INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90506, 2005, 'bmc', 'Communication and re-use of chemical information in bioscience', 'Murray-Rust, Peter|Mitchell, John B O|Rzepa, Henry S', 'Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK. pm286@hermes.cam.ac.uk|Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK. pm286@hermes.cam.ac.uk|Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK. pm286@hermes.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 17, 'Archives|Chemical Phenomena|Chemistry|Data Display|Databases, Factual|Information Storage and Retrieval|Journalism|Models, Chemical|Molecular Structure|Terminology as Topic', 'Journal Article', '10.1186/1471-2105-6-180', '16026614', 'The current methods of publishing chemical information in bioscience articles are analysed. Using 3 papers as use-cases, it is shown that conventional methods using human procedures, including cut-and-paste are time-consuming and introduce errors. The meaning of chemical terms and the identity of compounds is often ambiguous. valuable experimental data such as spectra and computational results are almost always omitted. We describe an Open XML architecture at proof-of-concept which addresses these concerns. Compounds are identified through explicit connection tables or links to persistent Open resources such as PubChem. It is argued that if publishers adopt these tools and protocols, then the quality and quantity of chemical information available to bioscientists will increase and the authors, publishers and readers will find the process cost-effective.'),
(90507, 2005, 'bmc', 'Vector analysis as a fast and easy method to compare gene expression responses between different experimental backgrounds', 'Breitling, Rainer|Armengaud, Patrick|Amtmann, Anna', 'Molecular Plant Science Group, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK. R.Breitling@bio.gla.ac.uk|Molecular Plant Science Group, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK. R.Breitling@bio.gla.ac.uk|Molecular Plant Science Group, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK. R.Breitling@bio.gla.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Arabidopsis|Computational Biology|Data Display|Gene Expression Profiling|Gene Expression Regulation, Plant|Models, Statistical', 'Comparative Study', '10.1186/1471-2105-6-181', '16029491', 'Gene expression studies increasingly compare expression responses between different experimental backgrounds (genetic, physiological, or phylogenetic). By focusing on dynamic responses rather than a direct comparison of static expression levels, this type of study allows a finer dissection of primary and secondary regulatory effects in the various backgrounds. Usually, results of such experiments are presented in the form of Venn diagrams, which are intuitive and visually appealing, but lack a statistical foundation.'),
(90508, 2005, 'bmc', 'Comparison of codon usage measures and their applicability in prediction of microbial gene expressivity', 'Supek, Fran|Vlahovicek, Kristian', 'Division of Biology, Department of Molecular Biology, Faculty of Science, Zagreb University, Rooseveltov trg 6, 10000 Zagreb, Croatia. fsupek@public.srce.hr|Division of Biology, Department of Molecular Biology, Faculty of Science, Zagreb University, Rooseveltov trg 6, 10000 Zagreb, Croatia. fsupek@public.srce.hr', 'Croatia|Croatia', 75, 'Chi-Square Distribution|Codon|Computational Biology|Gene Expression Regulation, Bacterial', 'Comparative Study', '10.1186/1471-2105-6-182', '16029499', 'There are a number of methods (also called: measures) currently in use that quantify codon usage in genes. These measures are often influenced by other sequence properties, such as length. This can introduce strong methodological bias into measurements, therefore we attempted to develop a method free from such dependencies. One of the common applications of codon usage analyses is to quantitatively predict gene expressivity.'),
(90509, 2005, 'bmc', 'Inconsistencies over time in 5% of NetAffx probe-to-gene annotations', 'Perez-Iratxeta, Carolina|Andrade, Miguel A', 'Division of Biology, Department of Molecular Biology, Faculty of Science, Zagreb University, Rooseveltov trg 6, 10000 Zagreb, Croatia. fsupek@public.srce.hr|Division of Biology, Department of Molecular Biology, Faculty of Science, Zagreb University, Rooseveltov trg 6, 10000 Zagreb, Croatia. fsupek@public.srce.hr', 'Croatia|Croatia', 22, 'Animals|Equipment Design|Mice|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Statistics as Topic|Terminology as Topic', 'Letter', '10.1186/1471-2105-6-183', '16033654', 'DNA microarray probes are designed to match particular mRNA transcripts, often based on expressed sequences like ESTs, or cDNAs, many times incomplete. As a result, the relations between probes and genes can change as the sequence data are updated. However, it is frequent that the reported results of microarray analyses are given just as lists of genes without any reference to the underlying probes.'),
