information Storage and Retrieval|Internet|Phenotype|Plant Proteins|Plants|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm013', '17237037', 'AppleBreed DataBase (DB) aims to store genotypic and phenotypic data from multiple pedigree verified plant populations (crosses, breeding selections and commercial cultivars) so that they are easily accessible for geneticists and breeders. It will help in elucidating the genetics of economically important traits, in identifying molecular markers associated with agronomic traits, in allele mining and in choosing the best parental cultivars for breeding. It also provides high traceability of data over generations, years and localities. AppleBreed DB could serve as a generic database design for other perennial crops with long economic lifespans, long juvenile periods and clonal propagation.'),
(73213, 2007, 'bio', 'R/qtlbim: QTL with Bayesian Interval Mapping in experimental crosses', 'Yandell, Brian S|Mehta, Tapan|Banerjee, Samprit|Shriner, Daniel|Venkataraman, Ramprasad|Moon, Jee Young|Neely, W Whipple|Wu, Hao|von Smith, Randy|Yi, Nengjun', 'Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu|Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu|Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu|Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu|Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu|Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu|Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu|Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu|Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu|Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. byandell@wisc.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 74, 'Algorithms|Bayes Theorem|Chromosome Mapping|Crosses, Genetic|Epistasis, Genetic|Markov Chains|Monte Carlo Method|Quantitative Trait Loci', 'Journal Article', '10.1093/bioinformatics/btm011', '17237038', 'R/qtlbim is an extensible, interactive environment for the Bayesian Interval Mapping of QTL, built on top of R/qtl (Broman et al., 2003), providing Bayesian analysis of multiple interacting quantitative trait loci (QTL) models for continuous, binary and ordinal traits in experimental crosses. It includes several efficient Markov chain Monte Carlo (MCMC) algorithms for evaluating the posterior of genetic architectures, i.e. the number and locations of QTL, their main and epistatic effects and gene-environment interactions. R/qtlbim provides extensive informative graphical and numerical summaries, and model selection and convergence diagnostics of the MCMC output, illustrated through the vignette, example and demo capabilities of R (R Development Core Team 2006).'),
(73214, 2007, 'bio', 'Identifying bacterial genes and endosymbiont DNA with Glimmer', 'Delcher, Arthur L|Bratke, Kirsten A|Powers, Edwin C|Salzberg, Steven L', 'Center for Bioinformatics & Computational Biology, University of Maryland, College Park, MD 20742, USA. adelcher@umiacs.umd.edu|Center for Bioinformatics & Computational Biology, University of Maryland, College Park, MD 20742, USA. adelcher@umiacs.umd.edu|Center for Bioinformatics & Computational Biology, University of Maryland, College Park, MD 20742, USA. adelcher@umiacs.umd.edu|Center for Bioinformatics & Computational Biology, University of Maryland, College Park, MD 20742, USA. adelcher@umiacs.umd.edu', 'United States|United States|United States|United States', 1796, 'Algorithms|Animals|Artifacts|Chromosome Mapping|DNA, Bacterial|Decapodiformes|Genome, Bacterial|Prochloron|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software|Symbiosis', 'Evaluation Studies', '10.1093/bioinformatics/btm009', '17237039', 'The Glimmer gene-finding software has been successfully used for finding genes in bacteria, archaea and viruses representing hundreds of species. We describe several major changes to the Glimmer system, including improved methods for identifying both coding regions and start codons. We also describe a new module of Glimmer that can distinguish host and endosymbiont DNA. This module was developed in response to the discovery that eukaryotic genome sequencing projects sometimes inadvertently capture the DNA of intracellular bacteria living in the host.'),
(73215, 2007, 'bio', 'Modeling nonlinearity in dilution design microarray data', 'Zheng, Xiuwen|Huang, Hung-Chung|Li, Wenyuan|Liu, Peng|Li, Quan-Zhen|Liu, Ying', 'Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX 75083-0688, USA.|Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX 75083-0688, USA.|Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX 75083-0688, USA.|Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX 75083-0688, USA.|Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX 75083-0688, USA.|Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX 75083-0688, USA.', 'United States|United States|United States|United States|United States|United States', 3, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Models, Genetic|Nonlinear Dynamics|Oligonucleotide Array Sequence Analysis|RNA', 'Journal Article', '10.1093/bioinformatics/btm002', '17237040', 'Dilution design (Mixed tissue RNA) has been utilized by some researchers to evaluate and assess the performance of multiple microarray platforms. Current microarray data analysis approaches assume that the quantified signal intensities are linearly related to the expression of the corresponding genes in the sample. However, there are sources of nonlinearity in microarray expression measurements. Such nonlinearity study in the expressions of the RNA mixtures provides a new way to analyze gene expression data, and we argue that the nonlinearity can reveal novel information for microarray data analysis. Therefore, we proposed a statistical model, called proportion model, which is based on the linear regression analysis. To approximately quantify the nonlinearity in the dilution design, a new calibration, beta ratio (BR) was derived from the proportion model. Furthermore, a new adjusted fold change (adj-FC) was proposed to predict the true FC without nonlinearity, in particular for large FC.'),
(73216, 2007, 'bio', 'A computational system to select candidate genes for complex human traits', 'Gaulton, Kyle J|Mohlke, Karen L|Vision, Todd J', 'Curriculum in Genetics and Molecular Biologly, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA. kgaulton@email.unc.edu|Curriculum in Genetics and Molecular Biologly, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA. kgaulton@email.unc.edu|Curriculum in Genetics and Molecular Biologly, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA. kgaulton@email.unc.edu', 'United States|United States|United States', 66, 'Algorithms|Database Management Systems|Databases, Genetic|Genes|Information Storage and Retrieval|Natural Language Processing|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/btm001', '17237041', 'Identification of the genetic variation underlying complex traits is challenging. The wealth of information publicly available about the biology of complex traits and the function of individual genes permits the development of informatics-assisted methods for the selection of candidate genes for these traits.'),
(73217, 2007, 'bio', 'A hidden Markov model-based approach for identifying timing differences in gene expression under different experimental factors', 'Yoneya, Takashi|Mamitsuka, Hiroshi', 'Bioinformatics Center, Kyoto University, Gokasho Uji, 611-0011, Japan. t-yoneya@kirin.co.jp|Bioinformatics Center, Kyoto University, Gokasho Uji, 611-0011, Japan. t-yoneya@kirin.co.jp', 'Japan|Japan', 9, 'Artificial Intelligence|Computer Simulation|Gene Expression Profiling|Markov Chains|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Time Factors', 'Comparative Study', '10.1093/bioinformatics/btl667', '17237042', 'Time series experiments of cDNA microarrays have been commonly used in various biological studies and conducted under a lot of experimental factors. A popular approach of time series microarray analysis is to compare one gene with another in their expression profiles, and clustering expression sequences is a typical example. On the other hand, a practically important issue in gene expression is to identify the general timing difference that is caused by experimental factors. This type of difference can be extracted by comparing a set of time series expression profiles under a factor with those under another factor, and so it would be difficult to tackle this issue by using only a current approach for time series microarray analysis.'),
(73218, 2007, 'bio', 'FIVA: Functional Information Viewer and Analyzer extracting biological knowledge from transcriptome data of prokaryotes', 'Blom, Evert-Jan|Bosman, Dinne W J|van Hijum, Sacha A F T|Breitling, Rainer|Tijsma, Lars|Silvis, Remko|Roerdink, Jos B T M|Kuipers, Oscar P', 'Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, Groningen, The Netherlands.|Molecular Genetics, Groningen Biomolecular Sciences, University of Groningen, Groningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 24, 'Algorithms|Artificial Intelligence|Biology|Chromosome Mapping|Health Knowledge, Attitudes, Practice|Prokaryotic Cells|Software|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl658', '17237043', 'FIVA (Function Information Viewer and Analyzer) aids researchers in the prokaryotic community to quickly identify relevant biological processes following transcriptome analysis. Our software assists in functional profiling of large sets of genes and generates a comprehensive overview of affected biological processes.'),
(73219, 2007, 'bio', 'A 3D pattern matching algorithm for DNA sequences', 'Hérisson, Joan|Payen, Guillaume|Gherbi, Rachid', 'LIMSI-CNRS, Univ. Paris-Sud, 91403 Orsay, France. herisson@epigenomique.genopole.fr|LIMSI-CNRS, Univ. Paris-Sud, 91403 Orsay, France. herisson@epigenomique.genopole.fr|LIMSI-CNRS, Univ. Paris-Sud, 91403 Orsay, France. herisson@epigenomique.genopole.fr', 'France|France|France', 10, 'Algorithms|Base Sequence|Computer Simulation|DNA|Imaging, Three-Dimensional|Models, Chemical|Models, Molecular|Molecular Sequence Data|Nucleic Acid Conformation|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btl669', '17237044', 'Biologists usually work with textual DNA sequences (succession of A, C, G and T). This representation allows biologists to study the syntax and other linguistic properties of DNA sequences. Nevertheless, such a linear coding offers only a local and a one-dimensional vision of the molecule. The 3D structure of DNA is known to be very important in many essential biological mechanisms. By using 3D conformation models, one is able to construct a 3D trajectory of a naked DNA molecule. From the various studies that we performed, it turned out that two very different textual DNA sequences could have similar 3D structures.'),
(73220, 2007, 'bio', 'Genomic characterization of multiple clinical phenotypes of cancer using multivariate linear regression models', 'Matsui, Shigeyuki|Ito, Masaaki|Nishiyama, Hiroyuki|Uno, Hajime|Kotani, Hirokazu|Watanabe, Jun|Guilford, Parry|Reeve, Anthony|Fukushima, Masanori|Ogawa, Osamu', 'Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp|Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp|Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp|Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp|Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp|Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp|Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp|Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp|Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp|Department of Pharmacoepidemiology, Graduate School of Public Health, Kyoto University, Kyotom, Japan. matsui@pbh.med.kyoto-u.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 6, 'Biomarkers, Tumor|Chromosome Mapping|Computer Simulation|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Linear Models|Models, Genetic|Multivariate Analysis|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Phenotype|Regression Analysis|Urinary Bladder Neoplasms', 'Evaluation Studies', '10.1093/bioinformatics/btl663', '17237045', 'The development of gene expression microarray technology has allowed the identification of differentially expressed genes between different clinical phenotypic classes of cancer from a large pool of candidate genes. Although many class comparisons concerned only a single phenotype, simultaneous assessment of the relationship between gene expression and multiple phenotypes would be warranted to better understand the underlying biological structure.'),
(73221, 2007, 'bio', 'Computing exact P-values for DNA motifs', 'Zhang, Jing|Jiang, Bo|Li, Ming|Tromp, John|Zhang, Xuegong|Zhang, Michael Q', 'State Key Laboratory of Intelligent Technology & System, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.|State Key Laboratory of Intelligent Technology & System, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.|State Key Laboratory of Intelligent Technology & System, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.|State Key Laboratory of Intelligent Technology & System, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.|State Key Laboratory of Intelligent Technology & System, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.|State Key Laboratory of Intelligent Technology & System, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China.', 'China|China|China|China|China|China', 33, 'Algorithms|Binding Sites|Computer Simulation|Models, Statistical|Promoter Regions, Genetic|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btl662', '17237046', 'Many heuristic algorithms have been designed to approximate P-values of DNA motifs described by position weight matrices, for evaluating their statistical significance. They often significantly deviate from the true P-value by orders of magnitude. Exact P-value computation is needed for ranking the motifs. Furthermore, surprisingly, the complexity of the problem is unknown.'),
(73222, 2007, 'bio', 'Structure-based evaluation of in silico predictions of protein-protein interactions using Comparative Docking', 'Cockell, Simon J|Oliva, Baldo|Jackson, Richard M', 'Institute of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom.|Institute of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom.|Institute of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, United Kingdom.', 'United Kingdom|United Kingdom|United Kingdom', 18, 'Azotobacter vinelandii|Computer Simulation|Databases, Protein|Dihydrolipoamide Dehydrogenase|Insulin Receptor Substrate Proteins|Models, Molecular|Phosphoproteins|Protein Conformation|Protein Interaction Mapping|Proteins|Receptor, Insulin|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btl661', '17237047', 'Due to the limitations in experimental methods for determining binary interactions and structure determination of protein complexes, the need exists for computational models to fill the increasing gap between genome sequence information and protein annotation. Here we describe a novel method that uses structural models to reduce a large number of in silico predictions to a high confidence subset that is amenable to experimental validation.'),
(73223, 2007, 'bio', 'A new protein-protein docking scoring function based on interface residue properties', 'Bernauer, J|Azé, J|Janin, J|Poupon, A', 'Yeast Structural Genomics, IBBMC UMR CNRS 8619, Bâtiment 430, Université Paris-Sud, 91405 Orsay, France.|Yeast Structural Genomics, IBBMC UMR CNRS 8619, Bâtiment 430, Université Paris-Sud, 91405 Orsay, France.|Yeast Structural Genomics, IBBMC UMR CNRS 8619, Bâtiment 430, Université Paris-Sud, 91405 Orsay, France.|Yeast Structural Genomics, IBBMC UMR CNRS 8619, Bâtiment 430, Université Paris-Sud, 91405 Orsay, France.', 'France|France|France|France', 48, 'Algorithms|Computer Simulation|Models, Molecular|Multiprotein Complexes|Protein Binding|Protein Interaction Mapping|Software', 'Comparative Study', '10.1093/bioinformatics/btl654', '17237048', 'Protein-protein complexes are known to play key roles in many cellular processes. However, they are often not accessible to experimental study because of their low stability and difficulty to produce the proteins and assemble them in native conformation. Thus, docking algorithms have been developed to provide an in silico approach of the problem. A protein-protein docking procedure traditionally consists of two successive tasks: a search algorithm generates a large number of candidate solutions, and then a scoring function is used to rank them.'),
(73224, 2007, 'bio', 'On the derivation of propensity scales for predicting exposed transmembrane residues of helical membrane proteins', 'Park, Yungki|Helms, Volkhard', 'Center for Bioinformatics, Saarland University, Germany.|Center for Bioinformatics, Saarland University, Germany.', 'Germany|Germany', 22, 'Algorithms|Amino Acid Sequence|Amino Acids|Artificial Intelligence|Cell Membrane|Computer Simulation|Membrane Proteins|Models, Chemical|Molecular Sequence Data|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btl653', '17237049', 'Helical membrane proteins (HMPs) play a crucial role in diverse physiological processes. Given the difficulty in determining their structures by experimental techniques, it is desired to develop computational methods for predicting the burial status of transmembrane residues. Deriving a propensity scale for the 20 amino acids to be exposed to the lipid bilayer from known structures is central to developing such methods. A fundamental problem in this regard is what would be the optimal way of deriving propensity scales. Here, we show that this problem can be reformulated such that an optimal scale is straightforwardly obtained in an analytical fashion. The derived scale favorably compares with others in terms of both algorithmic optimality and practical prediction accuracy. It also allows interesting insights into the structural organization of HMPs. Furthermore, the presented approach can be applied to other bioinformatics problems of HMPs, too. All the data sets and programs used in the study and detailed primary results are available upon request.'),
(73225, 2007, 'bio', 'LFM-Pro: a tool for detecting significant local structural sites in proteins', 'Sacan, Ahmet|Ozturk, Ozgur|Ferhatosmanoglu, Hakan|Wang, Yusu', 'Department of Computer Engineering, Middle East Technical University, Ankara, Turkey. ahmet@ceng.metu.edu.tr|Department of Computer Engineering, Middle East Technical University, Ankara, Turkey. ahmet@ceng.metu.edu.tr|Department of Computer Engineering, Middle East Technical University, Ankara, Turkey. ahmet@ceng.metu.edu.tr|Department of Computer Engineering, Middle East Technical University, Ankara, Turkey. ahmet@ceng.metu.edu.tr', 'Turkey|Turkey|Turkey|Turkey', 20, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/btl685', '17237050', 'The rapidly growing protein structure repositories have opened up new opportunities for discovery and analysis of functional and evolutionary relationships among proteins. Detecting conserved structural sites that are unique to a protein family is of great value in identification of functionally important atoms and residues. Currently available methods are computationally expensive and fail to detect biologically significant local features.'),
(73226, 2007, 'bio', 'APOPTO-CELL--a simulation tool and interactive database for analyzing cellular susceptibility to apoptosis', 'Huber, Heinrich J|Rehm, Markus|Plchut, Martin|Düssmann, Heiko|Prehn, Jochen H M', 'Systems Biology Group, RCSI Research Institute, Dublin 2, Ireland.|Systems Biology Group, RCSI Research Institute, Dublin 2, Ireland.|Systems Biology Group, RCSI Research Institute, Dublin 2, Ireland.|Systems Biology Group, RCSI Research Institute, Dublin 2, Ireland.|Systems Biology Group, RCSI Research Institute, Dublin 2, Ireland.', 'Ireland|Ireland|Ireland|Ireland|Ireland', 25, 'Apoptosis|Apoptosis Regulatory Proteins|Computer Graphics|Computer Simulation|Databases, Protein|HeLa Cells|Humans|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl684', '17237051', 'We have developed a web service that provides a comprehensive analysis of the susceptibility of cells to undergo apoptosis in response to an activation of the mitochondrial apoptotic pathway. Based on ordinary differential equations, (pre-determined) protein concentrations and release kinetics of mitochondrial pro-apoptotic factors, a network of 52 reactions and 19 reaction partners can be employed as a tool to display temporal protein profiles, to identify key regulatory proteins and to determine critical threshold concentrations required for the execution of apoptosis in HeLa cancer cells or other cell types. The web service also provides an interactive database function for the deposition of cell-type-specific quantitative data. In addition, the web service provides an output that can be compared directly to experimental results obtained from real-time single-cell experiments, making this a widely applicable systems biology tool for apoptosis and cancer researchers.'),
(73227, 2007, 'bio', 'Comparison of human protein-protein interaction maps', 'Futschik, Matthias E|Chaurasia, Gautam|Herzel, Hanspeter', 'Institute for Theoretical Biology, Charité, Humboldt-Universität, 10115 Berlin, Germany. m.futschik@biologie.hu-berlin.de|Institute for Theoretical Biology, Charité, Humboldt-Universität, 10115 Berlin, Germany. m.futschik@biologie.hu-berlin.de|Institute for Theoretical Biology, Charité, Humboldt-Universität, 10115 Berlin, Germany. m.futschik@biologie.hu-berlin.de', 'Germany|Germany|Germany', 0, 'Computational Biology|Databases, Protein|Humans|Protein Interaction Mapping|Proteins|Proteomics', 'Comparative Study', '10.1093/bioinformatics/btl683', '17237052', 'Large-scale mappings of protein-protein interactions have started to give us new views of the complex molecular mechanisms inside a cell. After initial projects to systematically map protein interactions in model organisms such as yeast, worm and fly, researchers have begun to focus on the mapping of the human interactome. To tackle this enormous challenge, different approaches have been proposed and pursued. While several large-scale human protein interaction maps have recently been published, their quality remains to be critically assessed.'),
(73228, 2007, 'bio', 'AphidBase: a database for aphid genomic resources', 'Gauthier, Jean-Pierre|Legeai, Fabrice|Zasadzinski, Alain|Rispe, Claude|Tagu, Denis', 'INRA, Agrocampus Rennes, UMR 1099 BiO3P (Biology of Organisms and Populations applied to Plant Protection), F-35653 LE RHEU, France. jean-pierre.gauthier@rennes.infra.fr|INRA, Agrocampus Rennes, UMR 1099 BiO3P (Biology of Organisms and Populations applied to Plant Protection), F-35653 LE RHEU, France. jean-pierre.gauthier@rennes.infra.fr|INRA, Agrocampus Rennes, UMR 1099 BiO3P (Biology of Organisms and Populations applied to Plant Protection), F-35653 LE RHEU, France. jean-pierre.gauthier@rennes.infra.fr|INRA, Agrocampus Rennes, UMR 1099 BiO3P (Biology of Organisms and Populations applied to Plant Protection), F-35653 LE RHEU, France. jean-pierre.gauthier@rennes.infra.fr|INRA, Agrocampus Rennes, UMR 1099 BiO3P (Biology of Organisms and Populations applied to Plant Protection), F-35653 LE RHEU, France. jean-pierre.gauthier@rennes.infra.fr', 'France|France|France|France|France', 26, 'Animals|Aphids|Chromosome Mapping|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btl682', '17237053', 'AphidBase aims to (i) store recently acquired genomic resources on aphids and (ii) compare them to other insect resources as functional annotation tools. For that, the Drosophila melanogaster genome has been loaded in the database using the GMOD open source software for a comparison with the 17 069 pea aphid unique transcripts (contigs) and the 13 639 gene transcripts of the Anopheles gambiae. Links to FlyBase and A.gambiae Entrez databases allow a rapid characterization of the putative functions of the aphid sequences. Text mining of the D.melanogaster literature was performed to construct a network of co-cited gene or protein names, which should facilitate functional annotation of aphid homolog sequences. AphidBase represents one of the first genomic databases for a hemipteran insect.'),
(73229, 2007, 'bio', 'The Treeterbi and Parallel Treeterbi algorithms: efficient, optimal decoding for ordinary, generalized and pair HMMs', 'Keibler, Evan|Arumugam, Manimozhiyan|Brent, Michael R', 'Laboratory for Computational Genomics, Campus Box 1045, Washington University, St. Louis, MO 63130, USA.|Laboratory for Computational Genomics, Campus Box 1045, Washington University, St. Louis, MO 63130, USA.|Laboratory for Computational Genomics, Campus Box 1045, Washington University, St. Louis, MO 63130, USA.', 'United States|United States|United States', 7, 'Algorithms|Chromosomes, Human|Computational Biology|DNA, Complementary|Genes|Genomics|Humans|Markov Chains|Programming Languages', 'Journal Article', '10.1093/bioinformatics/btl659', '17237054', 'Hidden Markov models (HMMs) and generalized HMMs been successfully applied to many problems, but the standard Viterbi algorithm for computing the most probable interpretation of an input sequence (known as decoding) requires memory proportional to the length of the sequence, which can be prohibitive. Existing approaches to reducing memory usage either sacrifice optimality or trade increased running time for reduced memory.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73230, 2007, 'bio', 'SMotif: a server for structural motifs in proteins', 'Pugalenthi, Ganesan|Suganthan, P N|Sowdhamini, R|Chakrabarti, Saikat', 'School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798.|School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798.|School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798.|School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798.', 'Singapore|Singapore|Singapore|Singapore', 13, 'Amino Acid Motifs|Conserved Sequence|Databases, Protein|Hydrogen Bonding|Internet|Protein Folding|Protein Structure, Secondary|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl679', '17237055', 'SMotif is a server that identifies important structural segments or motifs for a given protein structure(s) based on conservation of both sequential as well as important structural features such as solvent inaccessibility, secondary structural content, hydrogen bonding pattern and residue packing. This server also provides three-dimensional orientation patterns of the identified motifs in terms of inter-motif distances and torsion angles. These motifs may form the common core and therefore, can also be employed to design and rationalize protein engineering and folding experiments.'),
(73231, 2007, 'bio', 'The ESID Online Database network', 'Guzman, D|Veit, D|Knerr, V|Kindle, G|Gathmann, B|Eades-Perner, A M|Grimbacher, B', 'Department of Rheumatology and Clinical Immunology, University Hospital Freiburg, Germany.|Department of Rheumatology and Clinical Immunology, University Hospital Freiburg, Germany.|Department of Rheumatology and Clinical Immunology, University Hospital Freiburg, Germany.|Department of Rheumatology and Clinical Immunology, University Hospital Freiburg, Germany.|Department of Rheumatology and Clinical Immunology, University Hospital Freiburg, Germany.|Department of Rheumatology and Clinical Immunology, University Hospital Freiburg, Germany.|Department of Rheumatology and Clinical Immunology, University Hospital Freiburg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 32, 'Database Management Systems|Databases, Factual|Humans|Immunologic Deficiency Syndromes|Information Storage and Retrieval|Internet|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl675', '17237056', 'Primary immunodeficiencies (PIDs) belong to the group of rare diseases. The European Society for Immunodeficiencies (ESID), is establishing an innovative European patient and research database network for continuous long-term documentation of patients, in order to improve the diagnosis, classification, prognosis and therapy of PIDs. The ESID Online Database is a web-based system aimed at data storage, data entry, reporting and the import of pre-existing data sources in an enterprise business-to-business integration (B2B). The online database is based on Java 2 Enterprise System (J2EE) with high-standard security features, which comply with data protection laws and the demands of a modern research platform.'),
(73232, 2007, 'bio', 'Quaternionic periodicity transform: an algebraic solution to the tandem repeat detection problem', 'Brodzik, Andrzej K', 'The MITRE Corporation, Bedford, MA 01730, USA.', 'United States', 21, 'Algorithms|Base Sequence|DNA|Molecular Sequence Data|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Tandem Repeat Sequences', 'Evaluation Studies', '10.1093/bioinformatics/btl674', '17237057', 'One of the main tasks of DNA sequence analysis is identification of repetitive patterns. DNA symbol repetitions play a key role in a number of applications, including prediction of gene and exon locations, identification of diseases, reconstruction of human evolutionary history and DNA forensics.'),
(73233, 2007, 'bio', 'Identifying clusters of functionally related genes in genomes', 'Yi, Gangman|Sze, Sing-Hoi|Thon, Michael R', 'Department of Computer Science, Texas A&M University, College Station, TX 77845, USA.|Department of Computer Science, Texas A&M University, College Station, TX 77845, USA.|Department of Computer Science, Texas A&M University, College Station, TX 77845, USA.', 'United States|United States|United States', 79, 'Algorithms|Chromosome Mapping|Cluster Analysis|Multigene Family|Proteome|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btl673', '17237058', 'An increasing body of literature shows that genomes of eukaryotes can contain clusters of functionally related genes. Most approaches to identify gene clusters utilize microarray data or metabolic pathway databases to find groups of genes on chromosomes that are linked by common attributes. A generalized method that can find gene clusters regardless of the mechanism of origin would provide researchers with an unbiased method for finding clusters and studying the evolutionary forces that give rise to them.'),
(73234, 2007, 'bio', 'Analysis of E coli promoter recognition problem in dinucleotide feature space', 'Rani, T Sobha|Bhavani, S Durga|Bapi, Raju S', 'Computational Intelligence Lab, Department of Computer and Information Sciences, University of Hyderabad, Hyderabad 500046, India. tsrcs@uohyd.ernet.in|Computational Intelligence Lab, Department of Computer and Information Sciences, University of Hyderabad, Hyderabad 500046, India. tsrcs@uohyd.ernet.in|Computational Intelligence Lab, Department of Computer and Information Sciences, University of Hyderabad, Hyderabad 500046, India. tsrcs@uohyd.ernet.in', 'India|India|India', 19, 'Animals|Computer Simulation|Drosophila|Escherichia coli|Nucleotides|Promoter Regions, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btl670', '17237059', 'Patterns in the promoter sequences within a species are known to be conserved but there exist many exceptions to this rule which makes the promoter recognition a complex problem. Although many complex feature extraction schemes coupled with several classifiers have been proposed for promoter recognition in the current literature, the problem is still open.'),