(90510, 2005, 'bmc', 'A computational approach for identifying pathogenicity islands in prokaryotic genomes', 'Yoon, Sung Ho|Hur, Cheol-Goo|Kang, Ho-Young|Kim, Yeoun Hee|Oh, Tae Kwang|Kim, Jihyun F', 'Genome Research Center, Korea Research Institute of Bioscience and Biotechnology, 52 Oun-dong, Yuseong, Daejeon 305-333, Korea. moncher@kribb.re.kr|Genome Research Center, Korea Research Institute of Bioscience and Biotechnology, 52 Oun-dong, Yuseong, Daejeon 305-333, Korea. moncher@kribb.re.kr|Genome Research Center, Korea Research Institute of Bioscience and Biotechnology, 52 Oun-dong, Yuseong, Daejeon 305-333, Korea. moncher@kribb.re.kr|Genome Research Center, Korea Research Institute of Bioscience and Biotechnology, 52 Oun-dong, Yuseong, Daejeon 305-333, Korea. moncher@kribb.re.kr|Genome Research Center, Korea Research Institute of Bioscience and Biotechnology, 52 Oun-dong, Yuseong, Daejeon 305-333, Korea. moncher@kribb.re.kr|Genome Research Center, Korea Research Institute of Bioscience and Biotechnology, 52 Oun-dong, Yuseong, Daejeon 305-333, Korea. moncher@kribb.re.kr', '-|-|-|-|-|-', 0, 'Bacteria|Computational Biology|Genome|Genomic Islands|Prokaryotic Cells|Virulence', 'Journal Article', '10.1186/1471-2105-6-184', '16033657', 'Pathogenicity islands (PAIs), distinct genomic segments of pathogens encoding virulence factors, represent a subgroup of genomic islands (GIs) that have been acquired by horizontal gene transfer event. Up to now, computational approaches for identifying PAIs have been focused on the detection of genomic regions which only differ from the rest of the genome in their base composition and codon usage. These approaches often lead to the identification of genomic islands, rather than PAIs.'),
(90511, 2005, 'bmc', 'PSI-BLAST-ISS: an intermediate sequence search tool for estimation of the position-specific alignment reliability', 'Margelevicius, Mindaugas|Venclovas, Ceslovas', 'Institute of Biotechnology, Graiciuno 8, LT-02241 Vilnius, Lithuania. minmar@ibt.lt|Institute of Biotechnology, Graiciuno 8, LT-02241 Vilnius, Lithuania. minmar@ibt.lt', 'Lithuania|Lithuania', 27, 'Information Storage and Retrieval|Information Systems|Internet|Reproducibility of Results|Sequence Alignment|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-185', '16033659', 'Protein sequence alignments have become indispensable for virtually any evolutionary, structural or functional study involving proteins. Modern sequence search and comparison methods combined with rapidly increasing sequence data often can reliably match even distantly related proteins that share little sequence similarity. However, even highly significant matches generally may have incorrectly aligned regions. Therefore when exact residue correspondence is used to transfer biological information from one aligned sequence to another, it is critical to know which alignment regions are reliable and which may contain alignment errors.'),
(90512, 2005, 'bmc', 'Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments', 'Gao, Xin|Song, Peter X K', 'Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada. xingao@mathstat.yorku.ca|Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada. xingao@mathstat.yorku.ca', 'Canada|Canada', 8, 'Animals|Computational Biology|Gene Expression Profiling|Mice|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Species Specificity|Statistics, Nonparametric', 'Journal Article', '10.1186/1471-2105-6-186', '16042764', 'Numerous nonparametric approaches have been proposed in literature to detect differential gene expression in the setting of two user-defined groups. However, there is a lack of nonparametric procedures to analyze microarray data with multiple factors attributing to the gene expression. Furthermore, incorporating interaction effects in the analysis of microarray data has long been of great interest to biological scientists, little of which has been investigated in the nonparametric framework.'),
(90513, 2005, 'bmc', 'Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data', 'Jain, Nitin|Cho, HyungJun|OConnell, Michael|Lee, Jae K', 'Division of Biostatistics and Epidemiology, Department of Health Evaluation Sciences, University of Virginia School of Medicine, Hospital West Complex, Charlottesville, VA 22908-0717, USA. njain@alumni.virginia.edu|Division of Biostatistics and Epidemiology, Department of Health Evaluation Sciences, University of Virginia School of Medicine, Hospital West Complex, Charlottesville, VA 22908-0717, USA. njain@alumni.virginia.edu|Division of Biostatistics and Epidemiology, Department of Health Evaluation Sciences, University of Virginia School of Medicine, Hospital West Complex, Charlottesville, VA 22908-0717, USA. njain@alumni.virginia.edu|Division of Biostatistics and Epidemiology, Department of Health Evaluation Sciences, University of Virginia School of Medicine, Hospital West Complex, Charlottesville, VA 22908-0717, USA. njain@alumni.virginia.