(73235, 2007, 'bio', 'Quick calculation for sample size while controlling false discovery rate with application to microarray analysis', 'Liu, Peng|Hwang, J T Gene', 'Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA. pliu@iastate.edu|Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA. pliu@iastate.edu', 'United States|United States', 0, 'Algorithms|Artifacts|Data Interpretation, Statistical|False Positive Reactions|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Software', 'Evaluation Studies', '10.1093/bioinformatics/btl664', '17237060', 'Sample size calculation is important in experimental design and is even more so in microarray or proteomic experiments since only a few repetitions can be afforded. In the multiple testing problems involving these experiments, it is more powerful and more reasonable to control false discovery rate (FDR) or positive FDR (pFDR) instead of type I error, e.g. family-wise error rate (FWER). When controlling FDR, the traditional approach of estimating sample size by controlling type I error is no longer applicable.'),
(73236, 2007, 'bio', 'Speeding up tandem mass spectrometry database search: metric embeddings and fast near neighbor search', 'Dutta, Debojyoti|Chen, Ting', 'Department of Computational Biology, University of Southern California, 1050 Childs Way, Los Angeles, CA 90089, USA.|Department of Computational Biology, University of Southern California, 1050 Childs Way, Los Angeles, CA 90089, USA.', 'United States|United States', 32, 'Algorithms|Amino Acid Sequence|Computational Biology|Databases, Protein|Models, Biological|Molecular Sequence Data|Peptide Mapping|Programming Languages|Proteins|Sequence Analysis, Protein|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btl645', '17237061', 'Due to the recent advances in technology of mass spectrometry, there has been an exponential increase in the amount of data being generated in the past few years. Database searches have not been able to keep with this data explosion. Thus, speeding up the data searches becomes increasingly important in mass-spectrometry-based applications. Traditional database search methods use one-against-all comparisons of a query spectrum against a very large number of peptides generated from in silico digestion of protein sequences in a database, to filter potential candidates from this database followed by a detailed scoring and ranking of those filtered candidates.'),
(73237, 2007, 'bio', 'Software package for automatic microarray image analysis (MAIA)', 'Novikov, Eugene|Barillot, Emmanuel', 'Service Bioinformatique, Institut Curie, 75248 Paris Cedex 05, France. eugene.novikov@curie.fr|Service Bioinformatique, Institut Curie, 75248 Paris Cedex 05, France. eugene.novikov@curie.fr', 'France|France', 15, 'Algorithms|Computer Graphics|Image Processing, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Protein Array Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btl644', '17237062', 'Although various software solutions are currently available for microarray image analysis, one would still expect to develop algorithms ensuring higher level of intelligence and robustness. We present a fully functional software package for automatic processing of the two-color microarray images including spot localization, quantification and quality control. The developed algorithms aim at making ratio estimates more resistant to array contamination and offer automatic tools to evaluate spot quality.'),
(73238, 2007, 'bio', 'Compressed suffix tree--a basis for genome-scale sequence analysis', 'Välimäki, Niko|Gerlach, Wolfgang|Dixit, Kashyap|Mäkinen, Veli', 'Department of Computer Science, P.O. Box 68 (Gustaf Hällströmin katu 2b), FI-00014 University of Helsinki, Finland.|Department of Computer Science, P.O. Box 68 (Gustaf Hällströmin katu 2b), FI-00014 University of Helsinki, Finland.|Department of Computer Science, P.O. Box 68 (Gustaf Hällströmin katu 2b), FI-00014 University of Helsinki, Finland.|Department of Computer Science, P.O. Box 68 (Gustaf Hällströmin katu 2b), FI-00014 University of Helsinki, Finland.', 'Finland|Finland|Finland|Finland', 0, 'Algorithms|Computational Biology|DNA|Genomics|Programming Languages|Software', 'Comparative Study', '10.1093/bioinformatics/btl681', '17237063', 'Suffix tree is one of the most fundamental data structures in string algorithms and biological sequence analysis. Unfortunately, when it comes to implementing those algorithms and applying them to real genomic sequences, often the main memory size becomes the bottleneck. This is easily explained by the fact that while a DNA sequence of length n from alphabet sigma = {A, C, G, T} can be stored in n log absolute value(sigma) = 2n bits, its suffix tree occupies O(n log n) bits. In practice, the size difference easily reaches factor 50. We provide an implementation of the compressed suffix tree very recently proposed by Sadakane (Theory of Computing Systems, in press). The compressed suffix tree occupies space proportional to the text size, i.e. O(n log) absolute value(sigma)) bits, and supports all typical suffix tree operations with at most log n factor slowdown. Our experiments show that, e.g. on a 10 MB DNA sequence, the compressed suffix tree takes 10% of the space of normal suffix tree. Typical operations are slowed down by factor 60.'),
(73239, 2007, 'bio', 'Automatic recognition and annotation of gene expression patterns of fly embryos', 'Zhou, Jie|Peng, Hanchuan', 'Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. jzhou@cs.niu.edu|Department of Computer Science, Northern Illinois University, DeKalb, IL 60115, USA. jzhou@cs.niu.edu', 'United States|United States', 54, 'Algorithms|Animals|Computational Biology|Drosophila|Embryo, Nonmammalian|Gene Expression|In Situ Hybridization|RNA, Messenger', 'Comparative Study', '10.1093/bioinformatics/btl680', '17237064', 'Gene expression patterns obtained by in situ mRNA hybridization provide important information about different genes during Drosophila embryogenesis. So far, annotations of these images are done by manually assigning a subset of anatomy ontology terms to an image. This time-consuming process depends heavily on the consistency of experts.'),
(73240, 2007, 'bio', 'Peak selection from MALDI-TOF mass spectra using ant colony optimization', 'Ressom, H W|Varghese, R S|Drake, S K|Hortin, G L|Abdel-Hamid, M|Loffredo, C A|Goldman, R', 'Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA. hwr@georgetown.edu|Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA. hwr@georgetown.edu|Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA. hwr@georgetown.edu|Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA. hwr@georgetown.edu|Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA. hwr@georgetown.edu|Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA. hwr@georgetown.edu|Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA. hwr@georgetown.edu', 'United States|United States|United States|United States|United States|United States|United States', 86, 'Algorithms|Biomarkers, Tumor|Carcinoma, Hepatocellular|Computational Biology|Humans|Liver Cirrhosis|Liver Neoplasms|Models, Biological|Molecular Weight|Peptides|Proteomics|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Comparative Study', '10.1093/bioinformatics/btl678', '17237065', 'Due to the large number of peaks in mass spectra of low-molecular-weight (LMW) enriched sera, a systematic method is needed to select a parsimonious set of peaks to facilitate biomarker identification. We present computational methods for matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) spectral data preprocessing and peak selection. In particular, we propose a novel method that combines ant colony optimization (ACO) with support vector machines (SVM) to select a small set of useful peaks.'),
(73241, 2007, 'bio', 'Improving the accuracy of transmembrane protein topology prediction using evolutionary information', 'Jones, David T', 'Department of Computer Science, University College London, Gower Street, London WC1E 6BT, United Kingdom. dtj@cs.ucl.ac.uk', 'United Kingdom', 0, 'Algorithms|Computational Biology|Evolution, Molecular|Membrane Proteins|Protein Conformation|Reproducibility of Results|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btl677', '17237066', 'Many important biological processes such as cell signaling, transport of membrane-impermeable molecules, cell-cell communication, cell recognition and cell adhesion are mediated by membrane proteins. Unfortunately, as these proteins are not water soluble, it is extremely hard to experimentally determine their structure. Therefore, improved methods for predicting the structure of these proteins are vital in biological research. In order to improve transmembrane topology prediction, we evaluate the combined use of both integrated signal peptide prediction and evolutionary information in a single algorithm.'),
(73242, 2007, 'bio', 'Inferring pairwise regulatory relationships from multiple time series datasets', 'Shi, Yanxin|Mitchell, Tom|Bar-Joseph, Ziv', 'Machine Learning Department, Language Technologies Institute, Computer Science Department and Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA.|Machine Learning Department, Language Technologies Institute, Computer Science Department and Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA.|Machine Learning Department, Language Technologies Institute, Computer Science Department and Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA.', 'United States|United States|United States', 24, 'Algorithms|Computer Simulation|Databases, Factual|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Proteome', 'Evaluation Studies', '10.1093/bioinformatics/btl676', '17237067', 'Time series expression experiments have emerged as a popular method for studying a wide range of biological systems under a variety of conditions. One advantage of such data is the ability to infer regulatory relationships using time lag analysis. However, such analysis in a single experiment may result in many false positives due to the small number of time points and the large number of genes. Extending these methods to simultaneously analyze several time series datasets is challenging since under different experimental conditions biological systems may behave faster or slower making it hard to rely on the actual duration of the experiment.'),
(73243, 2007, 'bio', 'DP-Bind: a web server for sequence-based prediction of DNA-binding residues in DNA-binding proteins', 'Hwang, Seungwoo|Gou, Zhenkun|Kuznetsov, Igor B', 'Gen*NY*Sis Center for Excellence in Cancer Genomics, Department of Epidemiology and Biostatistics, One Discovery Drive, University at Albany, Rensselaer, NY 12144, USA.|Gen*NY*Sis Center for Excellence in Cancer Genomics, Department of Epidemiology and Biostatistics, One Discovery Drive, University at Albany, Rensselaer, NY 12144, USA.|Gen*NY*Sis Center for Excellence in Cancer Genomics, Department of Epidemiology and Biostatistics, One Discovery Drive, University at Albany, Rensselaer, NY 12144, USA.', 'United States|United States|United States', 0, 'Artificial Intelligence|Base Sequence|Binding Sites|Computational Biology|Computers|DNA-Binding Proteins|Internet|Logistic Models|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btl672', '17237068', 'This article describes DP-Bind, a web server for predicting DNA-binding sites in a DNA-binding protein from its amino acid sequence. The web server implements three machine learning methods: support vector machine, kernel logistic regression and penalized logistic regression. Prediction can be performed using either the input sequence alone or an automatically generated profile of evolutionary conservation of the input sequence in the form of PSI-BLAST position-specific scoring matrix (PSSM). PSSM-based kernel logistic regression achieves the accuracy of 77.2%, sensitivity of 76.4% and specificity of 76.6%. The outputs of all three individual methods are combined into a consensus prediction to help identify positions predicted with high level of confidence.'),
(73244, 2007, 'bio', 'BioWeka--extending the Weka framework for bioinformatics', 'Gewehr, Jan E|Szugat, Martin|Zimmer, Ralf', 'Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University Munich, Amalienstrasse 17, D-80333 Munich, Germany.|Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University Munich, Amalienstrasse 17, D-80333 Munich, Germany.|Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University Munich, Amalienstrasse 17, D-80333 Munich, Germany.', 'Germany|Germany|Germany', 36, 'Algorithms|Computational Biology|Databases, Factual|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl671', '17237069', 'Given the growing amount of biological data, data mining methods have become an integral part of bioinformatics research. Unfortunately, standard data mining tools are often not sufficiently equipped for handling raw data such as e.g. amino acid sequences. One popular and freely available framework that contains many well-known data mining algorithms is the Waikato Environment for Knowledge Analysis (Weka). In the BioWeka project, we introduce various input formats for bioinformatics data and bioinformatics methods like alignments to Weka. This allows users to easily combine them with Wekas classification, clustering, validation and visualization facilities on a single platform and therefore reduces the overhead of converting data between different data formats as well as the need to write custom evaluation procedures that can deal with many different programs. We encourage users to participate in this project by adding their own components and data formats to BioWeka.'),
(73245, 2007, 'bio', 'An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences', 'Ye, Kai|Kosters, Walter A|Ijzerman, Adriaan P', 'Division of Medicinal Chemistry, Leiden/Amsterdam Center for Drug Research and Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands. k.ye@lacdr.leidenuniv.nl|Division of Medicinal Chemistry, Leiden/Amsterdam Center for Drug Research and Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands. k.ye@lacdr.leidenuniv.nl|Division of Medicinal Chemistry, Leiden/Amsterdam Center for Drug Research and Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands. k.ye@lacdr.leidenuniv.nl', 'Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/btl665', '17237070', 'Pattern discovery in protein sequences is often based on multiple sequence alignments (MSA). The procedure can be computationally intensive and often requires manual adjustment, which may be particularly difficult for a set of deviating sequences. In contrast, two algorithms, PRATT2 (http//www.ebi.ac.uk/pratt/) and TEIRESIAS (http://cbcsrv.watson.ibm.com/) are used to directly identify frequent patterns from unaligned biological sequences without an attempt to align them. Here we propose a new algorithm with more efficiency and more functionality than both PRATT2 and TEIRESIAS, and discuss some of its applications to G protein-coupled receptors, a protein family of important drug targets.'),
(73246, 2007, 'bio', 'SBaddon: high performance simulation for the Systems Biology Toolbox for MATLAB', 'Schmidt, Henning', 'Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-41288 Göteborg. henning@fcc.chalmers.se', '-', 25, 'Algorithms|Computer Simulation|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btl668', '17237071', 'We present the SBaddon package as an extension to the Systems Biology Toolbox for MATLAB (SBtoolbox). The goal of this extension is to provide the users of the SBtoolbox with important functionality that is needed for parameter estimation applications. While simulation in the SBtoolbox relies on the MATLAB ODE solvers, the SBaddon package provides considerably increased simulation performance through automatic generation of compiled simulation functions. Furthermore, the package contains improved optimization algorithms, forward parameter sensitivity analysis and basic numeric parameter identifiability analysis.'),
(73247, 2007, 'bio', 'Biskit--a software platform for structural bioinformatics', 'Grünberg, Raik|Nilges, Michael|Leckner, Johan', 'CRG, Systems Biology program, Dr Aiguader 88, E-08003 Barcelona, Spain. raik.gruenberg@crg.es|CRG, Systems Biology program, Dr Aiguader 88, E-08003 Barcelona, Spain. raik.gruenberg@crg.es|CRG, Systems Biology program, Dr Aiguader 88, E-08003 Barcelona, Spain. raik.gruenberg@crg.es', 'Spain|Spain|Spain', 0, 'Computational Biology|Computer Graphics|Computer Simulation|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Programming Languages|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl655', '17237072', 'Biskit is a modular, object-oriented python library that provides intuitive classes for many typical tasks of structural bioinformatics research. It facilitates the manipulation and analysis of macromolecular structures, protein complexes and molecular dynamics trajectories. At the same time, Biskit offers a software platform for the rapid integration of external programs and new algorithms into complex structural bioinformatics workflows. Calculations are thus often delegated to established programs like Xplor, Amber, Hex, Prosa, Hmmer and Modeller, interfaces to further software can be easily added. Moreover, Biskit simplifies the parallelization of time consuming calculations via PVM (Parallel Virtual Machine).'),
(73248, 2007, 'bio', 'ProServer: a simple, extensible Perl DAS server', 'Finn, Robert D|Stalker, James W|Jackson, David K|Kulesha, Eugene|Clements, Jody|Pettett, Roger', 'Wellcome Trust Sanger Institute, Wellcome Trust Geome Campus, Hinxton, Cambridge, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Geome Campus, Hinxton, Cambridge, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Geome Campus, Hinxton, Cambridge, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Geome Campus, Hinxton, Cambridge, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Geome Campus, Hinxton, Cambridge, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Geome Campus, Hinxton, Cambridge, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 27, 'Computational Biology|Computer Communication Networks|Databases, Genetic|Genome, Human|Humans|Internet|Programming Languages|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btl650', '17237073', 'The increasing size and complexity of biological databases has led to a growing trend to federate rather than duplicate them. In order to share data between federated databases, protocols for the exchange mechanism must be developed. One such data exchange protocol that is widely used is the Distributed Annotation System (DAS). For example, DAS has enabled small experimental groups to integrate their data into the Ensembl genome browser. We have developed ProServer, a simple, lightweight, Perl-based DAS server that does not depend on a separate HTTP server. The ProServer package is easily extensible, allowing data to be served from almost any underlying data model. Recent additions to the DAS protocol have enabled both structure and alignment (sequence and structural) data to be exchanged. ProServer allows both of these data types to be served.'),
(73249, 2007, 'bio', 'DataBiNS: a BioMoby-based data-mining workflow for biological pathways and non-synonymous SNPs', 'Song, Young C|Kawas, Edward|Good, Ben M|Wilkinson, Mark D|Tebbutt, Scott J', 'James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St. Pauls Hospital, University of British Columbia, Vancouver, V6Z 1Y6, Canada.|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St. Pauls Hospital, University of British Columbia, Vancouver, V6Z 1Y6, Canada.|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St. Pauls Hospital, University of British Columbia, Vancouver, V6Z 1Y6, Canada.|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St. Pauls Hospital, University of British Columbia, Vancouver, V6Z 1Y6, Canada.|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St. Pauls Hospital, University of British Columbia, Vancouver, V6Z 1Y6, Canada.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Polymorphism, Single Nucleotide|Proteins|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl648', '17237074', 'DataBiNS is a custom-designed BioMoby Web Service workflow that integrates non-synonymous coding single nucleotide polymorphisms (nsSNPs) data with structure/function and pathway data for the relevant protein. A KEGG Pathway Identifier representing a specific human biological pathway initializes the DataBiNS workflow. The workflow retrieves a list of publications, gene ontology annotations and nsSNP information for each gene involved in the biological pathway. Manual inspection of output data from several trial runs confirms that all expected information is appropriately retrieved by the workflow services. The use of an automated BioMoby workflow, rather than manual surfing, to retrieve the necessary data, significantly reduces the effort required for functional interpretation of SNP data, and thus encourages more speculative investigation. Moreover, the modular nature of the individual BioMoby Services enables fine-grained reusing of each service in other workflows, thus reducing the effort required to achieve similar investigations in the future.'),
(73250, 2007, 'bio', 'ECCB 2006', 'Wolfson, Haim|Safer, Hershel', 'James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St. Pauls Hospital, University of British Columbia, Vancouver, V6Z 1Y6, Canada.|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St. Pauls Hospital, University of British Columbia, Vancouver, V6Z 1Y6, Canada.', 'Canada|Canada', 2, 'Computational Biology|Genomics|Molecular Biology', 'Congress', '10.1093/bioinformatics/btl631', '17237075', '-'),
(73251, 2007, 'bio', 'Analysis of binding site similarity, small-molecule similarity and experimental binding profiles in the human cytosolic sulfotransferase family', 'Najmanovich, Rafael J|Allali-Hassani, Abdellah|Morris, Richard J|Dombrovsky, Ludmila|Pan, Patricia W|Vedadi, Masoud|Plotnikov, Alexander N|Edwards, Aled|Arrowsmith, Cheryl|Thornton, Janet M', 'European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus Cambridge CB10 1SD, UK. rafael.najmanovich@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Binding Sites|Computer Simulation|Humans|Models, Chemical|Models, Molecular|Protein Binding|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Sulfotransferases', 'Journal Article', '10.1093/bioinformatics/btl292', '17237076', 'In the present work we combine computational analysis and experimental data to explore the extent to which binding site similarities between members of the human cytosolic sulfotransferase family correlate with small-molecule binding profiles. Conversely, from a small-molecule point of view, we explore the extent to which structural similarities between small molecules correlate to protein binding profiles.'),
(73252, 2007, 'bio', 'Phylogenetic reconstruction from non-genomic data', 'Clemente, José C|Satou, Kenji|Valiente, Gabriel', 'School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi Ishikawa 923-1292, Japan. clemente@jaist.ac.jp|School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi Ishikawa 923-1292, Japan. clemente@jaist.ac.jp|School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi Ishikawa 923-1292, Japan. clemente@jaist.ac.jp', 'Japan|Japan|Japan', 24, 'Algorithms|Chromosome Mapping|Computer Simulation|Databases, Factual|Evolution, Molecular|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Multienzyme Complexes|Phylogeny|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btl307', '17237077', 'Recent results related to horizontal gene transfer suggest that phylogenetic reconstruction cannot be determined conclusively from sequence data, resulting in a shift from approaches based on polymorphism information in DNA or protein sequence to studies aimed at understanding the evolution of complete biological processes. The increasing amount of available information on metabolic pathways for several species makes it of greater relevance to understand the similarities and differences among such pathways. These similarities can then be used to infer phylogenetic trees not based exclusively in sequence data, therefore avoiding the previously mentioned problems.'),
(73253, 2007, 'bio', 'Inferring phylogeny from whole genomes', 'Gxc3xb3recki, Pawexc5x82|Tiuryn, Jerzy', 'Institute of Informatics, Warsaw University Banacha 2, 02-678 Warsaw, Poland. gorecki@mimuw.edu.pl|Institute of Informatics, Warsaw University Banacha 2, 02-678 Warsaw, Poland. gorecki@mimuw.edu.pl', 'Poland|Poland', 25, 'Algorithms|Chromosome Mapping|Conserved Sequence|Evolution, Molecular|Genome, Fungal|Phylogeny|Proteome|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btl296', '17237078', 'Inferring species phylogenies with a history of gene losses and duplications is a challenging and an important task in computational biology. This problem can be solved by duplication-loss models in which the primary step is to reconcile a rooted gene tree with a rooted species tree. Most modern methods of phylogenetic reconstruction (from sequences) produce unrooted gene trees. This limitation leads to the problem of transforming unrooted gene tree into a rooted tree, and then reconciling rooted trees. The main questions are What about biological interpretation of choosing rooting?, Can we find efficiently the optimal rootings?, Is the optimal rooting unique?.'),
(73254, 2007, 'bio', 'Efficient parsimony-based methods for phylogenetic network reconstruction', 'Jin, Guohua|Nakhleh, Luay|Snir, Sagi|Tuller, Tamir', 'Department of Computer Science, Rice University, Houston, TX, USA.|Department of Computer Science, Rice University, Houston, TX, USA.|Department of Computer Science, Rice University, Houston, TX, USA.|Department of Computer Science, Rice University, Houston, TX, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Evolution, Molecular|Molecular Sequence Data|Phylogeny|Proteome|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btl313', '17237079', 'Phylogenies--the evolutionary histories of groups of organisms-play a major role in representing relationships among biological entities. Although many biological processes can be effectively modeled as tree-like relationships, others, such as hybrid speciation and horizontal gene transfer (HGT), result in networks, rather than trees, of relationships. Hybrid speciation is a significant evolutionary mechanism in plants, fish and other groups of species. HGT plays a major role in bacterial genome diversification and is a significant mechanism by which bacteria develop resistance to antibiotics. Maximum parsimony is one of the most commonly used criteria for phylogenetic tree inference. Roughly speaking, inference based on this criterion seeks the tree that minimizes the amount of evolution. In 1990, Jotun Hein proposed using this criterion for inferring the evolution of sequences subject to recombination. Preliminary results on small synthetic datasets. Nakhleh et al. (2005) demonstrated the criterions application to phylogenetic network reconstruction in general and HGT detection in particular. However, the naive algorithms used by the authors are inapplicable to large datasets due to their demanding computational requirements. Further, no rigorous theoretical analysis of computing the criterion was given, nor was it tested on biological data.'),
(73255, 2007, 'bio', 'Using median sets for inferring phylogenetic trees', 'Bernt, Matthias|Merkle, Daniel|Middendorf, Martin', 'Parallel Computing and Complex Systems Group, Department of Computer Science, University of Leipzig Augustusplatz 10/11, 04109 Leipzig, Germany.|Parallel Computing and Complex Systems Group, Department of Computer Science, University of Leipzig Augustusplatz 10/11, 04109 Leipzig, Germany.|Parallel Computing and Complex Systems Group, Department of Computer Science, University of Leipzig Augustusplatz 10/11, 04109 Leipzig, Germany.', 'Germany|Germany|Germany', 14, 'Algorithms|Chromosome Mapping|Conserved Sequence|Databases, Genetic|Evolution, Molecular|Gene Rearrangement|Genome|Linkage Disequilibrium|Phylogeny|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1093/bioinformatics/btl300', '17237080', 'Algorithms for phylogenetic tree reconstruction based on gene order data typically repeatedly solve instances of the reversal median problem (RMP) which is to find for three given gene orders a fourth gene order (called median) with a minimal sum of reversal distances. All existing algorithms of this type consider only one median for each RMP instance even when a large number of medians exist. A careful selection of one of the medians might lead to better phylogenetic trees.'),
(73256, 2007, 'bio', 'ISIS: interaction sites identified from sequence', 'Ofran, Yanay|Rost, Burkhard', 'CUBIC & North-East Structural Genomics Consortium, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. yanay.ofran@columbia.edu|CUBIC & North-East Structural Genomics Consortium, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY 10032, USA. yanay.ofran@columbia.edu', 'United States|United States', 0, 'Amino Acids|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Pattern Recognition, Automated|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btl303', '17237081', 'Large-scale experiments reveal pairs of interacting proteins but leave the residues involved in the interactions unknown. These interface residues are essential for understanding the mechanism of interaction and are often desired drug targets. Reliable identification of residues that reside in protein-protein interface typically requires analysis of protein structure. Therefore, for the vast majority of proteins, for which there is no high-resolution structure, there is no effective way of identifying interface residues.'),
(73257, 2007, 'bio', 'Phylogeny reconstruction: increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates', 'Ninio, Matan|Privman, Eyal|Pupko, Tal|Friedman, Nir', 'The Selim and Rachel Benin School of Computer Science and Engineering, Hebrew University Jerusalem 91904, Israel.|The Selim and Rachel Benin School of Computer Science and Engineering, Hebrew University Jerusalem 91904, Israel.|The Selim and Rachel Benin School of Computer Science and Engineering, Hebrew University Jerusalem 91904, Israel.|The Selim and Rachel Benin School of Computer Science and Engineering, Hebrew University Jerusalem 91904, Israel.', 'Benin|Benin|Benin|Benin', 9, 'Algorithms|Base Pair Mismatch|Bayes Theorem|Conserved Sequence|Evolution, Molecular|Linkage Disequilibrium|Phylogeny|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btl304', '17237082', 'Distance-based methods for phylogeny reconstruction are the fastest and easiest to use, and their popularity is accordingly high. They are also the only known methods that can cope with huge datasets of thousands of sequences. These methods rely on evolutionary distance estimation and are sensitive to errors in such estimations. In this study, a novel Bayesian method for estimation of evolutionary distances is developed. The proposed method enables the use of a sophisticated evolutionary model that better accounts for among-site rate variation (ASRV), thereby improving the accuracy of distance estimation. Rate variations are estimated within a Bayesian framework by extracting information from the entire dataset of sequences, unlike standard methods that can only use one pair of sequences at a time. We compare the accuracy of a cascade of distance estimation methods, starting from commonly used methods and moving towards the more sophisticated novel method. Simulation studies show significant improvements in the accuracy of distance estimation by the novel method over the commonly used ones. We demonstrate the effect of the improved accuracy on tree reconstruction using both real and simulated protein sequence alignments. An implementation of this method is available as part of the SEMPHY package.'),
(73258, 2007, 'bio', 'Efficient inference on known phylogenetic trees using Poisson regression', 'Rosset, Saharon', 'IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA. srosset@us.ibm.com', 'United States', 5, 'Base Sequence|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|DNA, Mitochondrial|Data Interpretation, Statistical|Evolution, Molecular|Models, Genetic|Models, Statistical|Molecular Sequence Data|Phylogeny|Poisson Distribution|Regression Analysis|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btl306', '17237083', 'We suggest the use of Poisson regression for time inference and hypothesis testing on a bifurcating Phylogenetic tree with known topology. This method is computationally simple and naturally accommodates variable substitution rates across different sites, without requiring the estimation of these rates. We identify the assumptions under which this is a maximum-likelihood inference approach and show that in some realistic situations--in particular, when the probability of repeated mutation within each branch of the tree is small--these assumptions hold with high probability.'),
(73259, 2007, 'bio', 'Identifying HLA supertypes by learning distance functions', 'Hertz, Tomer|Yanover, Chen', 'School of Computer Science and Engineering, Israel. tomboy@cs.huji.ac.il|School of Computer Science and Engineering, Israel. tomboy@cs.huji.ac.il', 'Israel|Israel', 28, 'Alleles|Artificial Intelligence|Binding Sites|Computer Simulation|Epitope Mapping|Histocompatibility Antigens Class I|Models, Chemical|Models, Immunological|Multigene Family|Protein Binding|Protein Interaction Mapping|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/Bioinformatics/btl324', '17237084', 'The development of epitope-based vaccines crucially relies on the ability to classify Human Leukocyte Antigen (HLA) molecules into sets that have similar peptide binding specificities, termed supertypes. In their seminal work, Sette and Sidney defined nine HLA class I supertypes and claimed that these provide an almost perfect coverage of the entire repertoire of HLA class I molecules. HLA alleles are highly polymorphic and polygenic and therefore experimentally classifying each of these molecules to supertypes is at present an impossible task. Recently, a number of computational methods have been proposed for this task. These methods are based on defining protein similarity measures, derived from analysis of binding peptides or from analysis of the proteins themselves.'),
(73260, 2007, 'bio', 'Learning probabilistic models of cis-regulatory modules that represent logical and spatial aspects', 'Noto, Keith|Craven, Mark', 'Department of Computer Sciences and Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI 53706, USA. noto@cs.wisc.edu|Department of Computer Sciences and Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI 53706, USA. noto@cs.wisc.edu', 'United States|United States', 8, 'Algorithms|Artificial Intelligence|Base Sequence|Chromosome Mapping|Computer Simulation|Genome, Fungal|Models, Genetic|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Regulatory Elements, Transcriptional|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btl319', '17237085', 'The process of transcription is controlled by systems of factors which bind in specific arrangements, called cis-regulatory modules (CRMs), in promoter regions. We present a discriminative learning algorithm which simultaneously learns the DNA binding site motifs as well as the logical structure and spatial aspects of CRMs.'),
(73261, 2007, 'bio', 'Rediscovering secondary structures as network motifs--an unsupervised learning approach', 'Raveh, Barak|Rahat, Ofer|Basri, Ronen|Schreiber, Gideon', 'Department of Computer Science & Applied Mathematics, Weizmann Institute of Science, Rehovot, 76100, Israel. barak.raveh@weizmann.ac.il|Department of Computer Science & Applied Mathematics, Weizmann Institute of Science, Rehovot, 76100, Israel. barak.raveh@weizmann.ac.il|Department of Computer Science & Applied Mathematics, Weizmann Institute of Science, Rehovot, 76100, Israel. barak.raveh@weizmann.ac.il|Department of Computer Science & Applied Mathematics, Weizmann Institute of Science, Rehovot, 76100, Israel. barak.raveh@weizmann.ac.il', 'Israel|Israel|Israel|Israel', 5, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btl290', '17237086', 'Secondary structures are key descriptors of a protein fold and its topology. In recent years, they facilitated intensive computational tasks for finding structural homologues, fold prediction and protein design. Their popularity stems from an appealing regularity in patterns of geometry and chemistry. However, the definition of secondary structures is of subjective nature. An unsupervised de-novo discovery of these structures would shed light on their nature, and improve the way we use these structures in algorithms of structural bioinformatics.'),
(73262, 2007, 'bio', 'Incremental window-based protein sequence alignment algorithms', 'Rangwala, Huzefa|Karypis, George', 'Department of Computer Science & Engineering, University of Minnesota Minneapolis, MN 55455, USA. rangwala@cs.umn.edu|Department of Computer Science & Engineering, University of Minnesota Minneapolis, MN 55455, USA. rangwala@cs.umn.edu', 'United States|United States', 3, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btl297', '17237087', 'Protein sequence alignment plays a critical role in computational biology as it is an integral part in many analysis tasks designed to solve problems in comparative genomics, structure and function prediction, and homology modeling.'),
(73263, 2007, 'bio', 'Identification of conserved protein complexes based on a model of protein network evolution', 'Hirsh, Eitan|Sharan, Roded', 'School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.', 'Israel|Israel', 74, 'Algorithms|Computer Simulation|Conserved Sequence|DNA Mutational Analysis|Evolution, Molecular|Models, Genetic|Phylogeny|Protein Interaction Mapping|Proteins|Sequence Analysis, DNA|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btl295', '17237088', 'Data on protein-protein interactions (PPIs) are increasing exponentially. To date, large-scale protein interaction networks are available for human and most model species. The arising challenge is to organize these networks into models of cellular machinery. As in other biological domains, a comparative approach provides a powerful basis for addressing this challenge.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73264, 2007, 'bio', 'Biological network comparison using graphlet degree distribution', 'Przulj, Natasa', 'Computer Science Department, University of California, Irvine, CA 92697-3425, USA. natasha@ics.uci.edu', 'United States', 395, 'Computer Graphics|Computer Simulation|Models, Biological|Proteome|Signal Transduction|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btl301', '17237089', 'Analogous to biological sequence comparison, comparing cellular networks is an important problem that could provide insight into biological understanding and therapeutics. For technical reasons, comparing large networks is computationally infeasible, and thus heuristics, such as the degree distribution, clustering coefficient, diameter, and relative graphlet frequency distribution have been sought. It is easy to demonstrate that two networks are different by simply showing a short list of properties in which they differ. It is much harder to show that two networks are similar, as it requires demonstrating their similarity in all of their exponentially many properties. Clearly, it is computationally prohibitive to analyze all network properties, but the larger the number of constraints we impose in determining network similarity, the more likely it is that the networks will truly be similar.'),
(73265, 2007, 'bio', 'Similarities and differences of gene expression in yeast stress conditions', 'Rokhlenko, Oleg|Wexler, Ydo|Yakhini, Zohar', 'Technion-Israel Institute of Technology, Department of Computer Science, Haifa 32000, Israel. olegro@cs.technion.ac.il|Technion-Israel Institute of Technology, Department of Computer Science, Haifa 32000, Israel. olegro@cs.technion.ac.il|Technion-Israel Institute of Technology, Department of Computer Science, Haifa 32000, Israel. olegro@cs.technion.ac.il', 'Israel|Israel|Israel', 20, 'Computer Simulation|Gene Expression|Gene Expression Regulation, Fungal|Heat-Shock Proteins|Heat-Shock Response|Models, Biological|Oxidative Stress|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btl308', '17237090', 'MOTIVATION AND METHODS: All living organisms and the survival of all cells critically depend on their ability to sense and quickly adapt to changes in the environment and to other stress conditions. We study stress response mechanisms in Saccharomyces cerevisiae by identifying genes that, according to very stringent criteria, have persistent co-expression under a variety of stress conditions. This is enabled through a fast clique search method applied to the intersection of several co-expression graphs calculated over the data of Gasch et al. This method exploits the topological characteristics of these graphs.'),
(73266, 2007, 'bio', 'TOPP--the OpenMS proteomics pipeline', 'Kohlbacher, Oliver|Reinert, Knut|Gröpl, Clemens|Lange, Eva|Pfeifer, Nico|Schulz-Trieglaff, Ole|Sturm, Marc', 'Simulation of Biological Systems, Eberhard Karls University Tübingen Sand 14, 72076 Tübingen, Germany. oliver.kohlbacher@uni-tuebingen.de|Simulation of Biological Systems, Eberhard Karls University Tübingen Sand 14, 72076 Tübingen, Germany. oliver.kohlbacher@uni-tuebingen.de|Simulation of Biological Systems, Eberhard Karls University Tübingen Sand 14, 72076 Tübingen, Germany. oliver.kohlbacher@uni-tuebingen.de|Simulation of Biological Systems, Eberhard Karls University Tübingen Sand 14, 72076 Tübingen, Germany. oliver.kohlbacher@uni-tuebingen.de|Simulation of Biological Systems, Eberhard Karls University Tübingen Sand 14, 72076 Tübingen, Germany. oliver.kohlbacher@uni-tuebingen.de|Simulation of Biological Systems, Eberhard Karls University Tübingen Sand 14, 72076 Tübingen, Germany. oliver.kohlbacher@uni-tuebingen.de|Simulation of Biological Systems, Eberhard Karls University Tübingen Sand 14, 72076 Tübingen, Germany. oliver.kohlbacher@uni-tuebingen.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 202, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Peptide Mapping|Programming Languages|Proteome|Proteomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btl299', '17237091', 'Experimental techniques in proteomics have seen rapid development over the last few years. Volume and complexity of the data have both been growing at a similar rate. Accordingly, data management and analysis are one of the major challenges in proteomics. Flexible algorithms are required to handle changing experimental setups and to assist in developing and validating new methods. In order to facilitate these studies, it would be desirable to have a flexible toolbox of versatile and user-friendly applications allowing for rapid construction of computational workflows in proteomics.'),
(73267, 2007, 'bio', 'Difference detection in LC-MS data for protein biomarker discovery', 'Listgarten, Jennifer|Neal, Radford M|Roweis, Sam T|Wong, Peter|Emili, Andrew', 'Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada. jenn@cs.toronto.edu|Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada. jenn@cs.toronto.edu|Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada. jenn@cs.toronto.edu|Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada. jenn@cs.toronto.edu|Department of Computer Science, University of Toronto, Toronto, Ontario M5S 3G4, Canada. jenn@cs.toronto.edu', 'Canada|Canada|Canada|Canada|Canada', 68, 'Algorithms|Biomarkers|Blood Proteins|Chromatography, Liquid|Mass Spectrometry|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btl326', '17237092', 'There is a pressing need for improved proteomic screening methods allowing for earlier diagnosis of disease, systematic monitoring of physiological responses and the uncovering of fundamental mechanisms of drug action. The combined platform of LC-MS (Liquid-Chromatography-Mass-Spectrometry) has shown promise in moving toward a solution in these areas. In this paper we present a technique for discovering differences in protein signal between two classes of samples of LC-MS serum proteomic data without use of tandem mass spectrometry, gels or labeling. This method works on data from a lower-precision MS instrument, the type routinely used by and available to the community at large today. We test our technique on a controlled (spike-in) but realistic (serum biomarker discovery) experiment which is therefore verifiable. We also develop a new method for helping to assess the difficulty of a given spike-in problem. Lastly, we show that the problem of class prediction, sometimes mistaken as a solution to biomarker discovery, is actually a much simpler problem.'),
(73268, 2007, 'bio', 'Vorolign--fast structural alignment using Voronoi contacts', 'Birzele, Fabian|Gewehr, Jan E|Csaba, Gergely|Zimmer, Ralf', 'Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University, Munich, Germany. fabian.birzele@ifi.lmu.de|Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University, Munich, Germany. fabian.birzele@ifi.lmu.de|Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University, Munich, Germany. fabian.birzele@ifi.lmu.de|Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University, Munich, Germany. fabian.birzele@ifi.lmu.de', 'Germany|Germany|Germany|Germany', 53, 'Algorithms|Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology', 'Evaluation Studies', '10.1093/bioinformatics/btl294', '17237093', 'Vorolign, a fast and flexible structural alignment method for two or more protein structures is introduced. The method aligns protein structures using double dynamic programming and measures the similarity of two residues based on the evolutionary conservation of their corresponding Voronoi-contacts in the protein structure. This similarity function allows aligning protein structures even in cases where structural flexibilities exist. Multiple structural alignments are generated from a set of pairwise alignments using a consistency-based, progressive multiple alignment strategy.'),
(73269, 2007, 'bio', 'Prediction and simulation of motion in pairs of transmembrane alpha-helices', 'Enosh, Angela|Fleishman, Sarel J|Ben-Tal, Nir|Halperin, Dan', 'School of Computer Science, Ramat Aviv 69978, Israel. angela@post.tau.ac.il|School of Computer Science, Ramat Aviv 69978, Israel. angela@post.tau.ac.il|School of Computer Science, Ramat Aviv 69978, Israel. angela@post.tau.ac.il|School of Computer Science, Ramat Aviv 69978, Israel. angela@post.tau.ac.il', 'Israel|Israel|Israel|Israel', 17, 'Algorithms|Cell Membrane|Computer Simulation|Kinetics|Membrane Proteins|Models, Chemical|Models, Molecular|Motion|Protein Conformation|Protein Structure, Secondary|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btl325', '17237094', 'Motion in transmembrane (TM) proteins plays an essential role in a variety of biological phenomena. Thus, developing an automated method for predicting and simulating motion in this class of proteins should result in an increased level of understanding of crucial physiological mechanisms. We have developed an algorithm for predicting and simulating motion in TM proteins of the alpha-helix bundle type. Our method employs probabilistic motion-planning techniques to suggest possible collision-free motion paths. The resulting paths are ranked according to the quality of the van der Waals interactions between the TM helices. Our algorithm considers a wide range of degrees of freedom (dofs) involved in the motion, including external and internal moves. However, in order to handle the vast dimensionality of the problem, we employ some constraints on these dofs in a way that is unlikely to rule out the native motion of the protein. Our algorithm simulates the motion, including all the dofs, and automatically produces a movie that demonstrates it.'),
(73270, 2007, 'bio', 'Using an alignment of fragment strings for comparing protein structures', 'Friedberg, Iddo|Harder, Tim|Kolodny, Rachel|Sitbon, Einat|Li, Zhanwen|Godzik, Adam', 'Program in Bioinformatics and Systems Biology, Burnham Institute for Medical Research, La Jolla, CA, USA. idoerg@burnham.org|Program in Bioinformatics and Systems Biology, Burnham Institute for Medical Research, La Jolla, CA, USA. idoerg@burnham.org|Program in Bioinformatics and Systems Biology, Burnham Institute for Medical Research, La Jolla, CA, USA. idoerg@burnham.org|Program in Bioinformatics and Systems Biology, Burnham Institute for Medical Research, La Jolla, CA, USA. idoerg@burnham.org|Program in Bioinformatics and Systems Biology, Burnham Institute for Medical Research, La Jolla, CA, USA. idoerg@burnham.org|Program in Bioinformatics and Systems Biology, Burnham Institute for Medical Research, La Jolla, CA, USA. idoerg@burnham.org', 'United States|United States|United States|United States|United States|United States', 34, 'Algorithms|Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Peptide Fragments|Peptide Mapping|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btl310', '17237095', 'Most methods that are used to compare protein structures use three-dimensional (3D) structural information. At the same time, it has been shown that a 1D string representation of local protein structure retains a degree of structural information. This type of representation can be a powerful tool for protein structure comparison and classification, given the arsenal of sequence comparison tools developed by computational biology. However, in order to do so, there is a need to first understand how much information is contained in various possible 1D representations of protein structure.'),
(73271, 2007, 'bio', 'A tale of two tails: why are terminal residues of proteins exposed?', 'Jacob, Etai|Unger, Ron', 'The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University Ramat-Gan, 52900, Israel.|The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University Ramat-Gan, 52900, Israel.', 'Israel|Israel', 67, 'Amino Acid Sequence|Amino Acids|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Analysis, Protein|Solvents|Structure-Activity Relationship|Surface Properties', 'Journal Article', '10.1093/bioinformatics/btl318', '17237096', 'It is widely known that terminal residues of proteins (i.e. the N- and C-termini) are predominantly located on the surface of proteins and exposed to the solvent. However, there is no good explanation as to the forces driving this phenomenon. The common explanation that terminal residues are charged, and charged residues prefer to be on the surface, cannot explain the magnitude of the phenomenon. Here, we survey a large number of proteins from the PDB in order to explore, quantitatively, this phenomenon, and then we use a lattice model to study the mechanisms involved.'),
(73272, 2007, 'bio', 'A novel pattern recognition algorithm to classify membrane protein unfolding pathways with high-throughput single-molecule force spectroscopy', 'Marsico, Annalisa|Labudde, Dirk|Sapra, Tanuj|Muller, Daniel J|Schroeder, Michael', 'Biotec, TU Dresden, Germany. annalisa.marsico@biotec.tu-dresden.de|Biotec, TU Dresden, Germany. annalisa.marsico@biotec.tu-dresden.de|Biotec, TU Dresden, Germany. annalisa.marsico@biotec.tu-dresden.de|Biotec, TU Dresden, Germany. annalisa.marsico@biotec.tu-dresden.de|Biotec, TU Dresden, Germany. annalisa.marsico@biotec.tu-dresden.de', 'Germany|Germany|Germany|Germany|Germany', 23, 'Algorithms|Artificial Intelligence|Bacteriorhodopsins|Computer Simulation|Elasticity|Membrane Proteins|Microscopy, Atomic Force|Models, Chemical|Models, Molecular|Numerical Analysis, Computer-Assisted|Pattern Recognition, Automated|Protein Conformation|Protein Denaturation|Protein Folding|Stress, Mechanical', 'Journal Article', '10.1093/bioinformatics/btl293', '17237097', 'Misfolding of membrane proteins plays an important role in many human diseases such as retinitis pigmentosa, hereditary deafness and diabetes insipidus. Little is known about membrane proteins as there are only very few high-resolution structures. Single-molecule force spectroscopy is a novel technique, which measures the force necessary to pull a protein out of a membrane. Such force curves contain valuable information on the protein structure, conformation, and inter- and intra-molecular forces. High-throughput force spectroscopy experiments generate hundreds of force curves including spurious ones and good curves, which correspond to different unfolding pathways. Manual analysis of these data is a bottleneck and source of inconsistent and subjective annotation.'),
(73273, 2007, 'bio', 'EBIMed--text crunching to gather facts for proteins from Medline', 'Rebholz-Schuhmann, Dietrich|Kirsch, Harald|Arregui, Miguel|Gaudan, Sylvain|Riethoven, Mark|Stoehr, Peter', 'European Bioinformatics Institute, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD, UK. Rebholz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD, UK. Rebholz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD, UK. Rebholz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD, UK. Rebholz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD, UK. Rebholz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD, UK. Rebholz@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 131, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Database Management Systems|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Proteins|Software|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/btl302', '17237098', 'To allow efficient and systematic retrieval of statements from Medline we have developed EBIMed, a service that combines document retrieval with co-occurrence-based analysis of Medline abstracts. Upon keyword query, EBIMed retrieves the abstracts from EMBL-EBIs installation of Medline and filters for sentences that contain biomedical terminology maintained in public bioinformatics resources. The extracted sentences and terminology are used to generate an overview table on proteins, Gene Ontology (GO) annotations, drugs and species used in the same biological context. All terms in retrieved abstracts and extracted sentences are linked to their entries in biomedical databases. We assessed the quality of the identification of terms and relations in the retrieved sentences. More than 90% of the protein names found indeed represented a protein. According to the analysis of four protein-protein pairs from the Wnt pathway we estimated that 37% of the statements containing such a pair mentioned a meaningful interaction and clarified the interaction of Dkk with LRP. We conclude that EBIMed improves access to information where proteins and drugs are involved in the same biological process, e.g. statements with GO annotations of proteins, protein-protein interactions and effects of drugs on proteins.'),
(73274, 2007, 'bio', 'Multiple alignment by sequence annealing', 'Schwartz, Ariel S|Pachter, Lior', 'EECS, Computer Science Division, University of California Berkeley, CA 94720, USA. sariel@cs.berkeley.edu|EECS, Computer Science Division, University of California Berkeley, CA 94720, USA. sariel@cs.berkeley.edu', 'United States|United States', 61, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btl311', '17237099', 'We introduce a novel approach to multiple alignment that is based on an algorithm for rapidly checking whether single matches are consistent with a partial multiple alignment. This leads to a sequence annealing algorithm, which is an incremental method for building multiple sequence alignments one match at a time. Our approach improves significantly on the standard progressive alignment approach to multiple alignment.'),
(73275, 2007, 'bio', 'Proceedings of the 5th European Conference on Computational Biology, ECCB 2006 January 21-24, 2007 Eilat, Israel', '-', '-', '-', 0, 'Computational Biology|Humans', 'Congress', '10.1093/bioinformatics/btl651', '17237100', '-'),
(73276, 2007, 'bio', 'Tandem repeats over the edit distance', 'Sokol, Dina|Benson, Gary|Tojeira, Justin', 'Department of Computer and Information Science, Brooklyn College of the City University of New York, Brooklyn, NY, USA. sokol@sci.brooklyn.cuny.edu|Department of Computer and Information Science, Brooklyn College of the City University of New York, Brooklyn, NY, USA. sokol@sci.brooklyn.cuny.edu|Department of Computer and Information Science, Brooklyn College of the City University of New York, Brooklyn, NY, USA. sokol@sci.brooklyn.cuny.edu', 'United States|United States|United States', 56, 'Algorithms|Base Sequence|Chromosome Mapping|DNA|Linkage Disequilibrium|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Tandem Repeat Sequences', 'Journal Article', '10.1093/bioinformatics/btl309', '17237101', 'A tandem repeat in DNA is a sequence of two or more contiguous, approximate copies of a pattern of nucleotides. Tandem repeats occur in the genomes of both eukaryotic and prokaryotic organisms. They are important in numerous fields including disease diagnosis, mapping studies, human identity testing (DNA fingerprinting), sequence homology and population studies. Although tandem repeats have been used by biologists for many years, there are few tools available for performing an exhaustive search for all tandem repeats in a given sequence.'),
(73277, 2007, 'bio', 'Designing patterns for profile HMM search', 'Sun, Yanni|Buhler, Jeremy', 'Department of Computer Science and Engineering, Washington University, St Louis, MO 63130, USA. yanni@cse.wustl.edu|Department of Computer Science and Engineering, Washington University, St Louis, MO 63130, USA. yanni@cse.wustl.edu', 'United States|United States', 10, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Conserved Sequence|Markov Chains|Models, Chemical|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btl323', '17237102', 'Profile HMMs are a powerful tool for modeling conserved motifs in proteins. These models are widely used by search tools to classify new protein sequences into families based on domain architecture. However, the proliferation of known motifs and new proteomic sequence data poses a computational challenge for search, requiring days of CPU time to annotate an organisms proteome.'),
(73278, 2007, 'bio', 'Simultaneous alignment and annotation of cis-regulatory regions', 'Bais, Abha Singh|Grossmann, Steffen|Vingron, Martin', 'Computational Molecular Biology, Max Planck Institute for Molecular Genetics Ihnestrasse 63-73, D-14195, Berlin, Germany. bais@molgen.mpg.de|Computational Molecular Biology, Max Planck Institute for Molecular Genetics Ihnestrasse 63-73, D-14195, Berlin, Germany. bais@molgen.mpg.de|Computational Molecular Biology, Max Planck Institute for Molecular Genetics Ihnestrasse 63-73, D-14195, Berlin, Germany. bais@molgen.mpg.de', 'Germany|Germany|Germany', 0, 'Algorithms|Base Sequence|Binding Sites|Molecular Sequence Data|Protein Binding|Regulatory Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btl305', '17237103', 'Current methods that annotate conserved transcription factor binding sites in an alignment of two regulatory regions perform the alignment and annotation step separately and combine the results in the end. If the site descriptions are weak or the sequence similarity is low, the local gap structure of the alignment poses a problem in detecting the conserved sites. It is therefore desirable to have an approach that is able to simultaneously consider the alignment as well as possibly matching site locations.'),
(73279, 2007, 'bio', 'Simulating multiplexed SNP discovery rates using base-specific cleavage and mass spectrometry', 'Böcker, Sebastian', 'Friedrich-Schiller-University Jena Ernst-Abbe-Platz 2, 07743 Jena, Germany. boecker@minet.uni-jena.de', 'Germany', 0, 'Algorithms|Base Pair Mismatch|Chromosome Mapping|DNA Fingerprinting|DNA Mutational Analysis|Mass Spectrometry|Models, Genetic|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btl291', '17237104', 'Single Nucleotide Polymorphisms (SNPs) are believed to contribute strongly to the genetic variability in living beings, and SNP and mutation discovery are of great interest in todays Life Sciences. A comparatively new method to discover such polymorphisms is based on base-specific cleavage, where resulting cleavage products are analyzed by mass spectrometry (MS). One particular advantage of this method is the possibility of multiplexing the biochemical reactions, i.e. examining multiple genomic regions in parallel. Simulations can help estimating the performance of a method for polymorphism discovery, and allow us to evaluate the influence of method parameters on the discovery rate, and also to investigate whether the method is well suited for a certain genomic region.'),