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Animals|Computational Biology|Data Interpretation, Statistical|False Positive Reactions|Gene Expression Profiling|Mice|Microarray Analysis|Models, Statistical|Pattern Recognition, Automated|Random Allocation|Reproducibility of Results|Sample Size|Software', 'Evaluation Studies', '10.1186/1471-2105-6-187', '16042779', 'The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustment methods for multiple comparisons such as family-wise error rate (FWER) have been found to be too conservative in analyzing large-screening microarray data, and the False Discovery Rate (FDR), the expected proportion of false positives among all positives, has been recently suggested as an alternative for controlling false positives. Several statistical approaches have been used to estimate and control FDR, but these may not provide reliable FDR estimation when applied to microarray data sets with a small number of replicates.'),
(90514, 2005, 'bmc', 'CGH-Profiler: data mining based on genomic aberration profiles', 'Schubert, Falk|Tausch, Bernhard|Joos, Stefan|Eils, Roland', 'Theoretical Bioinformatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. f.schubert@dkfz-heidelberg.de|Theoretical Bioinformatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. f.schubert@dkfz-heidelberg.de|Theoretical Bioinformatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. f.schubert@dkfz-heidelberg.de|Theoretical Bioinformatics, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. f.schubert@dkfz-heidelberg.de', 'Germany|Germany|Germany|Germany', 0, 'Chromosome Aberrations|Chromosome Mapping|Computational Biology|Cytogenetic Analysis|Data Collection|Genome|Humans|Information Storage and Retrieval|Nucleic Acid Hybridization|Reproducibility of Results|Software', 'Journal Article', '10.1186/1471-2105-6-188', '16042799', 'CGH-Profiler is a program that supports the analysis of genomic aberrations measured by Comparative Genomic Hybridisation (CGH). Comparative genomic hybridisation (CGH) is a well-established, molecular cytogenetic method that allows the detection of chromosomal imbalances in entire genomes. This technique is widely used in routine molecular diagnostics. Typically, chromosomal imbalances are described in a complex syntax based on the International Standard for Cytogenetic Nomenclature (ISCN). This semantic description of chromosomal imbalances hinders a large-scale statistical analysis across different experiments, e.g. for finding aberration patterns associated with a particular disease type or state.'),
(90515, 2005, 'bmc', 'GObar: a gene ontology based analysis and visualization tool for gene sets', 'Lee, Jason S M|Katari, Gurpreet|Sachidanandam, Ravi', 'Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. jayboy78@gmail.com|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. jayboy78@gmail.com|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. jayboy78@gmail.com', 'United States|United States|United States', 0, 'Algorithms|Animals|Data Collection|Data Display|Databases, Genetic|Drosophila melanogaster|Gene Expression Profiling|Humans|Information Storage and Retrieval|Internet|Mice|Models, Statistical|Oligonucleotide Array Sequence Analysis|Probability|Protein Splicing|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-189', '16042800', 'Microarray experiments, as well as other genomic analyses, often result in large gene sets containing up to several hundred genes. The biological significance of such sets of genes is, usually, not readily apparent. Identification of the functions of the genes in the set can help highlight features of interest. The Gene Ontology Consortium 1 has annotated genes in several model organisms using a controlled vocabulary of terms and placed the terms on a Gene Ontology (GO), which comprises three disjoint hierarchies for Molecular functions, Biological processes and Cellular locations. The annotations can be used to identify functions that are enriched in the set, but this analysis can be misleading since the underlying distribution of genes among various functions is not uniform. For example, a large number of genes in a set might be kinases just because the genome contains many kinases.'),
(90516, 2005, 'bmc', 'Information theory-based algorithm for in silico prediction of PCR products with whole genomic sequences as templates', 'Cao, Youfang|Wang, Lianjie|Xu, Kexue|Kou, Chunhai|Zhang, Yulei|Wei, Guifang|He, Junjian|Wang, Yunfang|Zhao, Liping', 'School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. yfcao@sjtu.edu.cn|School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. yfcao@sjtu.edu.cn|School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. yfcao@sjtu.edu.cn|School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. yfcao@sjtu.edu.cn|School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. yfcao@sjtu.edu.cn|School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. yfcao@sjtu.edu.cn|School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. yfcao@sjtu.edu.cn|School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. yfcao@sjtu.edu.cn|School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. yfcao@sjtu.edu.cn', 'China|China|China|China|China|China|China|China|China', 0, 'Algorithms|Conserved Sequence|Genes, rRNA|Genome, Bacterial|Information Storage and Retrieval|Models, Theoretical|Oligonucleotide Array Sequence Analysis|Polymerase Chain Reaction|Templates, Genetic', 'Comparative Study', '10.1186/1471-2105-6-190', '16042814', 'A new algorithm for assessing similarity between primer and template has been developed based on the hypothesis that annealing of primer to template is an information transfer process.'),
(90517, 2005, 'bmc', 'Evaluation of normalization methods for cDNA microarray data by k-NN classification', 'Wu, Wei|Xing, Eric P|Myers, Connie|Mian, I Saira|Bissell, Mina J', 'Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. wuw2@upmc.edu|Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. wuw2@upmc.edu|Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. wuw2@upmc.edu|Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. wuw2@upmc.edu|Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. wuw2@upmc.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Bias|Computational Biology|DNA, Complementary|Data Display|Electronic Data Processing|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Evaluation Studies', '10.1186/1471-2105-6-191', '16045803', 'Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification.'),
(90518, 2005, 'bmc', 'Storing, linking, and mining microarray databases using SRS', 'Veldhoven, Antoine|de Lange, Don|Smid, Marcel|de Jager, Victor|Kors, Jan A|Jenster, Guido', 'Department of Urology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. antoine@b2bdsl.nl|Department of Urology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. antoine@b2bdsl.nl|Department of Urology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. antoine@b2bdsl.nl|Department of Urology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. antoine@b2bdsl.nl|Department of Urology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. antoine@b2bdsl.nl|Department of Urology, Josephine Nefkens Institute, Erasmus MC, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands. antoine@b2bdsl.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Computational Biology|Data Collection|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-192', '16048644', 'SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range of different scientific databases in SRS, it has become a useful platform to incorporate and mine microarray data to facilitate the analyses of biological questions and non-hypothesis driven quests. Here we report various solutions and tools for integrating and mining annotated expression data in SRS.'),
(90519, 2005, 'bmc', 'Functional annotation by identification of local surface similarities: a novel tool for structural genomics', 'Ferrè, Fabrizio|Ausiello, Gabriele|Zanzoni, Andreas|Helmer-Citterich, Manuela', 'Boston College, Biology Department, Chestnut Hill MA, USA. ferref@bc.edu|Boston College, Biology Department, Chestnut Hill MA, USA. ferref@bc.edu|Boston College, Biology Department, Chestnut Hill MA, USA. ferref@bc.edu|Boston College, Biology Department, Chestnut Hill MA, USA. ferref@bc.edu', 'United States|United States|United States|United States', 31, 'Algorithms|Binding Sites|Computational Biology|Databases, Protein|False Negative Reactions|Genomics|Information Storage and Retrieval|Internet|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-6-194', '16076399', 'Protein function is often dependent on subsets of solvent-exposed residues that may exist in a similar three-dimensional configuration in non homologous proteins thus having different order and/or spacing in the sequence. Hence, functional annotation by means of sequence or fold similarity is not adequate for such cases.'),
(90520, 2005, 'bmc', 'Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm', 'Dawson, Kevin|Rodriguez, Raymond L|Malyj, Wasyl', 'Laboratory for High Performance Computing and Informatics, University of California, Davis MCB, One Shields Avenue, Davis, CA 95616, USA. kdawson@ucdavis.edu|Laboratory for High Performance Computing and Informatics, University of California, Davis MCB, One Shields Avenue, Davis, CA 95616, USA. kdawson@ucdavis.edu|Laboratory for High Performance Computing and Informatics, University of California, Davis MCB, One Shields Avenue, Davis, CA 95616, USA. kdawson@ucdavis.edu', 'United States|United States|United States', 0, 'Algorithms|Animals|Bias|Cell Death|Chromosome Mapping|Cluster Analysis|Computational Biology|Data Display|Drug Evaluation, Preclinical|HL-60 Cells|Humans|Models, Genetic|Neurons|Nonlinear Dynamics|Oligonucleotide Array Sequence Analysis|Rats|Spinal Cord Injuries', 'Journal Article', '10.1186/1471-2105-6-195', '16076401', 'Life processes are determined by the organisms genetic profile and multiple environmental variables. However the interaction between these factors is inherently non-linear. Microarray data is one representation of the nonlinear interactions among genes and genes and environmental factors. Still most microarray studies use linear methods for the interpretation of nonlinear data. In this study, we apply Isomap, a nonlinear method of dimensionality reduction, to analyze three independent large Affymetrix high-density oligonucleotide microarray data sets.'),