(73280, 2007, 'bio', 'A comparative genome approach to marker ordering', 'Faraut, T|de Givry, S|Chabrier, P|Derrien, T|Galibert, F|Hitte, C|Schiex, T', 'Laboratoire de génétique cellulaire BP 52627, 31326 Castanet Tolosan, France. thomas.faraut@toulouse.inra.fr|Laboratoire de génétique cellulaire BP 52627, 31326 Castanet Tolosan, France. thomas.faraut@toulouse.inra.fr|Laboratoire de génétique cellulaire BP 52627, 31326 Castanet Tolosan, France. thomas.faraut@toulouse.inra.fr|Laboratoire de génétique cellulaire BP 52627, 31326 Castanet Tolosan, France. thomas.faraut@toulouse.inra.fr|Laboratoire de génétique cellulaire BP 52627, 31326 Castanet Tolosan, France. thomas.faraut@toulouse.inra.fr|Laboratoire de génétique cellulaire BP 52627, 31326 Castanet Tolosan, France. thomas.faraut@toulouse.inra.fr|Laboratoire de génétique cellulaire BP 52627, 31326 Castanet Tolosan, France. thomas.faraut@toulouse.inra.fr', 'France|France|France|France|France|France|France', 0, 'Algorithms|Chromosome Mapping|Computer Simulation|Evolution, Molecular|Genetic Markers|Linkage Disequilibrium|Models, Genetic|Models, Statistical|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Species Specificity', 'Journal Article', '10.1093/bioinformatics/btl321', '17237105', 'Genome maps are fundamental to the study of an organism and essential in the process of genome sequencing which in turn provides the ultimate map of the genome. The increased number of genomes being sequenced offers new opportunities for the mapping of closely related organisms. We propose here an algorithmic formalization of a genome comparison approach to marker ordering.'),
(73281, 2007, 'bio', 'Genetic code symmetry and efficient design of GC-constrained coding sequences', 'Gavish, Matan|Peled, Amnon|Chor, Benny', 'School of Physics, Tel Aviv University Ramat-Aviv, Tel-Aviv 69978, Israel.|School of Physics, Tel Aviv University Ramat-Aviv, Tel-Aviv 69978, Israel.|School of Physics, Tel Aviv University Ramat-Aviv, Tel-Aviv 69978, Israel.', 'Israel|Israel|Israel', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Cloning, Molecular|DNA Probes|GC Rich Sequence|Genetic Code|Genetic Engineering|Molecular Sequence Data|Polymerase Chain Reaction|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btl317', '17237106', 'Cloning of long DNA sequences (40-60 bases) into phage display libraries using polymerase chain reaction (PCR) is a low efficiency process, in which PCR is used to incorporate a DNA insert, coding for a certain peptide, into the amplified sequence. The PCR efficiency in this process is strongly affected by the distribution of G-C bases in the amplified sequence. As any DNA insert coding for the target peptide may be attempted, there is a flexibility in choosing part of the amplified sequence. Since the number of inserts coding for the same peptide is exponential in the peptide length, a computational problem naturally arises--that of efficiently finding an insert, whose parameters are optimal for PCR cloning.'),
(73282, 2007, 'bio', 'Merging microarray cell synchronization experiments through curve alignment', 'Hermans, Filip|Tsiporkova, Elena', 'Computational Biology Division, Department of Plant Systems Biology Flanders Institute for Biotechnology, Technologiepark 917, 9052 Ghent, Belgium. fiher@psb.ugent.be|Computational Biology Division, Department of Plant Systems Biology Flanders Institute for Biotechnology, Technologiepark 917, 9052 Ghent, Belgium. fiher@psb.ugent.be', 'Belgium|Belgium', 32, 'Algorithms|Arabidopsis|Arabidopsis Proteins|Cell Cycle|Cell Cycle Proteins|Computer Simulation|Gene Expression Profiling|Information Storage and Retrieval|Models, Biological|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis', 'Evaluation Studies', '10.1093/bioinformatics/btl320', '17237107', 'The validity of periodic cell cycle regulation studies in plants is seriously compromised by the relatively poor quality of cell synchrony that is achieved for plant suspension cultures in comparison to yeast and mammals. The present state-of-the-art plant synchronization techniques cannot offer a complete cell cycle coverage and moreover a considerable loss of cell synchrony may occur toward the end of the sampling. One possible solution is to consider combining multiple datasets, produced by different synchronization techniques and thus covering different phases of the cell cycle, in order to arrive at a better cell cycle coverage.'),
(73283, 2007, 'bio', 'Family relationships: should consensus reign?--consensus clustering for protein families', 'Nikolski, Macha|Sherman, David J', 'CNRS/LaBRI, Université Bordeaux 1 351 cours de la Libération, 33405 Talence Cedex, France. macha@labri.fr|CNRS/LaBRI, Université Bordeaux 1 351 cours de la Libération, 33405 Talence Cedex, France. macha@labri.fr', 'France|France', 0, 'Algorithms|Amino Acid Sequence|Ascomycota|Cluster Analysis|Consensus Sequence|Fungal Proteins|Molecular Sequence Data|Multigene Family|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btl314', '17237108', 'Reliable identification of protein families is key to phylogenetic analysis, functional annotation and the exploration of protein function diversity in a given phylogenetic branch. As more and more complete genomes are sequenced, there is a need for powerful and reliable algorithms facilitating protein families construction.'),
(73284, 2007, 'bio', 'Optimization of probe coverage for high-resolution oligonucleotide aCGH', 'Lipson, Doron|Yakhini, Zohar|Aumann, Yonatan', 'Computer Science Department Technion, Israel. dlipson@cs.technion.ac.il|Computer Science Department Technion, Israel. dlipson@cs.technion.ac.il|Computer Science Department Technion, Israel. dlipson@cs.technion.ac.il', 'Israel|Israel|Israel', 14, 'Base Sequence|Chromosome Mapping|DNA Probes|Gene Dosage|In Situ Hybridization, Fluorescence|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btl316', '17237109', 'The resolution at which genomic alterations can be mapped by means of oligonucleotide aCGH (array-based comparative genomic hybridization) is limited by two factors: the availability of high-quality probes for the target genomic sequence and the array real-estate. Optimization of the probe selection process is required for arrays that are designed to probe specific genomic regions in very high resolution without compromising probe quality constraints.'),
(73285, 2007, 'bio', 'Discovering tightly regulated and differentially expressed gene sets in whole genome expression data', 'Ye, Chun|Eskin, Eleazar', 'Bioinformatics Program, University of California San Diego, La Jolla, CA 92093-0404, USA. cye@bioinf.ucsd.edu|Bioinformatics Program, University of California San Diego, La Jolla, CA 92093-0404, USA. cye@bioinf.ucsd.edu', 'United States|United States', 0, 'Chromosome Mapping|Computer Simulation|Data Interpretation, Statistical|Databases, Protein|Gene Expression|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Models, Statistical|Proteome|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btl315', '17237110', 'Recently, a new type of expression data is being collected which aims to measure the effect of genetic variation on gene expression in pathways. In these datasets, expression profiles are constructed for multiple strains of the same model organism under the same condition. The goal of analyses of these data is to find differences in regulatory patterns due to genetic variation between strains, often without a phenotype of interest in mind. We present a new method based on notions of tight regulation and differential expression to look for sets of genes which appear to be significantly affected by genetic variation.'),
(73286, 2007, 'bio', 'A supervised approach for identifying discriminating genotype patterns and its application to breast cancer data', 'Yosef, Nir|Yakhini, Zohar|Tsalenko, Anya|Kristensen, Vessela|Børresen-Dale, Anne-Lise|Ruppin, Eytan|Sharan, Roded', 'School of Computer Science, Tel-Aviv University Tel-Aviv 69978, Israel.|School of Computer Science, Tel-Aviv University Tel-Aviv 69978, Israel.|School of Computer Science, Tel-Aviv University Tel-Aviv 69978, Israel.|School of Computer Science, Tel-Aviv University Tel-Aviv 69978, Israel.|School of Computer Science, Tel-Aviv University Tel-Aviv 69978, Israel.|School of Computer Science, Tel-Aviv University Tel-Aviv 69978, Israel.|School of Computer Science, Tel-Aviv University Tel-Aviv 69978, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel', 11, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Breast Neoplasms|Diagnosis, Computer-Assisted|Discriminant Analysis|Gene Expression Profiling|Genotype|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Evaluation Studies', '10.1093/bioinformatics/btl298', '17237111', 'Large-scale association studies, investigating the genetic determinants of a phenotype of interest, are producing increasing amounts of genomic variation data on human cohorts. A fundamental challenge in these studies is the detection of genotypic patterns that discriminate individuals exhibiting the phenotype under study from individuals that do not possess it. The difficulty stems from the large number of single nucleotide polymorphism (SNP) combinations that have to be tested. The discrimination problem becomes even more involved when additional high-throughput data, such as gene expression data, are available for the same cohort.'),
(73287, 2007, 'bio', 'Electrostatic potentials of proteins in water: a structured continuum approach', 'Hildebrandt, Andreas|Blossey, Ralf|Rjasanow, Sergej|Kohlbacher, Oliver|Lenhof, Hans-Peter', 'Center for Bioinformatics, Saarland University PO 15 11 50, 66041 Saarbrücken, Germany. anhi@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University PO 15 11 50, 66041 Saarbrücken, Germany. anhi@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University PO 15 11 50, 66041 Saarbrücken, Germany. anhi@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University PO 15 11 50, 66041 Saarbrücken, Germany. anhi@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University PO 15 11 50, 66041 Saarbrücken, Germany. anhi@bioinf.uni-sb.de', 'Germany|Germany|Germany|Germany|Germany', 9, 'Acetylcholinesterase|Algorithms|Computer Simulation|Electrochemistry|Electromagnetic Fields|Models, Chemical|Models, Molecular|Protein Conformation|Solvents|Static Electricity|Trypsin|Water', 'Evaluation Studies', '10.1093/bioinformatics/btl312', '17237112', 'Electrostatic interactions play a crucial role in many biomolecular processes, including molecular recognition and binding. Biomolecular electrostatics is modulated to a large extent by the water surrounding the molecules. Here, we present a novel approach to the computation of electrostatic potentials which allows the inclusion of water structure into the classical theory of continuum electrostatics. Based on our recent purely differential formulation of nonlocal electrostatics [Hildebrandt, et al. (2004) Phys. Rev. Lett., 93, 108104] we have developed a new algorithm for its efficient numerical solution. The key component of this algorithm is a boundary element solver, having the same computational complexity as established boundary element methods for local continuum electrostatics. This allows, for the first time, the computation of electrostatic potentials and interactions of large biomolecular systems immersed in water including effects of the solvents structure in a continuum description. We illustrate the applicability of our approach with two examples, the enzymes trypsin and acetylcholinesterase. The approach is applicable to all problems requiring precise prediction of electrostatic interactions in water, such as protein-ligand and protein-protein docking, folding and chromatin regulation. Initial results indicate that this approach may shed new light on biomolecular electrostatics and on aspects of molecular recognition that classical local electrostatics cannot reveal.'),
(73288, 2007, 'bio', 'I-Ssp6803I: the first homing endonuclease from the PD-(D/E)XK superfamily exhibits an unusual mode of DNA recognition', 'Orlowski, Jerzy|Boniecki, Michal|Bujnicki, Janusz M', 'Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland.|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland.|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland.', 'Poland|Poland|Poland', 28, 'Amino Acid Motifs|Amino Acid Sequence|Binding Sites|DNA|Databases, Protein|Deoxyribonucleases, Type II Site-Specific|Evolution, Molecular|Models, Molecular|Molecular Sequence Data|Protein Folding|Protein Structure, Secondary|Sequence Alignment|Substrate Specificity', 'Journal Article', '10.1093/bioinformatics/btm007', '17242028', 'Restriction endonucleases (REases) and homing endonucleases (HEases) are biotechnologically important enzymes. Nearly all structurally characterized REases belong to the PD-(D/E)XK superfamily of nucleases, while most HEases belong to an unrelated LAGLIDADG superfamily. These two protein folds are typically associated with very different modes of protein-DNA recognition, consistent with the different mechanisms of action required to achieve high specificity. REases recognize short DNA sequences using multiple contacts per base pair, while HEases recognize very long sites using a few contacts per base pair, thereby allowing for partial degeneracy of the target sequence. Thus far, neither REases with the LAGLIDADG fold, nor HEases with the PD-(D/E)XK fold, have been found.'),
(73289, 2007, 'bio', 'On the relationship between sequence and structure similarities in proteomics', 'Krissinel, Evgeny', 'European Bioinformatics Institute, Genome Campus, Hinxton, Cambridge CB10 1SD, UK. keb@ebi.ac.ukkeb', 'United Kingdom', 60, 'Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteome|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Statistics as Topic|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/btm006', '17242029', 'The underlying assumption of many sequence-based comparative studies in proteomics is that different aspects of protein structure and therefore functionality may be linked to particular sequence motifs. This holds true if sequence similarity is sufficiently high, but in general the relationship between protein sequence and structure appears complex and is not well understood.'),
(73290, 2007, 'bio', 'SatDNA Analyzer: a computing tool for satellite-DNA evolutionary analysis', 'Navajas-Pérez, Rafael|Rubio-Escudero, Cristina|Aznarte, José Luis|Rejón, Manuel Ruiz|Garrido-Ramos, Manuel A', 'Departamento de Genética, Facultad de Ciencias, Universidad de Granada, 18071, Granada, Spain. rnavajas@uga.edu|Departamento de Genética, Facultad de Ciencias, Universidad de Granada, 18071, Granada, Spain. rnavajas@uga.edu|Departamento de Genética, Facultad de Ciencias, Universidad de Granada, 18071, Granada, Spain. rnavajas@uga.edu|Departamento de Genética, Facultad de Ciencias, Universidad de Granada, 18071, Granada, Spain. rnavajas@uga.edu|Departamento de Genética, Facultad de Ciencias, Universidad de Granada, 18071, Granada, Spain. rnavajas@uga.edu', 'Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Base Sequence|DNA Mutational Analysis|DNA, Satellite|Evolution, Molecular|Genetic Variation|Molecular Sequence Data|Polymorphism, Single Nucleotide|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btm005', '17242030', 'satDNA Analyzer is a program, implemented in C++, for the analysis of the patterns of variation at each nucleotide position considered independently amongst all units of a given satellite-DNA family when comparing it between a pair of species. The program classifies each site accordingly as monomorphic or polymorphic, discriminates shared from non-shared polymorphisms and classifies each non-shared polymorphism according to the model proposed by Strachan et al. in six different stages of transition during the spread of a variant repeat unit toward its fixation. Furthermore, this program implements several other utilities for satellite-DNA analysis evolution such as the design of the average consensus sequences, the average base pair contents, the distribution of variant sites, the transition to transversion ratio and different estimates of intra-specific variation and inter-specific variation. Aprioristic hypotheses on factors influencing the molecular drive process and the rates and biases of concerted evolution can be tested with this program. Additionally, satDNA Analyzer generates an output file containing a sequence alignment without shared polymorphisms to be used for further evolutionary analysis by using different phylogenetic softwares.'),
(73291, 2007, 'bio', 'Molecular basis for specificity in the druggable kinome: sequence-based analysis', 'Chen, Jianping|Zhang, Xi|Fernández, Ariel', 'Program in Applied Physics and Rice Quantum Institute, Rice University, Houston, TX 77005, USA.|Program in Applied Physics and Rice Quantum Institute, Rice University, Houston, TX 77005, USA.|Program in Applied Physics and Rice Quantum Institute, Rice University, Houston, TX 77005, USA.', 'United States|United States|United States', 35, 'Binding Sites|Databases, Protein|Drug Design|Ligands|Models, Molecular|Protein Conformation|Protein Kinases|Sensitivity and Specificity|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btl666', '17255140', 'Rational design of kinase inhibitors remains a challenge partly because there is no clear delineation of the molecular features that direct the pharmacological impact towards clinically relevant targets. Standard factors governing ligand affinity, such as potential for intermolecular hydrophobic interactions or for intermolecular hydrogen bonding do not provide good markers to assess cross reactivity. Thus, a core question in the informatics of drug design is what type of molecular similarity among targets promotes promiscuity and what type of molecular difference governs specificity. This work answers the question for a sizable screened sample of the human pharmacokinome including targets with unreported structure.'),
(73292, 2007, 'bio', 'Robustness analysis of the E coli chemosensory system to perturbations in chemoattractant concentrations', 'Patnaik, Pratap R', 'Institute of Microbial Technology, Sector 39-A, Chandigarh-160 036, India. pratap@imtech.res.in', 'India', 0, 'Adaptation, Physiological|Bacterial Proteins|Chemotactic Factors|Chemotaxis|Computer Simulation|Dose-Response Relationship, Drug|Escherichia coli|Escherichia coli Proteins|Histidine Kinase|Membrane Proteins|Methyl-Accepting Chemotaxis Proteins|Models, Biological|Phosphorylation', 'Journal Article', '10.1093/bioinformatics/btm028', '17267424', 'Cells of Escherichia coli sense and move toward chemical attractants. This is done through an intricate sensory system that eventually directs the movements of flagellae which regulate the runs and tumbles of the cells. Under realistic conditions, chemical stimuli often fluctuate due to noise from the environment. The effect of noise on the chemosensory system has been investigated here through the sensitivity coefficients of the concentrations of four key proteins--the phosphorylated forms of CheA, CheB and CheY, and the FliM-CheY-P complex--that govern chemotactic motility. The letter P denotes phosphorylation.'),
(73293, 2007, 'bio', 'A simulation test bed for hypotheses of genome evolution', 'Beiko, Robert G|Charlebois, Robert L', 'Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada. beiko@cs.dal.ca|Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada. beiko@cs.dal.ca', 'Canada|Canada', 31, 'Biological Evolution|Chromosome Mapping|Computer Simulation|Evolution, Molecular|Genetic Variation|Genome, Bacterial|Models, Genetic|Proteome|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm024', '17267425', 'Microbial genomes undergo evolutionary processes such as gene family expansion and contraction, variable rates and patterns of sequence substitution and lateral genetic transfer. Simulation tools are essential for both the generation of data under different evolutionary models and the validation of analytical methods on such data. However, meaningful investigation of phenomena such as lateral genetic transfer requires the simultaneous consideration of many underlying evolutionary processes.'),
(73294, 2007, 'bio', 'Boolean dynamics of genetic regulatory networks inferred from microarray time series data', 'Martin, Shawn|Zhang, Zhaoduo|Martino, Anthony|Faulon, Jean-Loup', 'Sandia National Laboratories, Computational Biology Department, PO Box 5800, Albuquerque, NM 87185-1316, USA.|Sandia National Laboratories, Computational Biology Department, PO Box 5800, Albuquerque, NM 87185-1316, USA.|Sandia National Laboratories, Computational Biology Department, PO Box 5800, Albuquerque, NM 87185-1316, USA.|Sandia National Laboratories, Computational Biology Department, PO Box 5800, Albuquerque, NM 87185-1316, USA.', 'United States|United States|United States|United States', 110, 'Algorithms|Artificial Intelligence|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Logistic Models|Models, Biological|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteome|Signal Transduction|Time Factors', 'Evaluation Studies', '10.1093/bioinformatics/btm021', '17267426', 'Methods available for the inference of genetic regulatory networks strive to produce a single network, usually by optimizing some quantity to fit the experimental observations. In this article we investigate the possibility that multiple networks can be inferred, all resulting in similar dynamics. This idea is motivated by theoretical work which suggests that biological networks are robust and adaptable to change, and that the overall behavior of a genetic regulatory network might be captured in terms of dynamical basins of attraction.'),
(73295, 2007, 'bio', 'A simple shape characteristic of protein-protein recognition', 'Nicola, George|Vakser, Ilya A', 'Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Rd, La Jolla, CA 92037, USA.|Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Rd, La Jolla, CA 92037, USA.', 'United States|United States', 0, 'Algorithms|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm018', '17267427', 'Observation of co-crystallized protein-protein complexes and low-resolution protein-protein docking studies suggest the existence of a binding-related anisotropic shape characteristic of protein-protein complexes.'),
(73296, 2007, 'bio', 'OMWSA: detection of DNA repeats using moving window spectral analysis', 'Du, Liping|Zhou, Hongxia|Yan, Hong', 'Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong.|Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong.|Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong', 21, 'Algorithms|DNA|Fourier Analysis|Humans|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btm008', '17267428', 'Repetitive DNA sequences play paramount biological roles, such as gene variation and regulatory functions on gene expressions. Until now, detection of various kinds of DNA repeats accurately is still an open problem. In this article, we propose a new method and a visualization tool for detecting DNA repeats in a 2D plane of location and frequency by using optimized moving window spectral analysis. The spectrogram can display the general distribution of repetitive sequences while showing the repeat period, length and location without any prior knowledge. Experimental results demonstrate that our method is accurate and robust even under the condition of excessive mutating and interleaving.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73297, 2007, 'bio', 'Gene expression network analysis and applications to immunology', 'Nacu, Serban|Critchley-Thorne, Rebecca|Lee, Peter|Holmes, Susan', 'Department of Statistics, Stanford University, Stanford, CA 94305, USA. serban@stat.stanford.edu|Department of Statistics, Stanford University, Stanford, CA 94305, USA. serban@stat.stanford.edu|Department of Statistics, Stanford University, Stanford, CA 94305, USA. serban@stat.stanford.edu|Department of Statistics, Stanford University, Stanford, CA 94305, USA. serban@stat.stanford.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Immunologic Techniques|Models, Immunological|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btm019', '17267429', 'We address the problem of using expression data and prior biological knowledge to identify differentially expressed pathways or groups of genes. Following an idea of Ideker et al. (2002), we construct a gene interaction network and search for high-scoring subnetworks. We make several improvements in terms of scoring functions and algorithms, resulting in higher speed and accuracy and easier biological interpretation. We also assign significance levels to our results, adjusted for multiple testing. Our methods are successfully applied to three human microarray data sets, related to cancer and the immune system, retrieving several known and potential pathways. The method, denoted by the acronym GXNA (Gene eXpression Network Analysis) is implemented in software that is publicly available and can be used on virtually any microarray data set.'),
(73298, 2007, 'bio', 'SGN Sim, a stochastic genetic networks simulator', 'Ribeiro, Andre S|Lloyd-Price, Jason', 'Institute for Biocomplexity and Informatics, University of Calgary, Canada. ARibeiro@ucalgary.ca|Institute for Biocomplexity and Informatics, University of Calgary, Canada. ARibeiro@ucalgary.ca', 'Canada|Canada', 0, 'Algorithms|Computer Simulation|Gene Expression Regulation|Models, Genetic|Models, Statistical|Protein Biosynthesis|Proteome|Signal Transduction|Stochastic Processes|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btm004', '17267430', 'We present SGNSim, Stochastic Gene Networks Simulator, a tool to model gene regulatory networks (GRN) where transcription and translation are modeled as multiple time delayed events and its dynamics is driven by a stochastic simulation algorithm (SSA) able to deal with multiple time delayed events. The delays can be drawn from several distributions and the reaction rates from complex functions or from physical parameters. SGNSim can generate ensembles of GRNs, within a set of user-defined parameters, such as topology. It can also be used to model specific GRNs and systems of chemical reactions. Perturbations, e.g. gene deletion, over-expression, copy and mutation, can be modeled as well. As examples, we present a model of a toggle switch without cooperative binding subject to perturbations, a system of reactions within a compartmentalized environment where membrane crossing is controlled by a negative feedback mechanism and a simulation based on the yeast transcriptional network.'),
(73299, 2007, 'bio', 'Large scale genotype-phenotype correlation analysis based on phylogenetic trees', 'Habib, Farhat|Johnson, Andrew D|Bundschuh, Ralf|Janies, Daniel', 'Department of Physics, The Ohio State University, Columbus, OH 43210, USA. farhat@pacific.mps.ohio-state.edu|Department of Physics, The Ohio State University, Columbus, OH 43210, USA. farhat@pacific.mps.ohio-state.edu|Department of Physics, The Ohio State University, Columbus, OH 43210, USA. farhat@pacific.mps.ohio-state.edu|Department of Physics, The Ohio State University, Columbus, OH 43210, USA. farhat@pacific.mps.ohio-state.edu', 'United States|United States|United States|United States', 13, 'Algorithms|Base Sequence|Chromosome Mapping|DNA|DNA Mutational Analysis|Genetic Variation|Genotype|Molecular Sequence Data|Phenotype|Phylogeny|Polymorphism, Single Nucleotide|Software|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/btm003', '17267431', 'We provide two methods for identifying changes in genotype that are correlated with changes in a phenotype implied by phylogenetic trees. The first method, VENN, works when the number of branches over which the change occurred are modest. VENN looks for genetic changes that are completely penetrant with phenotype changes on a tree. The second method, CCTSWEEP, allows for a partial matching between changes in phenotypes and genotypes and provides a score for each change using Maddisons concentrated changes test. The mutations that are highly correlated with phenotypic change can be ranked by score. We use these methods to find SNPs correlated with resistance to Bacillus anthracis in inbred mouse strains. Our findings are consistent with the current biological literature, and also suggest potential novel candidate genes.'),
(73300, 2007, 'bio', 'CGHcall: calling aberrations for array CGH tumor profiles', 'van de Wiel, Mark A|Kim, Kyung In|Vosse, Sjoerd J|van Wieringen, Wessel N|Wilting, Saskia M|Ylstra, Bauke', 'Department of Pathology, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Pathology, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Pathology, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Pathology, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Pathology, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl|Department of Pathology, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands. mark.vdwiel@vumc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Chromosome Aberrations|Chromosome Mapping|DNA, Neoplasm|Gene Dosage|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btm030', '17267432', 'CGHcall achieves high calling accuracy for array CGH data by effective use of breakpoint information from segmentation and by inclusion of several biological concepts that are ignored by existing algorithms. The algorithm is validated for simulated and verified real array CGH data. By incorporating more than three classes, CGHcall improves detection of single copy gains and amplifications. Moreover, it allows effective inclusion of chromosome arm information.'),
(73301, 2007, 'bio', 'Ontology development for biological systems: immunology', 'Diehl, Alexander D|Lee, Jamie A|Scheuermann, Richard H|Blake, Judith A', 'Mouse Genome Informatics, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04605, USA. adiehl@informatics.jax.org|Mouse Genome Informatics, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04605, USA. adiehl@informatics.jax.org|Mouse Genome Informatics, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04605, USA. adiehl@informatics.jax.org|Mouse Genome Informatics, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04605, USA. adiehl@informatics.jax.org', 'United States|United States|United States|United States', 0, 'Database Management Systems|Databases, Protein|Immunologic Techniques|Information Storage and Retrieval|Proteome|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btm029', '17267433', 'We recently implemented improvements to the representation of immunology content of the biological process branch of the Gene Ontology (GO). The aims of the revision were to provide a comprehensive representation of immunological processes and to improve the organization of immunology related terms in the GO to match current concepts in the field of immunology. With these improvements, the GO will better reflect current understanding in the field of immunology and thus prove to be a more valuable resource for knowledge representation in gene annotation and analysis in the areas of immunology related to genomics and bioinformatics.'),