(90521, 2005, 'bmc', 'COPASAAR--a database for proteomic analysis of single amino acid repeats', 'Depledge, Daniel P|Dalby, Andrew R', 'School of Biological and Chemical Sciences and Engineering, Washington Singer Laboratories, University of Exeter, Prince of Wales Road, Exeter, EX4 4PS, UK. dan_depledge@hotmail.com|School of Biological and Chemical Sciences and Engineering, Washington Singer Laboratories, University of Exeter, Prince of Wales Road, Exeter, EX4 4PS, UK. dan_depledge@hotmail.com', 'United Kingdom|United Kingdom', 22, 'Algorithms|Amino Acid Sequence|Computational Biology|Databases, Protein|Information Storage and Retrieval|Internet|Models, Statistical|Proteins|Proteome|Repetitive Sequences, Amino Acid|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-6-196', '16078990', 'Single amino acid repeats make up a significant proportion in all of the proteomes that have currently been determined. They have been shown to be functionally and medically significant, and are associated with cancers and neuro-degenerative diseases such as Huntingtons Chorea, where a poly-glutamine repeat is responsible for causing the disease. The COPASAAR database is a new tool to facilitate the rapid analysis of single amino acid repeats at a proteome level. The database aims to simplify the comparison of repeat distributions between proteomes in order to provide a better understanding of their function and evolution.'),
(90522, 2005, 'bmc', 'Squid - a simple bioinformatics grid', 'Carvalho, Paulo C|Glória, Rafael V|de Miranda, Antonio B|Degrave, Wim M', 'Laboratory for Functional Genomics and Bioinformatics, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro, Brazil. carvalhopc@fiocruz.br|Laboratory for Functional Genomics and Bioinformatics, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro, Brazil. carvalhopc@fiocruz.br|Laboratory for Functional Genomics and Bioinformatics, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro, Brazil. carvalhopc@fiocruz.br|Laboratory for Functional Genomics and Bioinformatics, Oswaldo Cruz Institute, Fiocruz, Rio de Janeiro, Brazil. carvalhopc@fiocruz.br', 'Brazil|Brazil|Brazil|Brazil', 0, 'Base Sequence|Computational Biology|Computer Systems|Databases, Protein|Internet|Online Systems|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-197', '16078998', 'BLAST is a widely used genetic research tool for analysis of similarity between nucleotide and protein sequences. This paper presents a software application entitled Squid that makes use of grid technology. The current version, as an example, is configured for BLAST applications, but adaptation for other computing intensive repetitive tasks can be easily accomplished in the open source version. This enables the allocation of remote resources to perform distributed computing, making large BLAST queries viable without the need of high-end computers.'),
(90523, 2005, 'bmc', 'FIGENIX: intelligent automation of genomic annotation: expertise integration in a new software platform', 'Gouret, Philippe|Vitiello, Vérane|Balandraud, Nathalie|Gilles, André|Pontarotti, Pierre|Danchin, Etienne G J', 'EA 3781 EGEE (Evolution, Genome, Environment), Université de Provence, Case 36, Pl. V. Hugo, 13331 Marseille Cedex 03, France. Philippe.Gouret@up.univ-mrs.fr|EA 3781 EGEE (Evolution, Genome, Environment), Université de Provence, Case 36, Pl. V. Hugo, 13331 Marseille Cedex 03, France. Philippe.Gouret@up.univ-mrs.fr|EA 3781 EGEE (Evolution, Genome, Environment), Université de Provence, Case 36, Pl. V. Hugo, 13331 Marseille Cedex 03, France. Philippe.Gouret@up.univ-mrs.fr|EA 3781 EGEE (Evolution, Genome, Environment), Université de Provence, Case 36, Pl. V. Hugo, 13331 Marseille Cedex 03, France. Philippe.Gouret@up.univ-mrs.fr|EA 3781 EGEE (Evolution, Genome, Environment), Université de Provence, Case 36, Pl. V. Hugo, 13331 Marseille Cedex 03, France. Philippe.Gouret@up.univ-mrs.fr|EA 3781 EGEE (Evolution, Genome, Environment), Université de Provence, Case 36, Pl. V. Hugo, 13331 Marseille Cedex 03, France. Philippe.Gouret@up.univ-mrs.fr', 'France|France|France|France|France|France', 0, 'Automation|Computational Biology|Computer Communication Networks|Databases, Genetic|Documentation|Expert Systems|Gene Expression Profiling|Humans|Information Storage and Retrieval|Phylogeny|Programming Languages|Sequence Homology|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-198', '16083500', 'Two of the main objectives of the genomic and post-genomic era are to structurally and functionally annotate genomes which consists of detecting genes position and structure, and inferring their function (as well as of other features of genomes). Structural and functional annotation both require the complex chaining of numerous different software, algorithms and methods under the supervision of a biologist. The automation of these pipelines is necessary to manage huge amounts of data released by sequencing projects. Several pipelines already automate some of these complex chaining but still necessitate an important contribution of biologists for supervising and controlling the results at various steps.'),