(73302, 2007, 'bio', 'COPYCAT: cophylogenetic analysis tool', 'Meier-Kolthoff, Jan P|Auch, Alexander F|Huson, Daniel H|Göker, Markus', 'Center for Bioinformatics (ZBIT), Sand 14, Tübingen, Germany.|Center for Bioinformatics (ZBIT), Sand 14, Tübingen, Germany.|Center for Bioinformatics (ZBIT), Sand 14, Tübingen, Germany.|Center for Bioinformatics (ZBIT), Sand 14, Tübingen, Germany.', 'Germany|Germany|Germany|Germany', 29, 'Algorithms|Computer Simulation|Host-Parasite Interactions|Models, Genetic|Phylogeny|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm027', '17267434', 'We have developed the software CopyCat which provides an easy and fast access to cophylogenetic analyses. It incorporates a wrapper for the program ParaFit, which conducts a statistical test for the presence of congruence between host and parasite phylogenies. CopyCat offers various features, such as the creation of customized host-parasite association data and the computation of phylogenetic host/parasite trees based on the NCBI taxonomy.'),
(73303, 2007, 'bio', 'De novo SVM classification of precursor microRNAs from genomic pseudo hairpins using global and intrinsic folding measures', 'Ng, Kwang Loong Stanley|Mishra, Santosh K', 'Bioinformatics Institute, Singapore. stanley@bii.a-star.edu.sg|Bioinformatics Institute, Singapore. stanley@bii.a-star.edu.sg', 'Singapore|Singapore', 182, 'Algorithms|Artificial Intelligence|Base Sequence|Chromosome Mapping|Computer Simulation|Humans|MicroRNAs|Models, Chemical|Models, Molecular|Molecular Sequence Data|Nucleic Acid Conformation|Pattern Recognition, Automated|RNA Precursors|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btm026', '17267435', 'MicroRNAs (miRNAs) are small ncRNAs participating in diverse cellular and physiological processes through the post-transcriptional gene regulatory pathway. Critically associated with the miRNAs biogenesis, the hairpin structure is a necessary feature for the computational classification of novel precursor miRNAs (pre-miRs). Though many of the abundant genomic inverted repeats (pseudo hairpins) can be filtered computationally, novel species-specific pre-miRs are likely to remain elusive.'),
(73304, 2007, 'bio', 'SNPassoc: an R package to perform whole genome association studies', 'González, Juan R|Armengol, Lluís|Solé, Xavier|Guinó, Elisabet|Mercader, Josep M|Estivill, Xavier|Moreno, Víctor', 'Genes and Disease Program, Centre for Genomic Regulation, IDIBELL, Catalan Institute of Oncology, Barcelona, Spain. juanramon.gonzalez@crg.es|Genes and Disease Program, Centre for Genomic Regulation, IDIBELL, Catalan Institute of Oncology, Barcelona, Spain. juanramon.gonzalez@crg.es|Genes and Disease Program, Centre for Genomic Regulation, IDIBELL, Catalan Institute of Oncology, Barcelona, Spain. juanramon.gonzalez@crg.es|Genes and Disease Program, Centre for Genomic Regulation, IDIBELL, Catalan Institute of Oncology, Barcelona, Spain. juanramon.gonzalez@crg.es|Genes and Disease Program, Centre for Genomic Regulation, IDIBELL, Catalan Institute of Oncology, Barcelona, Spain. juanramon.gonzalez@crg.es|Genes and Disease Program, Centre for Genomic Regulation, IDIBELL, Catalan Institute of Oncology, Barcelona, Spain. juanramon.gonzalez@crg.es|Genes and Disease Program, Centre for Genomic Regulation, IDIBELL, Catalan Institute of Oncology, Barcelona, Spain. juanramon.gonzalez@crg.es', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain', 503, 'Databases, Genetic|Genomics|Haplotypes|Linear Models|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btm025', '17267436', 'The popularization of large-scale genotyping projects has led to the widespread adoption of genetic association studies as the tool of choice in the search for single nucleotide polymorphisms (SNPs) underlying susceptibility to complex diseases. Although the analysis of individual SNPs is a relatively trivial task, when the number is large and multiple genetic models need to be explored it becomes necessary a tool to automate the analyses. In order to address this issue, we developed SNPassoc, an R package to carry out most common analyses in whole genome association studies. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis).'),
(73305, 2007, 'bio', 'PROMALS: towards accurate multiple sequence alignments of distantly related proteins', 'Pei, Jimin|Grishin, Nick V', 'Howard Hughes Medical Institute, The University of Texas Southwestern Medical Center at Dallas, 6001 Forest Park Road, Dallas, TX 75390-9050, USA. jpei@chop.swmed.edu|Howard Hughes Medical Institute, The University of Texas Southwestern Medical Center at Dallas, 6001 Forest Park Road, Dallas, TX 75390-9050, USA. jpei@chop.swmed.edu', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Molecular Sequence Data|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/btm017', '17267437', 'Accurate multiple sequence alignments are essential in protein structure modeling, functional prediction and efficient planning of experiments. Although the alignment problem has attracted considerable attention, preparation of high-quality alignments for distantly related sequences remains a difficult task.'),
(73306, 2007, 'bio', 'An ensemble approach to microarray data-based gene prioritization after missing value imputation', 'Hua, Dong|Lai, Yinglei', 'Department of Computer Science, The George Washington University, 801 22nd Street, Suite 704, N.W. Washington, DC 20052, USA.|Department of Computer Science, The George Washington University, 801 22nd Street, Suite 704, N.W. Washington, DC 20052, USA.', 'United States|United States', 7, 'Algorithms|Artifacts|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Evaluation Studies', '10.1093/bioinformatics/btm010', '17267438', 'Microarrays have been widely used to discover novel disease related genes. Some types of microarray, such as cDNA arrays, usually contain a considerable portion of missing values. When missing value imputation and gene prioritization are sequentially conducted, it is necessary to consider the distribution space of prioritization scores due to the existence of missing values. We propose an ensemble approach to address this issue. A bootstrap procedure enables us to generate a resample multivariate distribution of the prioritization scores and then to obtain the expected prioritization scores.'),
(73307, 2007, 'bio', 'SCOOP: a simple method for identification of novel protein superfamily relationships', 'Bateman, Alex|Finn, Robert D', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK. agb@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA, UK. agb@sanger.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acid Sequence|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Multigene Family|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/btm034', '17277330', 'Profile searches of sequence databases are a sensitive way to detect sequence relationships. Sophisticated profile-profile comparison algorithms that have been recently introduced increase search sensitivity even further.'),
(73308, 2007, 'bio', 'Disease-specific genomic analysis: identifying the signature of pathologic biology', 'Nicolau, Monica|Tibshirani, Robert|Børresen-Dale, Anne-Lise|Jeffrey, Stefanie S', 'Department of Surgery, Stanford University School of Medicine, Stanford University, Stanford, CA, USA.|Department of Surgery, Stanford University School of Medicine, Stanford University, Stanford, CA, USA.|Department of Surgery, Stanford University School of Medicine, Stanford University, Stanford, CA, USA.|Department of Surgery, Stanford University School of Medicine, Stanford University, Stanford, CA, USA.', 'United States|United States|United States|United States', 35, 'Biomarkers, Tumor|Breast Neoplasms|Chromosome Mapping|Diagnosis, Computer-Assisted|Female|Gene Expression Profiling|Genetic Markers|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Receptors, Estrogen|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1093/bioinformatics/btm033', '17277331', 'Genomic high-throughput technology generates massive data, providing opportunities to understand countless facets of the functioning genome. It also raises profound issues in identifying data relevant to the biology being studied.'),
(73309, 2007, 'bio', 'NetMatch: a Cytoscape plugin for searching biological networks', 'Ferro, A|Giugno, R|Pigola, G|Pulvirenti, A|Skripin, D|Bader, G D|Shasha, D', 'Dipartimento di Matematica e Informatica, Università di Catania, Viale A. Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A. Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A. Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A. Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A. Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A. Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it|Dipartimento di Matematica e Informatica, Università di Catania, Viale A. Doria 6, I-95125 Catania, Italy. ferro@dmi.unict.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Computer Graphics|Computer Simulation|Database Management Systems|Information Storage and Retrieval|Models, Biological|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm032', '17277332', 'NetMatch is a Cytoscape plugin which allows searching biological networks for subcomponents matching a given query. Queries may be approximate in the sense that certain parts of the subgraph-query may be left unspecified. To make the query creation process easy, a drawing tool is provided. Cytoscape is a bioinformatics software platform for the visualization and analysis of biological networks.'),
(73310, 2007, 'bio', 'Automatic correspondence of tags and genes (ACTG): a tool for the analysis of SAGE, MPSS and SBS data', 'Galante, Pedro A F|Trimarchi, Jeff|Cepko, Constance L|de Souza, Sandro J|Ohno-Machado, Lucila|Kuo, Winston P', 'Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil. pgalante@ludwig.org.br|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil. pgalante@ludwig.org.br|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil. pgalante@ludwig.org.br|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil. pgalante@ludwig.org.br|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil. pgalante@ludwig.org.br|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, Brazil. pgalante@ludwig.org.br', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 8, 'Chromosome Mapping|Expressed Sequence Tags|Gene Expression Profiling|Genes|Software|Statistics as Topic|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm023', '17277333', 'A critical step in any SAGE, MPSS and SBS data analysis is tag-to-gene assignment. Current available tools are limited by a tag-by-tag annotation process and/or do not provide the dataset that is used to produce a complete tag-to-gene mapping. We developed ACTG, a web-based application that allows a large-scale tag-to-gene mapping using several reference datasets. ACTG can annotate SAGE (14 or 21 bp), MPSS (17 or 20 bp) and SBS (16 bp) data for both human and mouse organisms.'),
(73311, 2007, 'bio', 'DFprot: a webtool for predicting local chain deformability', 'Garzón, José Ignacio|Kovacs, Julio|Abagyan, Ruben|Chacón, Pablo', 'Centro de Investigaciones Biológicas, CSIC, Ramiro de Maeztu 9, 28040 Madrid, Spain.|Centro de Investigaciones Biológicas, CSIC, Ramiro de Maeztu 9, 28040 Madrid, Spain.|Centro de Investigaciones Biológicas, CSIC, Ramiro de Maeztu 9, 28040 Madrid, Spain.|Centro de Investigaciones Biológicas, CSIC, Ramiro de Maeztu 9, 28040 Madrid, Spain.', 'Spain|Spain|Spain|Spain', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Elasticity|Internet|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btm014', '17277334', 'DFprot is a web-based server for predicting main-chain deformability from a single protein conformation. The server automatically performs a normal-mode analysis (NMA) of the uploaded structure and calculates its capability to deform at each of its residues. Non-specialists can easily and rapidly obtain a quantitative first approximation of the flexibility of their structures with a simple and efficient interface.'),
(73312, 2007, 'bio', 'Hardware acceleration of processing of mass spectrometric data for proteomics', 'Bogdan, Istvan|Coca, Daniel|Rivers, Jenny|Beynon, Robert J', 'Department of Automatic Control & Systems Engineering, The University of Sheffield, Mappin Street, Sheffield S1 3JD, UK.|Department of Automatic Control & Systems Engineering, The University of Sheffield, Mappin Street, Sheffield S1 3JD, UK.|Department of Automatic Control & Systems Engineering, The University of Sheffield, Mappin Street, Sheffield S1 3JD, UK.|Department of Automatic Control & Systems Engineering, The University of Sheffield, Mappin Street, Sheffield S1 3JD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 21, 'Algorithms|Equipment Design|Equipment Failure Analysis|Mass Spectrometry|Peptide Mapping|Proteomics|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Signal Processing, Computer-Assisted', 'Evaluation Studies', '10.1093/bioinformatics/btl656', '17277335', 'High-resolution mass spectrometers generate large data files that are complex, noisy and require extensive processing to extract the optimal data from raw spectra. This processing is readily achieved in software and is often embedded in manufacturers instrument control and data processing environments. However, the speed of this data processing is such that it is usually performed off-line, post data acquisition. We have been exploring strategies that would allow real-time advanced processing of mass spectrometric data, making use of the reconfigurable computing paradigm, which exploits the flexibility and versatility of Field Programmable Gate Arrays (FPGAs). This approach has emerged as a powerful solution for speeding up time-critical algorithms. We describe here a reconfigurable computing solution for processing raw mass spectrometric data generated by MALDI-ToF instruments. The hardware-implemented algorithms for de-noising, baseline correction, peak identification and deisotoping, running on a Xilinx Virtex 2 FPGA at 180 MHz, generate a mass fingerprint over 100 times faster than an equivalent algorithm written in C, running on a Dual 3 GHz Xeon workstation.'),
(73313, 2007, 'bio', 'NetPhosYeast: prediction of protein phosphorylation sites in yeast', 'Ingrell, Christian R|Miller, Martin L|Jensen, Ole N|Blom, Nikolaj', 'University of Southern Denmark, Campusvej 55, DK-5230, Odense M, Denmark.|University of Southern Denmark, Campusvej 55, DK-5230, Odense M, Denmark.|University of Southern Denmark, Campusvej 55, DK-5230, Odense M, Denmark.|University of Southern Denmark, Campusvej 55, DK-5230, Odense M, Denmark.', 'Denmark|Denmark|Denmark|Denmark', 95, 'Algorithms|Binding Sites|Fungal Proteins|Neural Networks (Computer)|Pattern Recognition, Automated|Phosphorylation|Protein Binding|Sequence Analysis, Protein|Yeasts', 'Journal Article', '10.1093/bioinformatics/btm020', '17282998', 'We here present a neural network-based method for the prediction of protein phosphorylation sites in yeast--an important model organism for basic research. Existing protein phosphorylation site predictors are primarily based on mammalian data and show reduced sensitivity on yeast phosphorylation sites compared to those in humans, suggesting the need for an yeast-specific phosphorylation site predictor. NetPhosYeast achieves a correlation coefficient close to 0.75 with a sensitivity of 0.84 and specificity of 0.90 and outperforms existing predictors in the identification of phosphorylation sites in yeast.'),
(73314, 2007, 'bio', 'Assessment of the probabilities for evolutionary structural changes in protein folds', 'Viksna, Juris|Gilbert, David', 'Institute of Mathematics and Computer Science, University of Latvia, Rainis boulevard 29, Riga LV-1459, Latvia. juris.viksna@mii.lu.lv|Institute of Mathematics and Computer Science, University of Latvia, Rainis boulevard 29, Riga LV-1459, Latvia. juris.viksna@mii.lu.lv', 'Latvia|Latvia', 0, 'Computer Simulation|Conserved Sequence|Data Interpretation, Statistical|Evolution, Molecular|Models, Chemical|Models, Genetic|Models, Molecular|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btm022', '17282999', 'The evolution of protein sequences can be described by a stepwise process, where each step involves changes of a few amino acids. In a similar manner, the evolution of protein folds can be at least partially described by an analogous process, where each step involves comparatively simple changes affecting few secondary structure elements. A number of such evolution steps, justified by biologically confirmed examples, have previously been proposed by other researchers. However, unlike the situation with sequences, as far as we know there have been no attempts to estimate the comparative probabilities for different kinds of such structural changes.'),
(73315, 2007, 'bio', 'Accurate automated clustering of two-dimensional data for single-nucleotide polymorphism genotyping by a combination of clustering methods: evaluation by large-scale real data', 'Takitoh, Shuichi|Fujii, Shogo|Mase, Yoichi|Takasaki, Junichi|Yamazaki, Toshimasa|Ohnishi, Yozo|Yanagisawa, Masao|Nakamura, Yusuke|Kamatani, Naoyuki', 'Laboratory for Statistical Analysis, Waseda University, Shinjuku, Tokyo, Japan.|Laboratory for Statistical Analysis, Waseda University, Shinjuku, Tokyo, Japan.|Laboratory for Statistical Analysis, Waseda University, Shinjuku, Tokyo, Japan.|Laboratory for Statistical Analysis, Waseda University, Shinjuku, Tokyo, Japan.|Laboratory for Statistical Analysis, Waseda University, Shinjuku, Tokyo, Japan.|Laboratory for Statistical Analysis, Waseda University, Shinjuku, Tokyo, Japan.|Laboratory for Statistical Analysis, Waseda University, Shinjuku, Tokyo, Japan.|Laboratory for Statistical Analysis, Waseda University, Shinjuku, Tokyo, Japan.|Laboratory for Statistical Analysis, Waseda University, Shinjuku, Tokyo, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 2, 'Algorithms|Artificial Intelligence|Chromosome Mapping|Cluster Analysis|DNA Mutational Analysis|Databases, Genetic|In Situ Hybridization, Fluorescence|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Reproducibility of Results|Sensitivity and Specificity|Spectrometry, Fluorescence', 'Evaluation Studies', '10.1093/bioinformatics/btl133', '17301273', 'The Invader assay is a fluorescence-based high-throughput genotyping technology. If the output data from the Invader assay were classified automatically, then genotypes for individuals would be determined efficiently. However, existing classification methods do not necessarily yield results with the same accuracy as can be achieved by technicians. Our clustering algorithm, Genocluster, is intended to increase the proportion of data points that need not be manually corrected by technicians.'),
(73316, 2007, 'bio', 'Analyzing gene expression data in terms of gene sets: methodological issues', 'Goeman, Jelle J|Bühlmann, Peter', 'Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. j.j.goeman@lumc.nl|Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands. j.j.goeman@lumc.nl', 'Netherlands|Netherlands', 498, 'Algorithms|Artifacts|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btm051', '17303618', 'Many statistical tests have been proposed in recent years for analyzing gene expression data in terms of gene sets, usually from Gene Ontology. These methods are based on widely different methodological assumptions. Some approaches test differential expression of each gene set against differential expression of the rest of the genes, whereas others test each gene set on its own. Also, some methods are based on a model in which the genes are the sampling units, whereas others treat the subjects as the sampling units. This article aims to clarify the assumptions behind different approaches and to indicate a preferential methodology of gene set testing.'),
(73317, 2007, 'bio', 'A new JAVA interface implementation of THESIAS: testing haplotype effects in association studies', 'Tregouet, D A|Garelle, V', 'INSERM, UMR S 525 and Université Pierre et Marie Curie-Paris6, UMR S 525, Paris, France. david.tregouet@chups.jussieu.fr|INSERM, UMR S 525 and Université Pierre et Marie Curie-Paris6, UMR S 525, Paris, France. david.tregouet@chups.jussieu.fr', 'France|France', 0, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Genetic Linkage|Polymorphism, Genetic|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btm058', '17308338', 'THESIAS (Testing Haplotype EffectS In Association Studies) is a popular software for carrying haplotype association analysis in unrelated individuals. In addition to the command line interface, a graphical JAVA interface is now proposed allowing one to run THESIAS in a user-friendly manner. Besides, new functionalities have been added to THESIAS including the possibility to analyze polychotomous phenotype and X-linked polymorphisms.'),
(73318, 2007, 'bio', 'Position dependencies in transcription factor binding sites', 'Tomovic, Andrija|Oakeley, Edward J', 'Friedrich Miescher Institute for Biomedical Research, Novartis Research Foundation, Basel, Switzerland.|Friedrich Miescher Institute for Biomedical Research, Novartis Research Foundation, Basel, Switzerland.', 'Switzerland|Switzerland', 57, 'Algorithms|Base Sequence|Binding Sites|Computer Simulation|DNA|Internet|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Sequence Data|Protein Binding|Sequence Analysis, DNA|Software|Structure-Activity Relationship|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm055', '17308339', 'Most of the available tools for transcription factor binding site prediction are based on methods which assume no sequence dependence between the binding site base positions. Our primary objective was to investigate the statistical basis for either a claim of dependence or independence, to determine whether such a claim is generally true, and to use the resulting data to develop improved scoring functions for binding-site prediction.'),
(73319, 2007, 'bio', 'A multi-stage approach to clustering and imputation of gene expression profiles', 'Wong, Dorothy S V|Wong, Frederick K|Wood, Graham R', 'Department of Statistics, Macquarie University, NSW 2109, Australia. dwong@efs.mq.edu.au|Department of Statistics, Macquarie University, NSW 2109, Australia. dwong@efs.mq.edu.au|Department of Statistics, Macquarie University, NSW 2109, Australia. dwong@efs.mq.edu.au', 'Australia|Australia|Australia', 28, 'Algorithms|Artificial Intelligence|Cluster Analysis|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Software', 'Journal Article', '10.1093/bioinformatics/btm053', '17308340', 'Microarray experiments have revolutionized the study of gene expression with their ability to generate large amounts of data. This article describes an alternative to existing approaches to clustering of gene expression profiles, the key idea is to cluster in stages using a hierarchy of distance measures. This method is motivated by the way in which the human mind sorts and so groups many items. The distance measures arise from the orthogonal breakup of Euclidean distance, giving us a set of independent measures of different attributes of the gene expression profile. Interpretation of these distances is closely related to the statistical design of the microarray experiment. This clustering method not only accommodates missing data but also leads to an associated imputation method.'),
(73320, 2007, 'bio', 'HomologMiner: looking for homologous genomic groups in whole genomes', 'Hou, Minmei|Berman, Piotr|Hsu, Chih-Hao|Harris, Robert S', 'Department of Computer Science & Engineering, Penn State University, PA, USA. mhou@cse.psu.edu|Department of Computer Science & Engineering, Penn State University, PA, USA. mhou@cse.psu.edu|Department of Computer Science & Engineering, Penn State University, PA, USA. mhou@cse.psu.edu|Department of Computer Science & Engineering, Penn State University, PA, USA. mhou@cse.psu.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Molecular Sequence Data|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btm048', '17308341', 'Complex genomes contain numerous repeated sequences, and genomic duplication is believed to be a main evolutionary mechanism to obtain new functions. Several tools are available for de novo repeat sequence identification, and many approaches exist for clustering homologous protein sequences. We present an efficient new approach to identify and cluster homologous DNA sequences with high accuracy at the level of whole genomes, excluding low-complexity repeats, tandem repeats and annotated interspersed repeats. We also determine the boundaries of each group member so that it closely represents a biological unit, e.g. a complete gene, or a partial gene coding a protein domain.'),
(73321, 2007, 'bio', 'ClusterDraw web server: a tool to identify and visualize clusters of binding motifs for transcription factors', 'Papatsenko, Dmitri', 'Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA. dxp@berkeley.edu', 'United States', 0, 'Algorithms|Amino Acid Motifs|Base Sequence|Binding Sites|Cluster Analysis|Internet|Molecular Sequence Data|Protein Binding|Regulatory Elements, Transcriptional|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm047', '17308342', 'ClusterDraw is a program aimed to identification of binding sites and binding-site clusters. Major difference of the ClusterDraw from existing tools is its ability to scan a wide range of parameter values and weigh statistical significance of all possible clusters, smaller than a selected size. The program produces graphs along with decorated FASTA files. ClusterDraw web server is available at the following URL: http://flydev.berkeley.edu/cgi-bin/cld/submit.cgi'),
(73322, 2007, 'bio', 'Simulating psoriasis by altering transit amplifying cells', 'Grabe, Niels|Neuber, Karsten', 'Department of Medical Informatics, Institute of Medical Biometry and Informatics, University Hospital Heidelberg, Heidelberg, Germany. niels.grabe@med.uni-heidelberg.de|Department of Medical Informatics, Institute of Medical Biometry and Informatics, University Hospital Heidelberg, Heidelberg, Germany. niels.grabe@med.uni-heidelberg.de', 'Germany|Germany', 31, 'Cell Cycle|Cell Cycle Proteins|Cell Differentiation|Cell Proliferation|Disease Progression|Humans|Keratinocytes|Models, Biological|Psoriasis|Skin|Stem Cells', 'Journal Article', '10.1093/bioinformatics/btm042', '17308343', 'Computational models of tissue homeostasis will facilitate a deeper understanding of many diseases. They link molecular networks, cellular differentiation and the spatial and temporal organization of tissues. Here we show an approach which is able to computationally turn a healthy in silico epidermis into one with four central properties of psoriatic epidermis. We achieve this by altering a single simulation parameter in the cellular differentiation program of the simulated epidermal keratinocytes: the fractional time period during which transit amplifying cells proliferate (tau). Prolonging tau results in the four main pathological characteristics of psoriatic skin: (1) an absolute increase of the germinative compartment, (2) an absolute increase of the differentiated compartment, (3) a higher proportion of germinative cells and (4) a marked reduction in turnover time. The prolongation of tau is able to increase the proliferation capacity of the epidermal tissue without altering the cell cycle frequency.'),
(73323, 2007, 'bio', 'Continuous-index hidden Markov modelling of array CGH copy number data', 'Stjernqvist, Susann|Rydén, Tobias|Sköld, Martin|Staaf, Johan', 'Centre for Mathematical Sciences, Lund University, Lund, Sweden. susann.stjernqvist@matstat.lu.se|Centre for Mathematical Sciences, Lund University, Lund, Sweden. susann.stjernqvist@matstat.lu.se|Centre for Mathematical Sciences, Lund University, Lund, Sweden. susann.stjernqvist@matstat.lu.se|Centre for Mathematical Sciences, Lund University, Lund, Sweden. susann.stjernqvist@matstat.lu.se', 'Sweden|Sweden|Sweden|Sweden', 35, 'Artificial Intelligence|Chromosome Mapping|Computer Simulation|Databases, Genetic|Gene Dosage|Markov Chains|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm059', '17309894', 'In recent years, a range of techniques for analysis and segmentation of array comparative genomic hybridization (aCGH) data have been proposed. For array designs in which clones are of unequal lengths, are unevenly spaced or overlap, the discrete-index view typically adopted by such methods may be questionable or improved.'),
(73324, 2007, 'bio', 'Cerebral: a Cytoscape plugin for layout of and interaction with biological networks using subcellular localization annotation', 'Barsky, Aaron|Gardy, Jennifer L|Hancock, Robert E W|Munzner, Tamara', 'Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada.|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Cell Physiological Phenomena|Computer Graphics|Computer Simulation|Models, Biological|Programming Languages|Proteome|Signal Transduction|Software|Subcellular Fractions|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm057', '17309895', 'Cerebral (Cell Region-Based Rendering And Layout) is an open-source Java plugin for the Cytoscape biomolecular interaction viewer. Given an interaction network and subcellular localization annotation, Cerebral automatically generates a view of the network in the style of traditional pathway diagrams, providing an intuitive interface for the exploration of a biological pathway or system. The molecules are separated into layers according to their subcellular localization. Potential products or outcomes of the pathway can be shown at the bottom of the view, clustered according to any molecular attribute data-protein function-for example. Cerebral scales well to networks containing thousands of nodes.'),
(73325, 2007, 'bio', 'Gepard: a rapid and sensitive tool for creating dotplots on genome scale', 'Krumsiek, Jan|Arnold, Roland|Rattei, Thomas', 'Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Neuherberg, Germany. krumsiek@in.tum.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Neuherberg, Germany. krumsiek@in.tum.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Neuherberg, Germany. krumsiek@in.tum.de', 'Germany|Germany|Germany', 0, 'Algorithms|Chromosome Mapping|Computer Graphics|Sensitivity and Specificity|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm039', '17309896', 'Gepard provides a user-friendly, interactive application for the quick creation of dotplots. It utilizes suffix arrays to reduce the time complexity of dotplot calculation to Theta(m*log n). A client-server mode, which is a novel feature for dotplot creation software, allows the user to calculate dotplots and color them by functional annotation without any prior downloading of sequence or annotation data.'),
(73326, 2007, 'bio', 'Clustering by common friends finds locally significant proteins mediating modules', 'Andreopoulos, Bill|An, Aijun|Wang, Xiaogang|Faloutsos, Michalis|Schroeder, Michael', 'Biotechnological Centre, Technische Universität Dresden, Germany. williama@biotec.tu-dresden.de|Biotechnological Centre, Technische Universität Dresden, Germany. williama@biotec.tu-dresden.de|Biotechnological Centre, Technische Universität Dresden, Germany. williama@biotec.tu-dresden.de|Biotechnological Centre, Technische Universität Dresden, Germany. williama@biotec.tu-dresden.de|Biotechnological Centre, Technische Universität Dresden, Germany. williama@biotec.tu-dresden.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Cluster Analysis|Computer Simulation|Models, Biological|Multigene Family|Protein Binding|Protein Interaction Mapping|Proteins|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm064', '17314122', 'Much research has been dedicated to large-scale protein interaction networks including the analysis of scale-free topologies, network modules and the relation of domain-domain to protein-protein interaction networks. Identifying locally significant proteins that mediate the function of modules is still an open problem.'),
(73327, 2007, 'bio', 'Gene symbol disambiguation using knowledge-based profiles', 'Xu, Hua|Fan, Jung-Wei|Hripcsak, George|Mendonça, Eneida A|Markatou, Marianthi|Friedman, Carol', 'Department of Biomedical Informatics, Columbia University, New York City, New York, USA.|Department of Biomedical Informatics, Columbia University, New York City, New York, USA.|Department of Biomedical Informatics, Columbia University, New York City, New York, USA.|Department of Biomedical Informatics, Columbia University, New York City, New York, USA.|Department of Biomedical Informatics, Columbia University, New York City, New York, USA.|Department of Biomedical Informatics, Columbia University, New York City, New York, USA.', 'United States|United States|United States|United States|United States|United States', 36, 'Abstracting and Indexing as Topic|Artificial Intelligence|Database Management Systems|Databases, Genetic|Genes|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Periodicals as Topic|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btm056', '17314123', 'The ambiguity of biomedical entities, particularly of gene symbols, is a big challenge for text-mining systems in the biomedical domain. Existing knowledge sources, such as Entrez Gene and the MEDLINE database, contain information concerning the characteristics of a particular gene that could be used to disambiguate gene symbols.'),
(73328, 2007, 'bio', 'SwS: a solvation web service for nucleic acids', 'Auffinger, Pascal|Hashem, Yaser', 'A.R.N., Université Louis Pasteur, IBMC-CNRS, Strasbourg, France. p.auffinger@ibmc.u-strasbg.fr|A.R.N., Université Louis Pasteur, IBMC-CNRS, Strasbourg, France. p.auffinger@ibmc.u-strasbg.fr', 'France|France', 32, 'Algorithms|Computer Simulation|Crystallography|Internet|Models, Chemical|Models, Molecular|Nucleic Acid Conformation|Nucleic Acids|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btm067', '17324939', 'SwS, based on a statistical analysis of crystallographic structures deposited in the NDB, is designed to provide an exhaustive overview of the solvation of nucleic acid structural elements through the generation of 3D solvent density maps. A first version (v1.0) of this web service focuses on the interaction of DNA, RNA and hybrid base pairs linked by two or three hydrogen bonds with water, cations and/or anions. Data provided by SwS are updated on a weekly basis and can be used by: (i) those involved in molecular dynamics simulation studies for validation purposes, (ii) crystallographers for help in the interpretation of solvent density maps, and all those involved in (iii) drug design and, more generally, in (iv) nucleic acid structural studies. SwS provides also statistical data related to the frequency of occurrence of different types of base pairs in crystallographic structures and the conformation of the involved nucleotides. This web service has been designed to allow a maximum of flexibility in terms of queries and has also been developed with didactic considerations in mind.'),
(73329, 2007, 'bio', 'Enabling high-throughput data management for systems biology: the Bioinformatics Resource Manager', 'Shah, Anuj R|Singhal, Mudita|Klicker, Kyle R|Stephan, Eric G|Wiley, H Steven|Waters, Katrina M', 'Biomolecular Systems Initiative, Pacific Northwest National Laboratory, Richland, WA, USA. anuj.shah@pnl.gov|Biomolecular Systems Initiative, Pacific Northwest National Laboratory, Richland, WA, USA. anuj.shah@pnl.gov|Biomolecular Systems Initiative, Pacific Northwest National Laboratory, Richland, WA, USA. anuj.shah@pnl.gov|Biomolecular Systems Initiative, Pacific Northwest National Laboratory, Richland, WA, USA. anuj.shah@pnl.gov|Biomolecular Systems Initiative, Pacific Northwest National Laboratory, Richland, WA, USA. anuj.shah@pnl.gov|Biomolecular Systems Initiative, Pacific Northwest National Laboratory, Richland, WA, USA. anuj.shah@pnl.gov', 'United States|United States|United States|United States|United States|United States', 22, 'Computational Biology|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Proteomics|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btm031', '17324940', 'The Bioinformatics Resource Manager (BRM) is a software environment that provides the user with data management, retrieval and integration capabilities. Designed in collaboration with biologists, BRM simplifies mundane analysis tasks of merging microarray and proteomic data across platforms, facilitates integration of users data with functional annotation and interaction data from public sources and provides connectivity to visual analytic tools through reformatting of the data for easy import or dynamic launching capability. BRM is developed using Java and other open-source technologies for free distribution.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73330, 2007, 'bio', 'Multiple structural alignment and clustering of RNA sequences', 'Torarinsson, Elfar|Havgaard, Jakob H|Gorodkin, Jan', 'Division of Genetics and Bioinformatics, IBHV and Center for Bioinformatics, University of Copenhagen, Frederiksberg C, Denmark.|Division of Genetics and Bioinformatics, IBHV and Center for Bioinformatics, University of Copenhagen, Frederiksberg C, Denmark.|Division of Genetics and Bioinformatics, IBHV and Center for Bioinformatics, University of Copenhagen, Frederiksberg C, Denmark.', 'Denmark|Denmark|Denmark', 115, 'Algorithms|Base Sequence|Cluster Analysis|Molecular Sequence Data|RNA|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btm049', '17324941', 'An apparent paradox in computational RNA structure prediction is that many methods, in advance, require a multiple alignment of a set of related sequences, when searching for a common structure between them. However, such a multiple alignment is hard to obtain even for few sequences with low sequence similarity without simultaneously folding and aligning them. Furthermore, it is of interest to conduct a multiple alignment of RNA sequence candidates found from searching as few as two genomic sequences.'),
(73331, 2007, 'bio', 'rh_tsp_map 30: end-to-end radiation hybrid mapping with improved speed and quality control', 'Schäffer, Alejandro A|Rice, Edward Stallknecht|Cook, William|Agarwala, Richa', 'National Center for Biotechnology Information, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.', 'United States|United States|United States|United States', 16, 'Algorithms|Base Sequence|Genetic Markers|Molecular Sequence Data|Quality Control|Radiation Hybrid Mapping|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btm077', '17332018', 'rh_tsp_map is a software package for computing radiation hybrid (RH) maps and for integrating physical and genetic maps. It solves the central mapping instances by reducing them to the traveling salesman problem (TSP) and using a modification of the CONCORDE package to solve the TSP instances. We present some of the features added between the initial rh_tsp_map version 1.0 and the current version 3.0, emphasizing the automation of many steps and addition of various checks designed to find problems with the input data. Iterations of improved input data followed by fast re-computation of the maps improves the quality of the final maps.'),
(73332, 2007, 'bio', 'COBALT: constraint-based alignment tool for multiple protein sequences', 'Papadopoulos, Jason S|Agarwala, Richa', 'National Center for Biotechnology Information, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.', 'United States|United States', 531, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/btm076', '17332019', 'A tool that simultaneously aligns multiple protein sequences, automatically utilizes information about protein domains, and has a good compromise between speed and accuracy will have practical advantages over current tools.'),
(73333, 2007, 'bio', 'CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes', 'Parra, Genis|Bradnam, Keith|Korf, Ian', 'UC Davis Genome Center, University of California Davis, Davis, CA 95616, USA.|UC Davis Genome Center, University of California Davis, Davis, CA 95616, USA.|UC Davis Genome Center, University of California Davis, Davis, CA 95616, USA.', 'United States|United States|United States', 1189, 'Algorithms|Animals|Base Sequence|Chromosome Mapping|Documentation|Humans|Molecular Sequence Data|Proteome|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btm071', '17332020', 'The numbers of finished and ongoing genome projects are increasing at a rapid rate, and providing the catalog of genes for these new genomes is a key challenge. Obtaining a set of well-characterized genes is a basic requirement in the initial steps of any genome annotation process. An accurate set of genes is needed in order to learn about species-specific properties, to train gene-finding programs, and to validate automatic predictions. Unfortunately, many new genome projects lack comprehensive experimental data to derive a reliable initial set of genes.'),
(73334, 2007, 'bio', 'Phylogenetic exploration of bacterial genomic rearrangements', 'Fremez, Romain|Faraut, Thomas|Fichant, Gwennaele|Gouzy, Jérôme|Quentin, Yves', 'Université Paul Sabatier, CNRS-LMGM, UMR 5100, Toulouse Cedex, France.|Université Paul Sabatier, CNRS-LMGM, UMR 5100, Toulouse Cedex, France.|Université Paul Sabatier, CNRS-LMGM, UMR 5100, Toulouse Cedex, France.|Université Paul Sabatier, CNRS-LMGM, UMR 5100, Toulouse Cedex, France.|Université Paul Sabatier, CNRS-LMGM, UMR 5100, Toulouse Cedex, France.', 'France|France|France|France|France', 4, 'Computer Graphics|Conserved Sequence|Evolution, Molecular|Genome, Bacterial|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm070', '17332021', 'We present a graphical tool dedicated to the exploration of bacterial genome rearrangements. The principle of this exploration relies on the reconstruction of ancestral genomes at each internal node of a gene-order-based phylogenetic tree. This tool allows the selection of internal nodes to visualize the rearrangements between the inferred chromosome of this node and its direct descendant on the tree.'),
(73335, 2007, 'bio', 'NucPred--predicting nuclear localization of proteins', 'Brameier, Markus|Krings, Andrea|MacCallum, Robert M', 'Bioinformatics Research Center (BiRC), University of Aarhus, Aarhus C, Denmark.|Bioinformatics Research Center (BiRC), University of Aarhus, Aarhus C, Denmark.|Bioinformatics Research Center (BiRC), University of Aarhus, Aarhus C, Denmark.', 'Denmark|Denmark|Denmark', 211, 'Algorithms|Amino Acid Sequence|Cell Nucleus|Molecular Sequence Data|Nuclear Proteins|Pattern Recognition, Automated|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btm066', '17332022', 'NucPred analyzes patterns in eukaryotic protein sequences and predicts if a protein spends at least some time in the nucleus or no time at all. Subcellular location of proteins represents functional information, which is important for understanding protein interactions, for the diagnosis of human diseases and for drug discovery. NucPred is a novel web tool based on regular expression matching and multiple program classifiers induced by genetic programming. A likelihood score is derived from the programs for each input sequence and each residue position. Different forms of visualization are provided to assist the detection of nuclear localization signals (NLSs). The NucPred server also provides access to additional sources of biological information (real and predicted) for a better validation and interpretation of results.'),
(73336, 2007, 'bio', 'Improving metabolic flux estimation via evolutionary optimization for convex solution space', 'Chen, Jiusheng|Zheng, Haoran|Liu, Haiyan|Niu, Junqing|Liu, Jianping|Shen, Tie|Rui, Bin|Shi, Yunyu', 'Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China.|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China.|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China.|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China.|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China.|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China.|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China.|Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China.', 'China|China|China|China|China|China|China|China', 6, 'Algorithms|Carbon|Computer Simulation|Energy Metabolism|Escherichia coli|Escherichia coli Proteins|Magnetic Resonance Spectroscopy|Models, Biological|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/btm050', '17332023', 'Flux estimation by using (13) C-labeling pattern information of metabolites is currently the only method that can give accurate, detailed quantification of all intracellular fluxes in the central metabolism of a microorganism. In essence, it corresponds to a constrained optimization problem which minimizes a weighted distance between measured and simulated results. Characteristics, such as existence of multiple local minima, non-linear and non-differentiable make this problem a special difficulty.'),
(73337, 2007, 'bio', 'Microarray blob-defect removal improves array analysis', 'Song, Jun S|Maghsoudi, Kaveh|Li, Wei|Fox, Edward|Quackenbush, John|Shirley Liu, X', 'Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health, Boston, MA, USA.', 'United States|United States|United States|United States|United States|United States', 17, 'Algorithms|Artifacts|Image Enhancement|Image Interpretation, Computer-Assisted|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm043', '17332024', 'New generation Affymetrix oligonucleotide microarrays often have blob-like image defects that will require investigators to either repeat their hybridization assays or analyze their data with the defects left in place. We investigated the effect of analyzing a spike-in experiment on Affymetrix ENCODE tiling arrays in the presence of simulated blobs covering between 1 and 9% of the array area. Using two different ChIP-chip tiling array analysis programs (Affymetrix tiling array software, TAS, and model-based analysis of tiling arrays, MAT), we found that even the smallest blob defects significantly decreased the sensitivity and increased the false discovery rate (FDR) of the spike-in target prediction.'),
(73338, 2007, 'bio', 'PhyloGena--a user-friendly system for automated phylogenetic annotation of unknown sequences', 'Hanekamp, Kristian|Bohnebeck, Uta|Beszteri, Bánk|Valentin, Klaus', 'Center for Computing Technologies (TZI), P.O.B. 330440, D-28334 Bremen, Germany.|Center for Computing Technologies (TZI), P.O.B. 330440, D-28334 Bremen, Germany.|Center for Computing Technologies (TZI), P.O.B. 330440, D-28334 Bremen, Germany.|Center for Computing Technologies (TZI), P.O.B. 330440, D-28334 Bremen, Germany.', 'Germany|Germany|Germany|Germany', 27, 'Algorithms|Artificial Intelligence|Base Sequence|Chromosome Mapping|Molecular Sequence Data|Pattern Recognition, Automated|Phylogeny|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm016', '17332025', 'Phylogenomic approaches towards functional and evolutionary annotation of unknown sequences have been suggested to be superior to those based only on pairwise local alignments. User-friendly software tools making the advantages of phylogenetic annotation available for the ever widening range of bioinformatically uninitiated biologists involved in genome/EST annotation projects are, however, not available. We were particularly confronted with this issue in the annotation of sequences from different groups of complex algae originating from secondary endosymbioses, where the identification of the phylogenetic origin of genes is often more problematic than in taxa well represented in the databases (e.g. animals, plants or fungi).'),
(73339, 2007, 'bio', 'GAPWM: a genetic algorithm method for optimizing a position weight matrix', 'Li, Leping|Liang, Yu|Bass, Robert L', 'Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA. li3@niehs.nih.gov|Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA. li3@niehs.nih.gov|Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA. li3@niehs.nih.gov', 'United States|United States|United States', 31, 'Algorithms|Animals|Binding Sites|Chromatin Immunoprecipitation|Humans|Mice|Models, Genetic|Octamer Transcription Factor-3|Tumor Suppressor Protein p53', 'Journal Article', '10.1093/bioinformatics/btm080', '17341493', 'Position weight matrices (PMWs) are simple models commonly used in motif-finding algorithms to identify short functional elements, such as cis-regulatory motifs, on genes. When few experimentally verified motifs are available, estimation of the PWM may be poor. The resultant PWM may not reliably discriminate a true motif from a false one. While experimentally identifying such motifs remains time-consuming and expensive, low-resolution binding data from techniques such as ChIP-on-chip and ChIP-PET have become available. We propose a novel but simple method to improve a poorly estimated PWM using ChIP data.'),
(73340, 2007, 'bio', 'Comparative annotation of viral genomes with non-conserved gene structure', 'de Groot, Saskia|Mailund, Thomas|Hein, Jotun', 'Department of Statistics, University of Oxford, UK. degroot@stats.ox.ac.uk|Department of Statistics, University of Oxford, UK. degroot@stats.ox.ac.uk|Department of Statistics, University of Oxford, UK. degroot@stats.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 8, 'Algorithms|Base Sequence|Chromosome Mapping|Conserved Sequence|Documentation|Evolution, Molecular|Genome, Viral|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Species Specificity', 'Evaluation Studies', '10.1093/bioinformatics/btm078', '17341494', 'Detecting genes in viral genomes is a complex task. Due to the biological necessity of them being constrained in length, RNA viruses in particular tend to code in overlapping reading frames. Since one amino acid is encoded by a triplet of nucleic acids, up to three genes may be coded for simultaneously in one direction. Conventional hidden Markov model (HMM)-based gene-finding algorithms may typically find it difficult to identify multiple coding regions, since in general their topologies do not allow for the presence of overlapping or nested genes. Comparative methods have therefore been restricted to likelihood ratio tests on potential regions as to being double or single coding, using the fact that the constrictions forced upon multiple-coding nucleotides will result in atypical sequence evolution. Exploiting these same constraints, we present an HMM based gene-finding program, which allows for coding in unidirectional nested and overlapping reading frames, to annotate two homologous aligned viral genomes. Our method does not insist on conserved gene structure between the two sequences, thus making it applicable for the pairwise comparison of more distantly related sequences.'),
(73341, 2007, 'bio', 'Metabolic network properties help assign weights to elementary modes to understand physiological flux distributions', 'Wang, Qingzhao|Yang, Yudi|Ma, Hongwu|Zhao, Xueming', 'Metabolic Engineering Laboratory, Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin, Peoples Republic of China. Wangqingzhao@eyou.com|Metabolic Engineering Laboratory, Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin, Peoples Republic of China. Wangqingzhao@eyou.com|Metabolic Engineering Laboratory, Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin, Peoples Republic of China. Wangqingzhao@eyou.com|Metabolic Engineering Laboratory, Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin, Peoples Republic of China. Wangqingzhao@eyou.com', 'China|China|China|China', 7, 'Algorithms|Computer Simulation|Energy Metabolism|Models, Biological|Proteome|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/btm074', '17341495', 'Elementary modes (EMs) analysis has been well established. The existing methodologies for assigning weights to EMs cannot be directly applied for large-scale metabolic networks, since the tremendous number of modes would make the computation a time-consuming or even an impossible mission. Therefore, developing more efficient methods to deal with large set of EMs is urgent.'),
(73342, 2007, 'bio', 'Andante: reducing side-chain rotamer search space during comparative modeling using environment-specific substitution probabilities', 'Smith, Richard E|Lovell, Simon C|Burke, David F|Montalvao, Rinaldo W|Blundell, Tom L', 'Department of Biochemistry, University of Cambridge, Cambridge, UK. res50@mole.bio.cam.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, UK. res50@mole.bio.cam.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, UK. res50@mole.bio.cam.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, UK. res50@mole.bio.cam.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, UK. res50@mole.bio.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 45, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Computer Simulation|Models, Chemical|Models, Statistical|Molecular Sequence Data|Mutagenesis, Site-Directed|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btm073', '17341496', 'The accurate placement of side chains in computational protein modeling and design involves the searching of vast numbers of rotamer combinations.'),
(73343, 2007, 'bio', 'AMPer: a database and an automated discovery tool for antimicrobial peptides', 'Fjell, Christopher D|Hancock, Robert E W|Cherkasov, Artem', 'Division of Infectious Diseases, Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada. cfjell@interchange.ubc.ca|Division of Infectious Diseases, Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada. cfjell@interchange.ubc.ca|Division of Infectious Diseases, Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada. cfjell@interchange.ubc.ca', 'Canada|Canada|Canada', 146, 'Algorithms|Amino Acid Sequence|Antimicrobial Cationic Peptides|Artificial Intelligence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Sequence Analysis, Protein|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btm068', '17341497', 'Increasing antibiotics resistance in human pathogens represents a pressing public health issue worldwide for which novel antibiotic therapies based on antimicrobial peptides (AMPs) may offer one possible solution. In the current study, we utilized publicly available data on AMPs to construct hidden Markov models (HMMs) that enable recognition of individual classes of antimicrobials peptides (such as defensins, cathelicidins, cecropins, etc.) with up to 99% accuracy and can be used for discovering novel AMP candidates.'),
(73344, 2007, 'bio', 'De novo peptide sequencing using ion peak intensity and amino acid cleavage intensity ratio', 'Kanazawa, Mitsuhiro|Anyoji, Hisae|Ogiwara, Atsushi|Nagashima, Umpei', 'Reifycs Inc., Tokyo, Japan. kanazawa@reifycs.com|Reifycs Inc., Tokyo, Japan. kanazawa@reifycs.com|Reifycs Inc., Tokyo, Japan. kanazawa@reifycs.com|Reifycs Inc., Tokyo, Japan. kanazawa@reifycs.com', 'Japan|Japan|Japan|Japan', 0, 'Algorithms|Amino Acid Sequence|Amino Acids|Computer Simulation|Mass Spectrometry|Models, Chemical|Molecular Sequence Data|Peptide Mapping|Peptides|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btm062', '17341498', 'Peptide-sequencing methods by mass spectrum use the following two approaches: database searching and de novo sequencing. The database-searching approach is convenient, however, in cases wherein the corresponding sequences are not included in the databases, the exact identification is difficult. On the other hand, in the case of de novo sequencing, no preliminary information is necessary, however, continuous amino acid sequence peaks and the differentiation of these peaks are required. It is, however, very difficult to obtain and differentiate the peaks of all amino acids by using an actual spectrum. We propose a novel de novo sequencing approach using not only mass-to-charge ratio but also ion peak intensity and amino acid cleavage intensity ratio (CIR).'),
(73345, 2007, 'bio', 'Simulating Epstein-Barr virus infection with C-ImmSim', 'Castiglione, Filippo|Duca, Karen|Jarrah, Abdul|Laubenbacher, Reinhard|Hochberg, Donna|Thorley-Lawson, David', 'Istituto Applicazioni del Calcolo M. Picone-CNR, Rome, Italy.|Istituto Applicazioni del Calcolo M. Picone-CNR, Rome, Italy.|Istituto Applicazioni del Calcolo M. Picone-CNR, Rome, Italy.|Istituto Applicazioni del Calcolo M. Picone-CNR, Rome, Italy.|Istituto Applicazioni del Calcolo M. Picone-CNR, Rome, Italy.|Istituto Applicazioni del Calcolo M. Picone-CNR, Rome, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Computer Simulation|Epstein-Barr Virus Infections|Herpesvirus 4, Human|Humans|Immunity, Innate|Models, Immunological|Models, Statistical|Software|Stochastic Processes|T-Lymphocytes|Virus Activation|Virus Latency', 'Journal Article', '10.1093/bioinformatics/btm044', '17341499', 'Epstein-Barr virus (EBV) infects greater than 90% of humans benignly for life but can be associated with tumors. It is a uniquely human pathogen that is amenable to quantitative analysis, however, there is no applicable animal model. Computer models may provide a virtual environment to perform experiments not possible in human volunteers.'),
(73346, 2007, 'bio', 'Glycan classification with tree kernels', 'Yamanishi, Yoshihiro|Bach, Francis|Vert, Jean-Philippe', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. yoshi@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. yoshi@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. yoshi@kuicr.kyoto-u.ac.jp', 'Japan|Japan|Japan', 0, 'Algorithms|Carbohydrate Conformation|Carbohydrate Sequence|Erythrocytes|Humans|Polysaccharides|Xenopus Proteins', 'Journal Article', '10.1093/bioinformatics/btm090', '17344232', 'Glycans are covalent assemblies of sugar that play crucial roles in many cellular processes. Recently, comprehensive data about the structure and function of glycans have been accumulated, therefore the need for methods and algorithms to analyze these data is growing fast.'),
(73347, 2007, 'bio', 'BioGuideSRS: querying multiple sources with a user-centric perspective', 'Cohen-Boulakia, Sarah|Biton, Olivier|Davidson, Susan|Froidevaux, Christine', 'Laboratoire de Recherche en Informatique, CNRS UMR 8023, Université Paris-Sud XI, 91405 Orsay, France. sarahcb@seas.upenn.edu|Laboratoire de Recherche en Informatique, CNRS UMR 8023, Université Paris-Sud XI, 91405 Orsay, France. sarahcb@seas.upenn.edu|Laboratoire de Recherche en Informatique, CNRS UMR 8023, Université Paris-Sud XI, 91405 Orsay, France. sarahcb@seas.upenn.edu|Laboratoire de Recherche en Informatique, CNRS UMR 8023, Université Paris-Sud XI, 91405 Orsay, France. sarahcb@seas.upenn.edu', 'France|France|France|France', 21, 'Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm088', '17344233', 'Biologists are frequently faced with the problem of integrating information from multiple heterogeneous sources with their own experimental data. Given the large number of public sources, it is difficult to choose which sources to integrate without assistance. When doing this manually, biologists differ in their preferences concerning the sources to be queried as well as the strategies, i.e. the querying process they follow for navigating through the sources. In response to these findings, we have developed BioGuide to assist scientists search for relevant data within external sources while taking their preferences and strategies into account. In this article, we present BioGuideSRS, a user-friendly system which automatically retrieves instances of data by using BioGuide on top of the sequence retrieval system (SRS). BioGuideSRS is an Applet that can be run from its web page on any system with Java 5.0.'),
(73348, 2007, 'bio', 'A new method to measure the semantic similarity of GO terms', 'Wang, James Z|Du, Zhidian|Payattakool, Rapeeporn|Yu, Philip S|Chen, Chin-Fu', 'School of Computing, Clemson University, Clemson, SC 29634, USA. jzwang@cs.clemson.edu|School of Computing, Clemson University, Clemson, SC 29634, USA. jzwang@cs.clemson.edu|School of Computing, Clemson University, Clemson, SC 29634, USA. jzwang@cs.clemson.edu|School of Computing, Clemson University, Clemson, SC 29634, USA. jzwang@cs.clemson.edu|School of Computing, Clemson University, Clemson, SC 29634, USA. jzwang@cs.clemson.edu', 'United States|United States|United States|United States|United States', 613, 'Algorithms|Computational Biology|Databases, Genetic|Humans|Semantics|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btm087', '17344234', 'Although controlled biochemical or biological vocabularies, such as Gene Ontology (GO) (http://www.geneontology.org), address the need for consistent descriptions of genes in different data sources, there is still no effective method to determine the functional similarities of genes based on gene annotation information from heterogeneous data sources.'),
(73349, 2007, 'bio', 'ABCGrid: Application for Bioinformatics Computing Grid', 'Sun, Ying|Zhao, Shuqi|Yu, Huashan|Gao, Ge|Luo, Jingchu', 'Center for Bioinformatics, National Laboratory of Plant Genetic Engineering and Protein Engineering and College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Plant Genetic Engineering and Protein Engineering and College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Plant Genetic Engineering and Protein Engineering and College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Plant Genetic Engineering and Protein Engineering and College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Plant Genetic Engineering and Protein Engineering and College of Life Sciences, Peking University, Beijing, PR China.', 'China|China|China|China|China', 0, 'Computational Biology|Computing Methodologies|Databases, Genetic|Information Storage and Retrieval|Internet|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btm086', '17344235', 'We have developed a package named Application for Bioinformatics Computing Grid (ABCGrid). ABCGrid was designed for biology laboratories to use heterogeneous computing resources and access bioinformatics applications from one master node. ABCGrid is very easy to install and maintain at the premise of robustness and high performance. We implement a mechanism to install and update all applications and databases in worker nodes automatically to reduce the workload of manual maintenance. We use a backup task method and self-adaptive job dispatch approach to improve performance. Currently, ABCGrid integrates NCBI_BLAST, Hmmpfam and CE, running on a number of computing platforms including UNIX/Linux, Windows and Mac OS X.'),