(90524, 2005, 'bmc', 'A comparative review of estimates of the proportion unchanged genes and the false discovery rate', 'Broberg, Per', 'Biological Sciences, AstraZeneca R&D Lund, S-221 87 Lund, Sweden. per.broberg@astrazeneca.com', 'Sweden', 52, 'Amino Acid Sequence|Base Sequence|Computational Biology|DNA|False Positive Reactions|Gene Order|Microarray Analysis|Models, Genetic|Models, Molecular|Templates, Genetic|Transcription, Genetic', 'Comparative Study', '10.1186/1471-2105-6-199', '16086831', 'In the analysis of microarray data one generally produces a vector of p-values that for each gene give the likelihood of obtaining equally strong evidence of change by pure chance. The distribution of these p-values is a mixture of two components corresponding to the changed genes and the unchanged ones. The focus of this article is how to estimate the proportion unchanged and the false discovery rate (FDR) and how to make inferences based on these concepts. Six published methods for estimating the proportion unchanged genes are reviewed, two alternatives are presented, and all are tested on both simulated and real data. All estimates but one make do without any parametric assumptions concerning the distributions of the p-values. Furthermore, the estimation and use of the FDR and the closely related q-value is illustrated with examples. Five published estimates of the FDR and one new are presented and tested. Implementations in R code are available.'),
(90525, 2005, 'bmc', 'Genomic multiple sequence alignments: refinement using a genetic algorithm', 'Wang, Chunlin|Lefkowitz, Elliot J', 'Department of Microbiology, University of Alabama, Birmingham, Alabama 35294-2170, USA. wangcl@uab.edu|Department of Microbiology, University of Alabama, Birmingham, Alabama 35294-2170, USA. wangcl@uab.edu', 'United States|United States', 20, 'Algorithms|Cluster Analysis|Genome|Models, Genetic|Models, Molecular|Orthopoxvirus|Sequence Alignment|Software', 'Evaluation Studies', '10.1186/1471-2105-6-200', '16086841', 'Genomic sequence data cannot be fully appreciated in isolation. Comparative genomics--the practice of comparing genomic sequences from different species--plays an increasingly important role in understanding the genotypic differences between species that result in phenotypic differences as well as in revealing patterns of evolutionary relationships. One of the major challenges in comparative genomics is producing a high-quality alignment between two or more related genomic sequences. In recent years, a number of tools have been developed for aligning large genomic sequences. Most utilize heuristic strategies to identify a series of strong sequence similarities, which are then used as anchors to align the regions between the anchor points. The resulting alignment is globally correct, but in many cases is suboptimal locally. We describe a new program, GenAlignRefine, which improves the overall quality of global multiple alignments by using a genetic algorithm to improve local regions of alignment. Regions of low quality are identified, realigned using the program T-Coffee, and then refined using a genetic algorithm. Because a better COFFEE (Consistency based Objective Function For alignmEnt Evaluation) score generally reflects greater alignment quality, the algorithm searches for an alignment that yields a better COFFEE score. To improve the intrinsic slowness of the genetic algorithm, GenAlignRefine was implemented as a parallel, cluster-based program.'),
(90526, 2005, 'bmc', 'DynGO: a tool for visualizing and mining of Gene Ontology and its associations', 'Liu, Hongfang|Hu, Zhang-Zhi|Wu, Cathy H', 'Department of Information Systems, University of Maryland, Baltimore County, 1000 Hilltop Circle, MD 21050, USA. hfliu@umbc.edu|Department of Information Systems, University of Maryland, Baltimore County, 1000 Hilltop Circle, MD 21050, USA. hfliu@umbc.edu|Department of Information Systems, University of Maryland, Baltimore County, 1000 Hilltop Circle, MD 21050, USA. hfliu@umbc.edu', 'United States|United States|United States', 0, 'Computer Graphics|Data Display|Databases, Genetic|Documentation|Genes|Information Storage and Retrieval|Semantics|Software|User-Computer Interface|Vocabulary', 'Journal Article', '10.1186/1471-2105-6-201', '16091147', 'A large volume of data and information about genes and gene products has