(73350, 2007, 'bio', 'EuSplice: a unified resource for the analysis of splice signals and alternative splicing in eukaryotic genes', 'Bhasi, Ashwini|Pandey, Ram Vinay|Utharasamy, Suriya Prabha|Senapathy, Periannan', 'Department of Human Genetics, Genome Technologies, Inc., 8000 Excelsior Drive, Madison, WI 53717, USA.|Department of Human Genetics, Genome Technologies, Inc., 8000 Excelsior Drive, Madison, WI 53717, USA.|Department of Human Genetics, Genome Technologies, Inc., 8000 Excelsior Drive, Madison, WI 53717, USA.|Department of Human Genetics, Genome Technologies, Inc., 8000 Excelsior Drive, Madison, WI 53717, USA.', 'United States|United States|United States|United States', 18, 'Alternative Splicing|Computational Biology|Data Interpretation, Statistical|Databases, Genetic|Evolution, Molecular|Fungal Proteins|Genes, Fungal|Genome|Genomics|Internet|Models, Genetic|RNA Splicing|RNA, Messenger|Software|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btm084', '17344236', 'Despite increased availability of genome annotation data, a comprehensive resource for in-depth analysis of splice signal distributions and alternative splicing (AS) patterns in eukaryote genomes is still lacking. To meet this need, we have developed EuSplice--a unique splice-centric database which provides reliable splice signal and AS information for 23 eukaryotes.'),
(73351, 2007, 'bio', 'Metabolic systems cost-benefit analysis for interpreting network structure and regulation', 'Carlson, Ross P', 'Department of Chemical and Biological Engineering, Center for Biofilm Engineering, Montana State University, Bozeman, MT 59717, USA. rossc@coe.montana.edu [corrected].', 'United States', 39, 'Biological Evolution|Computer Simulation|Escherichia coli|Metabolic Networks and Pathways|Models, Biological|Proteome|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btm082', '17344237', 'Interpretation of bioinformatics data in terms of cellular function is a major challenge facing systems biology. This question is complicated by robust metabolic networks filled with structural features like parallel pathways and isozymes. Under conditions of nutrient sufficiency, metabolic networks are well known to be regulated for thermodynamic efficiency however, efficient biochemical pathways are anabolically expensive to construct. While parameters like thermodynamic efficiency have been extensively studied, a systems-based analysis of anabolic proteome synthesis costs and the cellular function implications of these costs has not been reported.'),
(73352, 2007, 'bio', 'Pooling mRNA in microarray experiments and its effect on power', 'Zhang, Wuyan|Carriquiry, Alicia|Nettleton, Dan|Dekkers, Jack C M', 'Department of Statistics, Iowa State University, USA.|Department of Statistics, Iowa State University, USA.|Department of Statistics, Iowa State University, USA.|Department of Statistics, Iowa State University, USA.', 'United States|United States|United States|United States', 40, 'Gene Expression Profiling|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|RNA, Messenger|Research Design', 'Journal Article', '10.1093/bioinformatics/btm081', '17344238', 'Microarrays can simultaneously measure the expression levels of many genes and are widely applied to study complex biological problems at the genetic level. To contain costs, instead of obtaining a microarray on each individual, mRNA from several subjects can be first pooled and then measured with a single array. mRNA pooling is also necessary when there is not enough mRNA from each subject. Several studies have investigated the impact of pooling mRNA on inferences about gene expression, but have typically modeled the process of pooling as if it occurred in some transformed scale. This assumption is unrealistic.'),
(73353, 2007, 'bio', 'Analyzing microarray data using CLANS', 'Frickey, Tancred|Weiller, Georg', 'ARC Centre of Excellence for Interactive Legume Research and Bioinformatics Laboratory, Genomic Interactions Group, Research School of Biological Sciences, Australian National University, Canberra, ACT, Australia|ARC Centre of Excellence for Interactive Legume Research and Bioinformatics Laboratory, Genomic Interactions Group, Research School of Biological Sciences, Australian National University, Canberra, ACT, Australia', 'Australia|Australia', 0, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm079', '17344239', 'Analysis of microarray experiments is complicated by the huge amount of data involved. Searching for groups of co-expressed genes is akin to searching for protein families in a database as, in both cases, small subsets of genes with similar features are to be found within vast quantities of data. CLANS was originally developed to find protein families in large sets of amino acid sequences where the amount of data involved made phylogenetic approaches overly cumbersome. We present a number of improvements that greatly extend the previous version of CLANS and show its application to microarray data as well as its ability of incorporating additional information to facilitate interactive analysis.'),
(73354, 2007, 'bio', 'Codelink: an R package for analysis of GE healthcare gene expression bioarrays', 'Diez, Diego|Alvarez, Rebeca|Dopazo, Ana', 'Instituto de Investigaciones Biomédicas Alberto Sols, Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid, Madrid, Spain. diez@kuicr.kyoto-u.ac.jp|Instituto de Investigaciones Biomédicas Alberto Sols, Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid, Madrid, Spain. diez@kuicr.kyoto-u.ac.jp|Instituto de Investigaciones Biomédicas Alberto Sols, Consejo Superior de Investigaciones Cientificas-Universidad Autonoma de Madrid, Madrid, Spain. diez@kuicr.kyoto-u.ac.jp', 'Spain|Spain|Spain', 15, 'Algorithms|Computer Graphics|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Programming Languages|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btm072', '17344240', 'Microarray-based expression profiles have become a standard methodology in any high-throughput analysis. Several commercial platforms are available, each with its strengths and weaknesses. The R platform for statistical analysis and graphics is a powerful environment for the analysis of microarray data, because it has many integrated statistical methods available as well as the specialized microarray analysis project Bioconductor. Many packages have been added in the last few years increasing the range of possible analysis. Here, we report the availability of a package for reading and analyzing data from GE Healthcare Gene Expression Bioarrays within the R environment.'),
(73355, 2007, 'bio', 'pcaMethods--a bioconductor package providing PCA methods for incomplete data', 'Stacklies, Wolfram|Redestig, Henning|Scholz, Matthias|Walther, Dirk|Selbig, Joachim', 'CAS-MPG Partner Institute for Comp. Biology, Shanghai, China.|CAS-MPG Partner Institute for Comp. Biology, Shanghai, China.|CAS-MPG Partner Institute for Comp. Biology, Shanghai, China.|CAS-MPG Partner Institute for Comp. Biology, Shanghai, China.|CAS-MPG Partner Institute for Comp. Biology, Shanghai, China.', 'China|China|China|China|China', 479, 'Algorithms|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Sample Size|Software', 'Evaluation Studies', '10.1093/bioinformatics/btm069', '17344241', 'pcaMethods is a Bioconductor compliant library for computing principal component analysis (PCA) on incomplete data sets. The results can be analyzed directly or used to estimate missing values to enable the use of missing value sensitive statistical methods. The package was mainly developed with microarray and metabolite data sets in mind, but can be applied to any other incomplete data set as well.'),
(73356, 2007, 'bio', 'From structure to dynamics of metabolic pathways: application to the plant mitochondrial TCA cycle', 'Steuer, Ralf|Nesi, Adriano Nunes|Fernie, Alisdair R|Gross, Thilo|Blasius, Bernd|Selbig, Joachim', 'University Potsdam, Institute for Biochemistry and Biology, Haus 20, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Institute for Biochemistry and Biology, Haus 20, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Institute for Biochemistry and Biology, Haus 20, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Institute for Biochemistry and Biology, Haus 20, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Institute for Biochemistry and Biology, Haus 20, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Institute for Biochemistry and Biology, Haus 20, Germany. steuer@agnld.uni-potsdam.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Citric Acid Cycle|Computer Simulation|Metabolic Clearance Rate|Mitochondria|Mitochondrial Proteins|Models, Biological|Plant Leaves|Plant Proteins|Plants', 'Journal Article', '10.1093/bioinformatics/btm065', '17344242', 'Mitochondrial metabolism, dominated by the reactions of the tricarboxylic acid (TCA) cycle, is of vital importance for a wide range of metabolic processes. In particular for autotrophic tissue, such as plant leaves, the TCA cycle marks the point of divergence of anabolic pathways and plays an essential role in biosynthesis. However, despite extensive knowledge about its stoichiometric properties, the function and the dynamical capabilities of the TCA cycle remain largely unknown.'),
(73357, 2007, 'bio', 'MedicCyc: a biochemical pathway database for Medicago truncatula', 'Urbanczyk-Wochniak, Ewa|Sumner, Lloyd W', 'The Samuel Roberts Noble Foundation, Inc., Ardmore, OK 73401, USA.|The Samuel Roberts Noble Foundation, Inc., Ardmore, OK 73401, USA.', 'United States|United States', 68, 'Computer Graphics|Computer Simulation|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Medicago truncatula|Models, Biological|Plant Proteins|Proteome|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm040', '17344243', 'There is an imperative need to integrate functional genomics data to obtain a more comprehensive systems-biology view of the results. We believe that this is best achieved through the visualization of data within the biological context of metabolic pathways. Accordingly, metabolic pathway reconstruction was used to predict the metabolic composition for Medicago truncatula and these pathways were engineered to enable the correlated visualization of integrated functional genomics data.'),
(73358, 2007, 'bio', 'Discovery of microRNA-mRNA modules via population-based probabilistic learning', 'Joung, Je-Gun|Hwang, Kyu-Baek|Nam, Jin-Wu|Kim, Soo-Jin|Zhang, Byoung-Tak', 'Center for Bioinformation Technology, Seoul National University, Seoul, Korea.|Center for Bioinformation Technology, Seoul National University, Seoul, Korea.|Center for Bioinformation Technology, Seoul National University, Seoul, Korea.|Center for Bioinformation Technology, Seoul National University, Seoul, Korea.|Center for Bioinformation Technology, Seoul National University, Seoul, Korea.', '-|-|-|-|-', 0, 'Artificial Intelligence|Base Sequence|Binding Sites|Computer Simulation|Evolution, Molecular|Genetics, Population|MicroRNAs|Models, Genetic|Molecular Sequence Data|Pattern Recognition, Automated|RNA, Messenger|Sequence Analysis, RNA', 'Evaluation Studies', '10.1093/bioinformatics/btm045', '17350973', 'MicroRNAs (miRNAs) and mRNAs constitute an important part of gene regulatory networks, influencing diverse biological phenomena. Elucidating closely related miRNAs and mRNAs can be an essential first step towards the discovery of their combinatorial effects on different cellular states. Here, we propose a probabilistic learning method to identify synergistic miRNAs involving regulation of their condition-specific target genes (mRNAs) from multiple information sources, i.e. computationally predicted target genes of miRNAs and their respective expression profiles.'),
(73359, 2007, 'bio', 'iPTREE-STAB: interpretable decision tree based method for predicting protein stability changes upon mutations', 'Huang, Liang-Tsung|Gromiha, M Michael|Ho, Shinn-Ying', 'Department of Computer Science and Information Engineering, Ming-Dao University, Changhua 523, Taiwan.|Department of Computer Science and Information Engineering, Ming-Dao University, Changhua 523, Taiwan.|Department of Computer Science and Information Engineering, Ming-Dao University, Changhua 523, Taiwan.', '-|-|-', 0, 'Algorithms|Amino Acid Substitution|Mutation|Protein Conformation|Proteins|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btm100', '17379687', 'We have developed a web server, iPTREE-STAB for discriminating the stability of proteins (stabilizing or destabilizing) and predicting their stability changes (delta deltaG) upon single amino acid substitutions from amino acid sequence. The discrimination and prediction are mainly based on decision tree coupled with adaptive boosting algorithm, and classification and regression tree, respectively, using three neighboring residues of the mutant site along N- and C-terminals. Our method showed an accuracy of 82% for discriminating the stabilizing and destabilizing mutants, and a correlation of 0.70 for predicting protein stability changes upon mutations.'),
(73360, 2007, 'bio', 'UniRef: comprehensive and non-redundant UniProt reference clusters', 'Suzek, Baris E|Huang, Hongzhan|McGarvey, Peter|Mazumder, Raja|Wu, Cathy H', 'Protein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, USA. bes23@georgetown.edu|Protein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, USA. bes23@georgetown.edu|Protein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, USA. bes23@georgetown.edu|Protein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, USA. bes23@georgetown.edu|Protein Information Resource, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20007, USA. bes23@georgetown.edu', 'United States|United States|United States|United States|United States', 609, 'Amino Acid Sequence|Animals|Computational Biology|Databases, Protein|Humans|Information Storage and Retrieval|Proteins', 'Journal Article', '10.1093/bioinformatics/btm098', '17379688', 'Redundant protein sequences in biological databases hinder sequence similarity searches and make interpretation of search results difficult. Clustering of protein sequence space based on sequence similarity helps organize all sequences into manageable datasets and reduces sampling bias and overrepresentation of sequences.'),
(73361, 2007, 'bio', 'IMEx: Imperfect Microsatellite Extractor', 'Mudunuri, Suresh B|Nagarajaram, Hampapathalu A', 'Laboratory of Computational Biology, Centre for DNA Fingerprinting and Diagnostics, ECIL Road, Nacharam, Hyderabad 500 076, India.|Laboratory of Computational Biology, Centre for DNA Fingerprinting and Diagnostics, ECIL Road, Nacharam, Hyderabad 500 076, India.', 'India|India', 0, 'Algorithms|Genome|Humans|Internet|Microsatellite Repeats|Nerve Tissue Proteins|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btm097', '17379689', 'Microsatellites, also known as simple sequence repeats, are the tandem repeats of nucleotide motifs of the size 1-6 bp found in every genome known so far. Their importance in genomes is well known. Microsatellites are associated with various disease genes, have been used as molecular markers in linkage analysis and DNA fingerprinting studies, and also seem to play an important role in the genome evolution. Therefore, it is of importance to study distribution, enrichment and polymorphism of microsatellites in the genomes of interest. For this, the prerequisite is the availability of a computational tool for extraction of microsatellites (perfect as well as imperfect) and their related information from whole genome sequences. Examination of available tools revealed certain lacunae in them and prompted us to develop a new tool.'),
(73362, 2019, 'bio', 'RETRACTED: Analysis and prediction of xcexb2-turn types using multinomial logistic regression and artificial neural network', 'Mehdi, Poursheikhali Asgary|Parviz, Abdolmaleki|Anoshirvan, Kazemnejad|Samad, Jahandidehs', 'Department of biophysics, Faculty of Basic Sciences, Tarbiat Modares University, Tehran, Iran.|Department of biophysics, Faculty of Basic Sciences, Tarbiat Modares University, Tehran, Iran.|Department of biostatistics, Faculty of Medical Sciences, Tarbiat Modares university, Tehran, Iran.|Department of biophysics, Faculty of Basic Sciences, Tarbiat Modares University, Tehran, Iran.', '-|-|-|-', 0, '-', 'Journal Article', '10.1093/bioinformatics/btm094', '17379690', 'So far various statistical and machine learning techniques applied for prediction of xcexb2-turns. The majority of these techniques have been only focused on the prediction of xcexb2-turn location in proteins. We developed a hybrid approach for analysis and prediction of different types of xcexb2-turn.'),
(73363, 2007, 'bio', 'The impact of function perturbations in Boolean networks', 'Xiao, Yufei|Dougherty, Edward R', 'Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX 77843, USA.', 'United States|United States', 99, 'Algorithms|Animals|Body Patterning|Computer Simulation|Drosophila melanogaster|Gene Regulatory Networks|Humans|Melanoma|Models, Genetic|Models, Statistical|Neoplasm Metastasis|Proto-Oncogene Proteins|Systems Biology|Wnt Proteins|Wnt-5a Protein', 'Journal Article', '10.1093/bioinformatics/btm093', '17379691', 'A network is said to be robust relative to a certain network characteristic if a small change in network structure does not significantly affect the characteristic. From the perspective of network stability, robustness is desirable, however, from the perspective of intervention to exert influence on network behavior, it is undesirable. For Boolean networks, there are two fundamental types of robustness. One type pertains to perturbing the state of the network and the other to perturbing the rule-based structure.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73364, 2007, 'bio', 'Domain-enhanced analysis of microarray data using GO annotations', 'Liu, Jiajun|Hughes-Oliver, Jacqueline M|Menius, J Alan', 'Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA. jliu6@stat.ncsu.edu|Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA. jliu6@stat.ncsu.edu|Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA. jliu6@stat.ncsu.edu', 'United States|United States|United States', 0, 'Burkitt Lymphoma|Computational Biology|Computer Simulation|Gene Expression Profiling|Humans|Leukemia-Lymphoma, Adult T-Cell|Oligonucleotide Array Sequence Analysis|Sensitivity and Specificity|Software', 'Evaluation Studies', '10.1093/bioinformatics/btm092', '17379692', 'New biological systems technologies give scientists the ability to measure thousands of bio-molecules including genes, proteins, lipids and metabolites. We use domain knowledge, e.g. the Gene Ontology, to guide analysis of such data. By focusing on domain-aggregated results at, say the molecular function level, increased interpretability is available to biological scientists beyond what is possible if results are presented at the gene level.'),
(73365, 2007, 'bio', 'Enhancements and modifications of primer design program Primer3', 'Koressaar, Triinu|Remm, Maido', 'Department of Bioinformatics, Institute of Molecular and Cell Biology, University of Tartu, Riia str. 23, Tartu 51010, Estonia.|Department of Bioinformatics, Institute of Molecular and Cell Biology, University of Tartu, Riia str. 23, Tartu 51010, Estonia.', 'Estonia|Estonia', 1416, 'Algorithms|DNA Primers|Polymerase Chain Reaction|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btm091', '17379693', 'The determination of annealing temperature is a critical step in PCR design. This parameter is typically derived from the melting temperature of the PCR primers, so for successful PCR work it is important to determine the melting temperature of primer accurately. We introduced several enhancements in the widely used primer design program Primer3. The improvements include a formula for calculating melting temperature and a salt correction formula. Also, the new version can take into account the effects of divalent cations, which are included in most PCR buffers. Another modification enables using lowercase masked template sequences for primer design.'),
(73366, 2007, 'bio', 'AutoSCOP: automated prediction of SCOP classifications using unique pattern-class mappings', 'Gewehr, Jan E|Hintermair, Volker|Zimmer, Ralf', 'Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University Munich, Amalienstr. 17, D-80333 Munich, Germany. jan.gewehr@ifi.lmu.de|Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University Munich, Amalienstr. 17, D-80333 Munich, Germany. jan.gewehr@ifi.lmu.de|Practical Informatics and Bioinformatics Group, Department of Informatics, Ludwig-Maximilians-University Munich, Amalienstr. 17, D-80333 Munich, Germany. jan.gewehr@ifi.lmu.de', 'Germany|Germany|Germany', 0, 'Animals|Computational Biology|Databases, Protein|Mice|Pattern Recognition, Automated|Protein Folding|Protein Structure, Tertiary|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btm089', '17379694', 'The sequence patterns contained in the available motif and hidden Markov model (HMM) databases are a valuable source of information for protein sequence annotation. For structure prediction and fold recognition purposes, we computed mappings from such pattern databases to the protein domain hierarchy given by the ASTRAL compendium and applied them to the prediction of SCOP classifications. Our aim is to make highly confident predictions also for non-trivial cases if possible and abstain from a prediction otherwise, and thus to provide a method that can be used as a first step in a pipeline of prediction methods. We describe two successful examples for such pipelines. With the AutoSCOP approach, it is possible to make predictions in a large-scale manner for many domains of the available sequences in the well-known protein sequence databases.'),
(73367, 2007, 'bio', 'Using DNA microarrays to study gene expression in closely related species', 'Oshlack, Alicia|Chabot, Adrien E|Smyth, Gordon K|Gilad, Yoav', 'Walter and Eliza Hall Institute of Medical Research, Parkville, Vic 3050, Australia. oshlack@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Parkville, Vic 3050, Australia. oshlack@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Parkville, Vic 3050, Australia. oshlack@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Parkville, Vic 3050, Australia. oshlack@wehi.edu.au', 'Australia|Australia|Australia|Australia', 0, 'Animals|DNA, Complementary|Gene Expression|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Primates|RNA, Complementary|Sequence Analysis, DNA|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/btm111', '17384014', 'Comparisons of gene expression levels within and between species have become a central tool in the study of the genetic basis for phenotypic variation, as well as in the study of the evolution of gene regulation. DNA microarrays are a key technology that enables these studies. Currently, however, microarrays are only available for a small number of species. Thus, in order to study gene expression levels in species for which microarrays are not available, researchers face three sets of choices: (i) use a microarray designed for another species, but only compare gene expression levels within species, (ii) construct a new microarray for every species whose gene expression profiles will be compared or (iii) build a multi-species microarray with probes from each species of interest. Here, we use data collected using a multi-primate cDNA array to evaluate the reliability of each approach.'),
(73368, 2007, 'bio', 'GenABEL: an R library for genome-wide association analysis', 'Aulchenko, Yurii S|Ripke, Stephan|Isaacs, Aaron|van Duijn, Cornelia M', 'Department of Epidemiology and Biostatistics, Erasmus MC Rotterdam, Postbus 2040, 3000 CA Rotterdam, The Netherlands. i.aoultchenko@erasmusmc.nl|Department of Epidemiology and Biostatistics, Erasmus MC Rotterdam, Postbus 2040, 3000 CA Rotterdam, The Netherlands. i.aoultchenko@erasmusmc.nl|Department of Epidemiology and Biostatistics, Erasmus MC Rotterdam, Postbus 2040, 3000 CA Rotterdam, The Netherlands. i.aoultchenko@erasmusmc.nl|Department of Epidemiology and Biostatistics, Erasmus MC Rotterdam, Postbus 2040, 3000 CA Rotterdam, The Netherlands. i.aoultchenko@erasmusmc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Computational Biology|Computer Simulation|Gene Library|Genome|Genome, Human|Haplotypes|Humans|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btm108', '17384015', 'Here we describe an R library for genome-wide association (GWA) analysis. It implements effective storage and handling of GWA data, fast procedures for genetic data quality control, testing of association of single nucleotide polymorphisms with binary or quantitative traits, visualization of results and also provides easy interfaces to standard statistical and graphical procedures implemented in base R and special R libraries for genetic analysis. We evaluated GenABEL using one simulated and two real data sets. We conclude that GenABEL enables the analysis of GWA data on desktop computers.'),
(73369, 2007, 'bio', 'Mediante: a web-based microarray data manager', 'Le Brigand, Kevin|Barbry, Pascal', 'CNRS and University of Nice Sophia Antipolis, Institut de Pharmacologie Moléculaire et Cellulaire, UMR6097, 06560 Sophia Antipolis, France.|CNRS and University of Nice Sophia Antipolis, Institut de Pharmacologie Moléculaire et Cellulaire, UMR6097, 06560 Sophia Antipolis, France.', 'France|France', 26, 'Information Management|Internet|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm106', '17384016', 'Mediante is a MIAME-compliant microarray data manager that links together annotations and experimental data. Developed as a J2EE three-tier application, Mediante integrates a management system for production of long oligonucleotide microarrays, an experimental data repository suitable for home made or commercial microarrays, and a user interface dedicated to the management of microarrays projects. Several tools allow quality control of hybridizations and submission of validated data to public repositories.'),
(73370, 2007, 'bio', 'SBML export interface for the systems biology toolbox for MATLAB', 'Schmidt, Hening|Drews, Gunnar|Vera, Julio|Wolkenhauer, Olaf', 'Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden. henning@fcc.chalmers.se|Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden. henning@fcc.chalmers.se|Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden. henning@fcc.chalmers.se|Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Gothenburg, Sweden. henning@fcc.chalmers.se', 'Sweden|Sweden|Sweden|Sweden', 0, 'Documentation|Information Management|Internet|Programming Languages|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btm105', '17384017', 'In this application note, we present an Systems biology markup language (SBML) export interface for the Systems Biology Toolbox for MATLAB. This interface allows modelers to automatically convert models, represented in the toolboxs own format (SBmodels) to SBML files. Since SBmodels do not explicitly contain all the information that is required to generate SBML, the necessary information is gathered by parsing SBmodels. The export can be done in two different ways. First, it is possible to call the export from the command line, thereby directly converting a model to an SBML file. The second option is to inspect and edit the conversion results with the help of a graphical user interface and to subsequently export the model to SBML.'),
(73371, 2007, 'bio', 'A mixture model approach to the tests of concordance and discordance between two large-scale experiments with two-sample groups', 'Lai, Yinglei|Adam, Bao-ling|Podolsky, Robert|She, Jin-Xiong', 'Department of Statistics and Biostatistics Center, The George Washington University, 2140 Pennsylvania Avenue, N.W. Washington, DC 20052, USA. ylai@gwu.edu|Department of Statistics and Biostatistics Center, The George Washington University, 2140 Pennsylvania Avenue, N.W. Washington, DC 20052, USA. ylai@gwu.edu|Department of Statistics and Biostatistics Center, The George Washington University, 2140 Pennsylvania Avenue, N.W. Washington, DC 20052, USA. ylai@gwu.edu|Department of Statistics and Biostatistics Center, The George Washington University, 2140 Pennsylvania Avenue, N.W. Washington, DC 20052, USA. ylai@gwu.edu', 'United States|United States|United States|United States', 12, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Diabetes Mellitus, Type 1|Female|Humans|Male|Models, Genetic|Models, Statistical|Ovarian Neoplasms|Prostatic Neoplasms|Proteomics|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Journal Article', '10.1093/bioinformatics/btm103', '17384018', 'Due to advances in experimental technologies, such as microarray, mass spectrometry and nuclear magnetic resonance, it is feasible to obtain large-scale data sets, in which measurements for a large number of features can be simultaneously collected. However, the sample sizes of these data sets are usually small due to their relatively high costs, which leads to the issue of concordance among different data sets collected for the same study: features should have consistent behavior in different data sets. There is a lack of rigorous statistical methods for evaluating this concordance or discordance.'),
(73372, 2007, 'bio', 'Quantitating tissue specificity of human genes to facilitate biomarker discovery', 'Vasmatzis, George|Klee, Eric W|Kube, Dagmar M|Therneau, Terry M|Kosari, Farhad', 'Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, Rochester, MN 55905, USA. vasm@mayo.edu|Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, Rochester, MN 55905, USA. vasm@mayo.edu|Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, Rochester, MN 55905, USA. vasm@mayo.edu|Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, Rochester, MN 55905, USA. vasm@mayo.edu|Mayo Clinic Comprehensive Cancer Center and Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, Rochester, MN 55905, USA. vasm@mayo.edu', 'United States|United States|United States|United States|United States', 13, 'Biomarkers, Tumor|Chromosome Mapping|Expressed Sequence Tags|Genetic Predisposition to Disease|Genome, Human|Humans|Neoplasm Proteins|Neoplasms|Organ Specificity|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm102', '17384019', 'We describe a method to identify candidate cancer biomarkers by analyzing numeric approximations of tissue specificity of human genes. These approximations were calculated by analyzing predicted tissue expression distributions of genes derived from mapping expressed sequence tags (ESTs) to the human genome sequence using a binary indexing algorithm. Tissue-specificity values facilitated high-throughput analysis of the human genes and enabled the identification of genes highly specific to different tissues. Tissue expression distributions for several genes were compared to estimates obtained from other public gene expression datasets and experimentally validated using quantitative RT-PCR on RNA isolated from several human tissues. Our results demonstrate that most human genes ( approximately 98%) are expressed in many tissues (low specificity), and only a small number of genes possess very specific tissue expression profiles. These genes comprise a rich dataset from which novel therapeutic targets and novel diagnostic serum biomarkers may be selected.'),