been stored in various molecular biology databases. A major challenge for knowledge discovery using these databases is to identify related genes and gene products in disparate databases. The development of Gene Ontology (GO) as a common vocabulary for annotation allows integrated queries across multiple databases and identification of semantically related genes and gene products (i.e., genes and gene products that have similar GO annotations). Meanwhile, dozens of tools have been developed for browsing, mining or editing GO terms, their hierarchical relationships, or their associated genes and gene products (i.e., genes and gene products annotated with GO terms). Tools that allow users to directly search and inspect relations among all GO terms and their associated genes and gene products from multiple databases are needed.'),
(90527, 2005, 'bmc', 'PALSSE: a program to delineate linear secondary structural elements from protein structures', 'Majumdar, Indraneel|Krishna, S Sri|Grishin, Nick V', 'Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, USA. indraneel@chop.swmed.edu|Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, USA. indraneel@chop.swmed.edu|Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, USA. indraneel@chop.swmed.edu', 'United States|United States|United States', 0, 'Algorithms|Computational Biology|Data Display|Databases, Protein|Protein Structure, Secondary|Reproducibility of Results|Software', 'Comparative Study', '10.1186/1471-2105-6-202', '16095538', 'The majority of residues in protein structures are involved in the formation of alpha-helices and beta-strands. These distinctive secondary structure patterns can be used to represent a protein for visual inspection and in vector-based protein structure comparison. Success of such structural comparison methods depends crucially on the accurate identification and delineation of secondary structure elements.'),
(90528, 2005, 'bmc', 'Calibration of mass spectrometric peptide mass fingerprint data without specific external or internal calibrants', 'Wolski, Witold E|Lalowski, Maciej|Jungblut, Peter|Reinert, Knut', 'Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk', 'Germany|Germany|Germany|Germany', 18, 'Algorithms|Animals|Calibration|Computers, Molecular|Mass Spectrometry|Mice|Open Reading Frames|Peptide Mapping|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-6-203', '16102175', 'Peptide Mass Fingerprinting (PMF) is a widely used mass spectrometry (MS) method of analysis of proteins and peptides. It relies on the comparison between experimentally determined and theoretical mass spectra. The PMF process requires calibration, usually performed with external or internal calibrants of known molecular masses.'),
(90529, 2005, 'bmc', 'Tandem machine learning for the identification of genes regulated by transcription factors', 'Dinakarpandian, Deendayal|Raheja, Venetia|Mehta, Saumil|Schuetz, Erin G|Rogan, Peter K', 'School of Computing and Engineering, University Of Missouri-Kansas City, Kansas City, Missouri, USA. dinakard@umkc.edu|School of Computing and Engineering, University Of Missouri-Kansas City, Kansas City, Missouri, USA. dinakard@umkc.edu|School of Computing and Engineering, University Of Missouri-Kansas City, Kansas City, Missouri, USA. dinakard@umkc.edu|School of Computing and Engineering, University Of Missouri-Kansas City, Kansas City, Missouri, USA. dinakard@umkc.edu|School of Computing and Engineering, University Of Missouri-Kansas City, Kansas City, Missouri, USA. dinakard@umkc.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Binding Sites|Chromosome Mapping|Cluster Analysis|Gene Expression Profiling|Nucleic Acids|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Pregnane X Receptor|Receptors, Cytoplasmic and Nuclear|Receptors, Steroid|Transcription Factors', 'Evaluation Studies', '10.1186/1471-2105-6-204', '16115317', 'The identification of promoter regions that are regulated by a given transcription factor has traditionally relied upon the identification and distributions of binding sites recognized by the factor. In this study, we have developed a tandem machine learning approach for the identification of regulatory target genes based on these parameters and on the corresponding binding site information contents that measure the affinities of the factor for these cognate elements.'),