(73373, 2007, 'bio', 'IlluminaGUI: graphical user interface for analyzing gene expression data generated on the Illumina platform', 'Schultze, Joachim L|Eggle, Daniela', 'Molecular Tumor Biology and Tumor Immunology, Department of Internal Medicine I, University of Cologne, Cologne, Germany. joachim.schultze@uk-koeln.de|Molecular Tumor Biology and Tumor Immunology, Department of Internal Medicine I, University of Cologne, Cologne, Germany. joachim.schultze@uk-koeln.de', 'Germany|Germany', 14, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm101', '17384020', 'IlluminaGUI is a graphical user interface implemented for analyzing microarray data from the Illumina BeadChip platform. All key components of a microarray experiment, including quality control, normalization, inference and classification methods are provided in a point and click approach. IlluminaGUI is implemented as a R package based on the R-Tcl/Tk interface and is available for platforms on which R runs including Windows, Mac and Unix-type machines.'),
(73374, 2007, 'bio', 'Unsupervised segmentation of continuous genomic data', 'Day, Nathan|Hemmaplardh, Andrew|Thurman, Robert E|Stamatoyannopoulos, John A|Noble, William S', 'Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA.|Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA.|Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA.|Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA.|Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA.', 'United States|United States|United States|United States|United States', 60, 'Algorithms|Artificial Intelligence|Chromosome Mapping|Computer Simulation|Databases, Genetic|Information Storage and Retrieval|Markov Chains|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm096', '17384021', 'The advent of high-density, high-volume genomic data has created the need for tools to summarize large datasets at multiple scales. HMMSeg is a command-line utility for the scale-specific segmentation of continuous genomic data using hidden Markov models (HMMs). Scale specificity is achieved by an optional wavelet-based smoothing operation. HMMSeg is capable of handling multiple datasets simultaneously, rendering it ideal for integrative analysis of expression, phylogenetic and functional genomic data.'),
(73375, 2007, 'bio', 'SNPTools: a software tool for visualization and analysis of microarray data', 'Sørensen, Frank J|Andersen, Claus L|Wiuf, Carsten', 'Bioinformatics Research Center, University of Aarhus, Høegh Guldbergs Gade 10, Aarhus C, Denmark.|Bioinformatics Research Center, University of Aarhus, Høegh Guldbergs Gade 10, Aarhus C, Denmark.|Bioinformatics Research Center, University of Aarhus, Høegh Guldbergs Gade 10, Aarhus C, Denmark.', 'Denmark|Denmark|Denmark', 3, 'Chromosome Mapping|Chromosomes, Human|Computational Biology|Computer Graphics|Gene Dosage|Humans|Loss of Heterozygosity|Neoplasms|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|RNA, Messenger|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm122', '17384422', 'We have created a software tool, SNPTools, for analysis and visualization of microarray data, mainly SNP array data. The software can analyse and find differences in intensity levels between groups of arrays and identify segments of SNPs (genes, clones), where the intensity levels differ significantly between the groups. In addition, SNPTools can show jointly loss-of-heterozygosity (LOH) data (derived from genotypes) and intensity data for paired samples of tumour and normal arrays. The output graphs can be manipulated in various ways to modify and adjust the layout. A wizard allows options and parameters to be changed easily and graphs replotted. All output can be saved in various formats, and also re-opened in SNPTools for further analysis. For explorative use, SNPTools allows various genome information to be loaded onto the graphs.'),
(73376, 2007, 'bio', 'Searching for three-dimensional secondary structural patterns in proteins with ProSMoS', 'Shi, Shuoyong|Zhong, Yi|Majumdar, Indraneel|Sri Krishna, S|Grishin, Nick V', 'Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.|Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.', 'United States|United States|United States|United States|United States', 32, 'Algorithms|Amino Acid Sequence|Computer Simulation|Expert Systems|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btm121', '17384423', 'Many evolutionarily distant, but functionally meaningful links between proteins come to light through comparison of spatial structures. Most programs that assess structural similarity compare two proteins to each other and find regions in common between them. Structural classification experts look for a particular structural motif instead. Programs base similarity scores on superposition or closeness of either Cartesian coordinates or inter-residue contacts. Experts pay more attention to the general orientation of the main chain and mutual spatial arrangement of secondary structural elements. There is a need for a computational tool to find proteins with the same secondary structures, topological connections and spatial architecture, regardless of subtle differences in 3D coordinates.'),
(73377, 2007, 'bio', 'Finding new structural and sequence attributes to predict possible disease association of single amino acid polymorphism (SAP)', 'Ye, Zhi-Qiang|Zhao, Shu-Qi|Gao, Ge|Liu, Xiao-Qiao|Langlois, Robert E|Lu, Hui|Wei, Liping', 'Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing, PR China.', 'China|China|China|China|China|China|China', 44, 'Amino Acid Sequence|Amino Acids|Artificial Intelligence|Conserved Sequence|Databases, Protein|Disease|Disulfides|Humans|Hydrogen Bonding|Polymorphism, Genetic|Protein Structure, Secondary|Protein Structure, Tertiary|Reproducibility of Results|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Evaluation Studies', '10.1093/bioinformatics/btm119', '17384424', 'The rapid accumulation of single amino acid polymorphisms (SAPs), also known as non-synonymous single nucleotide polymorphisms (nsSNPs), brings the opportunities and needs to understand and predict their disease association. Currently published attributes are limited, the detailed mechanisms governing the disease association of a SAP remain unclear and thus, further investigation of new attributes and improvement of the prediction are desired.'),
(73378, 2007, 'bio', 'Enhancing the functional annotation of PDB structures in PDBsum using key figures extracted from the literature', 'Laskowski, Roman A', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. roman@ebi.ac.uk', 'United Kingdom', 43, 'Computational Biology|Computer Graphics|Databases, Protein|Imaging, Three-Dimensional|Molecular Conformation|Molecular Structure|Proteins|PubMed|Publications|Software', 'Journal Article', '10.1093/bioinformatics/btm085', '17384425', 'The Protein Data Bank (PDB) contains over 43,800 experimentally determined 3D models of macromolecular structures and their complexes. Each 3D model reveals something interesting and important about the given molecules function and biological significance. Usually the best source of this information is the original article describing it, and it is often possible to discern the key aspects of the structure from just one or two of the figures in that article.'),
(73379, 2007, 'bio', 'GoSh: a web-based database for goat and sheep EST sequences', 'Caprera, Andrea|Lazzari, Barbara|Stella, Alessandra|Merelli, Ivan|Caetano, Alexandre R|Mariani, Paola', 'Parco Tecnologico Padano, Località Cascina Codazza, Lodi, Italy. andrea.caprera@tecnoparco.org|Parco Tecnologico Padano, Località Cascina Codazza, Lodi, Italy. andrea.caprera@tecnoparco.org|Parco Tecnologico Padano, Località Cascina Codazza, Lodi, Italy. andrea.caprera@tecnoparco.org|Parco Tecnologico Padano, Località Cascina Codazza, Lodi, Italy. andrea.caprera@tecnoparco.org|Parco Tecnologico Padano, Località Cascina Codazza, Lodi, Italy. andrea.caprera@tecnoparco.org|Parco Tecnologico Padano, Località Cascina Codazza, Lodi, Italy. andrea.caprera@tecnoparco.org', 'Italy|Italy|Italy|Italy|Italy|Italy', 6, 'Algorithms|Animals|Computer Graphics|Database Management Systems|Databases, Genetic|Expressed Sequence Tags|Goats|Information Storage and Retrieval|Internet|Sequence Analysis, DNA|Sheep|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm063', '17384426', 'The GoSh database is a collection of 58 990 Capra hircus and Ovis aries expressed sequence tags. A perl pipeline was prepared to process sequences, and data were collected in a MySQL database. A PHP-based web interface allows browsing and querying the database. Putative single nucleotide polymorphism (SNP) detection, as well as search to repeats were performed, and links to external related resources were provided. Sequences were annotated against three different databases and an algorithm was implemented to create statistics of the distribution of retrieved homologous ontologies in the Gene Ontology categories. The GoSh database is a repository of data and links related to goat and sheep expressed genes.'),
(73380, 2007, 'bio', 'POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties', 'Tung, Chun-Wei|Ho, Shinn-Ying', 'Institute of Bioinformatics, National Chiao Tung University, Hsinchu, Taiwan.|Institute of Bioinformatics, National Chiao Tung University, Hsinchu, Taiwan.', '-|-', 78, 'Algorithms|Artificial Intelligence|Binding Sites|Epitope Mapping|Histocompatibility Antigens Class I|Oligopeptides|Pattern Recognition, Automated|Protein Binding|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btm061', '17384427', 'Both modeling of antigen-processing pathway including major histocompatibility complex (MHC) binding and immunogenicity prediction of those MHC-binding peptides are essential to develop a computer-aided system of peptide-based vaccine design that is one goal of immunoinformatics. Numerous studies have dealt with modeling the immunogenic pathway but not the intractable problem of immunogenicity prediction due to complex effects of many intrinsic and extrinsic factors. Moderate affinity of the MHC-peptide complex is essential to induce immune responses, but the relationship between the affinity and peptide immunogenicity is too weak to use for predicting immunogenicity. This study focuses on mining informative physicochemical properties from known experimental immunogenicity data to understand immune responses and predict immunogenicity of MHC-binding peptides accurately.'),
(73381, 2007, 'bio', 'Semantic Web Service provision: a realistic framework for Bioinformatics programmers', 'Gordon, Paul M K|Trinh, Quang|Sensen, Christoph W', 'University of Calgary, Faculty of Medicine, Sun Center of Excellence for Visual Genomics, Calgary, AB, Canada. gordonp@ucalgary.ca|University of Calgary, Faculty of Medicine, Sun Center of Excellence for Visual Genomics, Calgary, AB, Canada. gordonp@ucalgary.ca|University of Calgary, Faculty of Medicine, Sun Center of Excellence for Visual Genomics, Calgary, AB, Canada. gordonp@ucalgary.ca', 'Canada|Canada|Canada', 12, 'Computational Biology|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Natural Language Processing|Programming Languages|Semantics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm060', '17384428', 'Several semantic Web Services clients for Bioinformatics have been released, but to date no support systems for service providers have been described. We have created a framework (MobyServlet) that very simply allows an existing Java application to conform to the MOBY-S semantic Web Services protocol. Using an existing Java program for codon-pair bias determination as an example, we enumerate the steps required for MOBY-S compliance. With minimal programming effort, such a deployment has the advantages of: (1) wider exposure to the user community by automatic inclusion in all MOBY-S client programs and (2) automatic interoperability with other MOBY-S services for input and output. Complex on-line analysis will become easier for biologists as more developers adopt MOBY-S.'),
(73382, 2007, 'bio', 'Improved centroids estimation for the nearest shrunken centroid classifier', 'Wang, Sijian|Zhu, Ji', 'Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States', 41, 'Algorithms|Artificial Intelligence|Cluster Analysis|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm046', '17384429', 'The nearest shrunken centroid (NSC) method has been successfully applied in many DNA-microarray classification problems. The NSC uses shrunken centroids as prototypes for each class and identifies subsets of genes that best characterize each class. Classification is then made to the nearest (shrunken) centroid. The NSC is very easy to implement and very easy to interpret, however, it has drawbacks.'),
(73383, 2007, 'bio', 'MPP: a microarray-to-phylogeny pipeline for analysis of gene and marker content datasets', 'Davey, Robert|Savva, George|Dicks, Jo|Roberts, Ian N', 'National Collection of Yeast Cultures, Institute of Food Research, Norwich Research Park, Colney, Norwich, UK. robert.davey@bbsrc.ac.uk|National Collection of Yeast Cultures, Institute of Food Research, Norwich Research Park, Colney, Norwich, UK. robert.davey@bbsrc.ac.uk|National Collection of Yeast Cultures, Institute of Food Research, Norwich Research Park, Colney, Norwich, UK. robert.davey@bbsrc.ac.uk|National Collection of Yeast Cultures, Institute of Food Research, Norwich Research Park, Colney, Norwich, UK. robert.davey@bbsrc.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 4, 'Algorithms|Chromosome Mapping|Databases, Genetic|Gene Dosage|Genetic Markers|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Phylogeny|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btm038', '17384430', 'MPP is a Java application, encompassing both new and established algorithms, for the analysis of gene and marker content datasets arising from high-throughput microarray techniques. MPP analyses flat file output from microarray experiments to determine the probability of the presence or absence of genes or markers within a genome. MPP can construct gene or marker content datasets for a number of genomes and can use the data to estimate an evolutionary tree or network. Results from gene content analyses may be validated by comparing them to known gene contents. MPP was initially developed to analyse data derived from comparative genome hybridization (CGH) microarray experiments in fungi and bacteria. It has recently been adapted to analyse retrotransposon-based insertion polymorphism (RBIP) marker scores derived from tagged microarray marker (TAM) experiments in pea. New analytical procedures may be added easily to MPP as plugins in order to increase the scope of the software.'),
(73384, 2007, 'bio', 'Regression analysis and modelling of data acquisition for SELDI-TOF mass spectrometry', 'Sköld, Martin|Rydén, Tobias|Samuelsson, Viktoria|Bratt, Charlotte|Ekblad, Lars|Olsson, Håkan|Baldetorp, Bo', 'Centre for Mathematical Sciences, Lund University, Lund, Sweden. martins@maths.lth.se|Centre for Mathematical Sciences, Lund University, Lund, Sweden. martins@maths.lth.se|Centre for Mathematical Sciences, Lund University, Lund, Sweden. martins@maths.lth.se|Centre for Mathematical Sciences, Lund University, Lund, Sweden. martins@maths.lth.se|Centre for Mathematical Sciences, Lund University, Lund, Sweden. martins@maths.lth.se|Centre for Mathematical Sciences, Lund University, Lund, Sweden. martins@maths.lth.se|Centre for Mathematical Sciences, Lund University, Lund, Sweden. martins@maths.lth.se', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 7, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Microarray Analysis|Models, Statistical|Regression Analysis|Reproducibility of Results|Sensitivity and Specificity|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Evaluation Studies', '10.1093/bioinformatics/btm104', '17387110', 'Pre-processing of SELDI-TOF mass spectrometry data is currently performed on a largel y ad hoc basis. This makes comparison of results from independent analyses troublesome and does not provide a framework for distinguishing different sources of variation in data.'),
(73385, 2007, 'bio', 'Ngila: global pairwise alignments with logarithmic and affine gap costs', 'Cartwright, Reed A', 'Department of Genetics, University of Georgia, Athens, GA 30602-7223, USA. racartwr@ncsu.edu', 'Georgia', 11, 'Algorithms|Base Sequence|DNA Transposable Elements|Data Interpretation, Statistical|Gene Deletion|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btm095', '17387111', 'Ngila is an application that will find the best alignment of a pair of sequences using log-affine gap costs, which are the most biologically realistic gap costs.'),
(73386, 2007, 'bio', 'A sequential Monte Carlo EM approach to the transcription factor binding site identification problem', 'Jackson, Edmund S|Fitzgerald, William J', 'Signal Processing Laboratory, Department of Engineering, Cambridge University, UK. ej230@cam.ac.uk|Signal Processing Laboratory, Department of Engineering, Cambridge University, UK. ej230@cam.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Base Sequence|Binding Sites|Likelihood Functions|Models, Genetic|Models, Statistical|Molecular Sequence Data|Monte Carlo Method|Pattern Recognition, Automated|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm054', '17387112', 'A significant and stubbornly intractable problem in genome sequence analysis has been the de novo identification of transcription factor binding sites in promoter regions. Although theoretically pleasing, probabilistic methods have faced difficulties due to model mismatch and the nature of the biological sequence. These problems result in inference in a high dimensional, highly multimodal space, and consequently often display only local convergence and hence unsatisfactory performance.'),
(73387, 2007, 'bio', 'Assessing the need for sequence-based normalization in tiling microarray experiments', 'Royce, Thomas E|Rozowsky, Joel S|Gerstein, Mark B', 'Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.', 'United States|United States|United States', 35, 'Algorithms|Base Sequence|Computer Simulation|DNA Probes|Models, Genetic|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btm052', '17387113', 'Increases in microarray feature density allow the construction of so-called tiling microarrays. These arrays, or sets of arrays, contain probes targeting regions of sequenced genomes at regular genomic intervals. The unbiased nature of this approach allows for the identification of novel transcribed sequences, the localization of transcription factor binding sites (ChIP-chip), and high resolution comparative genomic hybridization, among other uses. These applications are quickly growing in popularity as tiling microarrays become more affordable. To reach maximum utility, the tiling microarray platform needs be developed to the point that 1 nt resolutions are achieved and that we have confidence in individual measurements taken at this fine of resolution. Any biases in tiling array signals must be systematically removed to achieve this goal.'),
(73388, 2007, 'bio', 'Local structural disorder imparts plasticity on linear motifs', 'Fuxreiter, Monika|Tompa, Peter|Simon, István', 'Institute of Enzymology, BRC, Hungarian Academy of Sciences, Budapest, Hungary.|Institute of Enzymology, BRC, Hungarian Academy of Sciences, Budapest, Hungary.|Institute of Enzymology, BRC, Hungarian Academy of Sciences, Budapest, Hungary.', 'Hungary|Hungary|Hungary', 309, 'Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Computer Simulation|Linear Models|Models, Chemical|Models, Statistical|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm035', '17387114', 'The dynamic nature of protein interaction networks requires fast and transient molecular switches. The underlying recognition motifs (linear motifs, LMs) are usually short and evolutionarily variable segments, which in several cases, such as phosphorylation sites or SH3-binding regions, fall into locally disordered regions. We probed the generality of this phenomenon by predicting the intrinsic disorder of all LM-containing proteins enlisted in the Eukaryotic Linear Motif (ELM) database.'),
(73389, 2007, 'bio', 'Classification based upon gene expression data: bias and precision of error rates', 'Wood, Ian A|Visscher, Peter M|Mengersen, Kerrie L', 'School of Mathematical Sciences, Queensland University of Technology, Gardens Point, Brisbane, QLD, Australia. i.wood@qut.edu.au|School of Mathematical Sciences, Queensland University of Technology, Gardens Point, Brisbane, QLD, Australia. i.wood@qut.edu.au|School of Mathematical Sciences, Queensland University of Technology, Gardens Point, Brisbane, QLD, Australia. i.wood@qut.edu.au', 'Australia|Australia|Australia', 57, 'Algorithms|Artifacts|Artificial Intelligence|Cluster Analysis|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm117', '17392326', 'Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean.'),
(73390, 2007, 'bio', 'Extending the pathway analysis framework with a test for transcriptional variance implicates novel pathway modulation during myogenic differentiation', 'Kemp, Daniel M|Nirmala, N R|Szustakowski, Joseph D', 'Diabetes and Metabolism Disease Area, Novartis Institutes for BioMedical Research, Cambridge, MA 02139, USA.|Diabetes and Metabolism Disease Area, Novartis Institutes for BioMedical Research, Cambridge, MA 02139, USA.|Diabetes and Metabolism Disease Area, Novartis Institutes for BioMedical Research, Cambridge, MA 02139, USA.', 'United States|United States|United States', 5, 'Animals|Cell Differentiation|Computer Simulation|Gene Expression Regulation, Developmental|Genetic Variation|Mice|Models, Biological|Muscle Cells|Muscle Proteins|Myoblasts|Signal Transduction|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1093/bioinformatics/btm116', '17392327', 'We describe an extension of the pathway-based enrichment approach for analyzing microarray data via a robust test for transcriptional variance. The use of a variance test is intended to identify additional patterns of transcriptional regulation in which many genes in a pathway are up- and down-regulated. Such patterns may be indicative of the reciprocal regulation of pathway activators and inhibitors or of the differential regulation of separate biological sub-processes and should extend the number of detectable patterns of transcriptional modulation.'),
(73391, 2007, 'bio', 'SherLoc: high-accuracy prediction of protein subcellular localization by integrating text and protein sequence data', 'Shatkay, Hagit|Höglund, Annette|Brady, Scott|Blum, Torsten|Dönnes, Pierre|Kohlbacher, Oliver', 'School of Computing, Queens University, Kingston, Ontario, Canada. shatkay@cs.queensu.ca|School of Computing, Queens University, Kingston, Ontario, Canada. shatkay@cs.queensu.ca|School of Computing, Queens University, Kingston, Ontario, Canada. shatkay@cs.queensu.ca|School of Computing, Queens University, Kingston, Ontario, Canada. shatkay@cs.queensu.ca|School of Computing, Queens University, Kingston, Ontario, Canada. shatkay@cs.queensu.ca|School of Computing, Queens University, Kingston, Ontario, Canada. shatkay@cs.queensu.ca', 'Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Amino Acid Sequence|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Natural Language Processing|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship|Subcellular Fractions', 'Journal Article', '10.1093/bioinformatics/btm115', '17392328', 'Knowing the localization of a protein within the cell helps elucidate its role in biological processes, its function and its potential as a drug target. Thus, subcellular localization prediction is an active research area. Numerous localization prediction systems are described in the literature, some focus on specific localizations or organisms, while others attempt to cover a wide range of localizations.'),
(73392, 2007, 'bio', 'A fast and flexible approach to oligonucleotide probe design for genomes and gene families', 'Feng, Shengzhong|Tillier, Elisabeth R M', 'Institute of Computing Technology, Chinese Academy of Sciences, China.|Institute of Computing Technology, Chinese Academy of Sciences, China.', 'China|China', 26, 'Algorithms|Bacteria|Computational Biology|Genome, Bacterial|Microarray Analysis|Multigene Family|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Software', 'Journal Article', '10.1093/bioinformatics/btm114', '17392329', 'With hundreds of completely sequenced microbial genomes available, and advancements in DNA microarray technology, the detection of genes in microbial communities consisting of hundreds of thousands of sequences may be possible. The existing strategies developed for DNA probe design, geared toward identifying specific sequences, are not suitable due to the lack of coverage, flexibility and efficiency necessary for applications in metagenomics.'),
(73393, 2007, 'bio', 'DPTF: a database of poplar transcription factors', 'Zhu, Qi-Hui|Guo, An-Yuan|Gao, Ge|Zhong, Ying-Fu|Xu, Meng|Huang, Minren|Luo, Jinchu', 'Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering and College of Life Sciences, Peking University, Beijing 100871, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering and College of Life Sciences, Peking University, Beijing 100871, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering and College of Life Sciences, Peking University, Beijing 100871, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering and College of Life Sciences, Peking University, Beijing 100871, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering and College of Life Sciences, Peking University, Beijing 100871, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering and College of Life Sciences, Peking University, Beijing 100871, PR China.|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering and College of Life Sciences, Peking University, Beijing 100871, PR China.', 'China|China|China|China|China|China|China', 75, 'Databases, Protein|Internet|Plant Proteins|Populus|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btm113', '17392330', 'The database of poplar transcription factors (DPTF) is a plant transcription factor (TF) database containing 2576 putative poplar TFs distributed in 64 families. These TFs were identified from both computational prediction and manual curation. We have provided extensive annotations including sequence features, functional domains, GO assignment and expression evidence for all TFs. In addition, DPTF contains cross-links to the Arabidopsis and rice transcription factor databases making it a unique resource for genome-scale comparative studies of transcriptional regulation in model plants. Availiability: DPTF is available at http://dptf.cbi.pku.edu.cn.'),
(73394, 2007, 'bio', 'Modeling sequence-sequence interactions for drug response', 'Lin, Min|Li, Hongying|Hou, Wei|Johnson, Julie A|Wu, Rongling', 'Department of Statistics, University of Florida, Gainesville, FL 32611, USA.|Department of Statistics, University of Florida, Gainesville, FL 32611, USA.|Department of Statistics, University of Florida, Gainesville, FL 32611, USA.|Department of Statistics, University of Florida, Gainesville, FL 32611, USA.|Department of Statistics, University of Florida, Gainesville, FL 32611, USA.', 'United States|United States|United States|United States|United States', 0, 'Adult|Aged|Aged, 80 and over|Dobutamine|Dose-Response Relationship, Drug|Epistasis, Genetic|Female|Haplotypes|Heart Rate|Humans|Likelihood Functions|Male|Middle Aged|Models, Statistical|Pharmacogenetics|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Receptors, Adrenergic, beta-1|Receptors, Adrenergic, beta-2', 'Journal Article', '10.1093/bioinformatics/btm110', '17392331', 'Genetic interactions or epistasis may play an important role in the genetic etiology of drug response. With the availability of large-scale, high-density single nucleotide polymorphism markers, a great challenge is how to associate haplotype structures and complex drug response through its underlying pharmacodynamic mechanisms.'),
(73395, 2007, 'bio', 'uBioRSS: tracking taxonomic literature using RSS', 'Leary, Patrick R|Remsen, David P|Norton, Catherine N|Patterson, David J|Sarkar, Indra Neil', 'MBL Informatics, Marine Biological Laboratory, Woods Hole, MA 02543, USA.|MBL Informatics, Marine Biological Laboratory, Woods Hole, MA 02543, USA.|MBL Informatics, Marine Biological Laboratory, Woods Hole, MA 02543, USA.|MBL Informatics, Marine Biological Laboratory, Woods Hole, MA 02543, USA.|MBL Informatics, Marine Biological Laboratory, Woods Hole, MA 02543, USA.', 'United States|United States|United States|United States|United States', 22, 'Abstracting and Indexing as Topic|Classification|Database Management Systems|Information Storage and Retrieval|Internet|Natural Language Processing|Periodicals as Topic|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btm109', '17392332', 'Web content syndication through standard formats such as RSS and ATOM has become an increasingly popular mechanism for publishers, news sources and blogs to disseminate regularly updated content. These standardized syndication formats deliver content directly to the subscriber, allowing them to locally aggregate content from a variety of sources instead of having to find the information on multiple websites. The uBioRSS application is a taxonomically intelligent service customized for the biological sciences. It aggregates syndicated content from academic publishers and science news feeds, and then uses a taxonomic Named Entity Recognition algorithm to identify and index taxonomic names within those data streams. The resulting name index is cross-referenced to current global taxonomic datasets to provide context for browsing the publications by taxonomic group. This process, called taxonomic indexing, draws upon services developed specifically for biological sciences, collectively referred to as taxonomic intelligence. Such value-added enhancements can provide biologists with accelerated and improved access to current biological content.');