(90530, 2005, 'bmc', 'A comparative study of discriminating human heart failure etiology using gene expression profiles', 'Huang, Xiaohong|Pan, Wei|Grindle, Suzanne|Han, Xinqiang|Chen, Yingjie|Park, Soon J|Miller, Leslie W|Hall, Jennifer', 'Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. xiaohong@biostat.umn.edu|Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. xiaohong@biostat.umn.edu|Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. xiaohong@biostat.umn.edu|Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. xiaohong@biostat.umn.edu|Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. xiaohong@biostat.umn.edu|Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. xiaohong@biostat.umn.edu|Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. xiaohong@biostat.umn.edu|Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. xiaohong@biostat.umn.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 44, 'Data Interpretation, Statistical|Gene Expression Profiling|Heart Failure|Humans|Linear Models|Male|Models, Genetic|Models, Statistical|Myocardial Ischemia|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1186/1471-2105-6-205', '16120216', 'Human heart failure is a complex disease that manifests from multiple genetic and environmental factors. Although ischemic and non-ischemic heart disease present clinically with many similar decreases in ventricular function, emerging work suggests that they are distinct diseases with different responses to therapy. The ability to distinguish between ischemic and non-ischemic heart failure may be essential to guide appropriate therapy and determine prognosis for successful treatment. In this paper we consider discriminating the etiologies of heart failure using gene expression libraries from two separate institutions.'),
(90531, 2005, 'bmc', 'Genomes are covered with ubiquitous 11 bp periodic patterns, the class A flexible patterns', 'Larsabal, Etienne|Danchin, Antoine', 'Unité de Génétique des Génomes Bactériens, Institut Pasteur, URA CNRS 2171, 28 Rue du Docteur Roux, 75724 Paris Cedex 15, France. etienne.larsabal@normalesup.org|Unité de Génétique des Génomes Bactériens, Institut Pasteur, URA CNRS 2171, 28 Rue du Docteur Roux, 75724 Paris Cedex 15, France. etienne.larsabal@normalesup.org', 'France|France', 0, 'Computers, Molecular|DNA|Eukaryotic Cells|Genome|Models, Genetic|Nucleic Acid Conformation|Nucleotide Mapping|Pattern Recognition, Automated|Periodicity|Probability|Prokaryotic Cells|Repetitive Sequences, Nucleic Acid|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-6-206', '16120222', 'The genomes of prokaryotes and lower eukaryotes display a very strong 11 bp periodic bias in the distribution of their nucleotides. This bias is present throughout a given genome, both in coding and non-coding sequences. Until now this bias remained of unknown origin.'),
(90532, 2005, 'bmc', 'A protein domain interaction interface database: InterPare', 'Gong, Sungsam|Park, Changbum|Choi, Hansol|Ko, Junsu|Jang, Insoo|Lee, Jungsul|Bolser, Dan M|Oh, Donghoon|Kim, Deok-Soo|Bhak, Jong', 'National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr|National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr|National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr|National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr|National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr|National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr|National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr|National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr|National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr|National Genome Information Center, KRIBB, Daejeon, Korea. ssgong@kaist.ac.kr', '-|-|-|-|-|-|-|-|-|-', 44, 'Computers, Molecular|Databases, Protein|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1186/1471-2105-6-207', '16122378', 'Most proteins function by interacting with other molecules. Their interaction interfaces are highly conserved throughout evolution to avoid undesirable interactions that lead to fatal disorders in cells. Rational drug discovery includes computational methods to identify the interaction sites of lead compounds to the target molecules. Identifying and classifying protein interaction interfaces on a large scale can help researchers discover drug targets more efficiently.'),
(90533, 2005, 'bmc', 'An edit script for taxonomic classifications', 'Page, Roderic D M|Valiente, Gabriel', 'DEEB, IBLS, University of Glasgow, Glasgow G12 8QQ, UK. r.page@bio.gla.ac.uk|DEEB, IBLS, University of Glasgow, Glasgow G12 8QQ, UK. r.page@bio.gla.ac.uk', 'United Kingdom|United Kingdom', 44, 'Algorithms|Animals|Classification|Computers, Molecular|Databases, Genetic|Databases, Nucleic Acid|Humans|Phylogeny|Species Specificity', 'Journal Article', '10.1186/1471-2105-6-207', '16122379', 'The NCBI taxonomy provides one of the most powerful ways to navigate sequence data bases but currently users are forced to formulate queries according to a single taxonomic classification. Given that there is not universal agreement on the classification of organisms, providing a single classification places constraints on the questions biologists can ask. However, maintaining multiple classifications is burdensome in the face of a constantly growing NCBI classification.'),
(90534, 2005, 'bmc', 'FiatFlux--a software for metabolic flux analysis from 13C-glucose experiments', 'Zamboni, Nicola|Fischer, Eliane|Sauer, Uwe', 'Institute of Biotechnology, ETH Zurich, 8093 Zurich, Switzerland. nzamboni@imsb.biol.ethz.ch|Institute of Biotechnology, ETH Zurich, 8093 Zurich, Switzerland. nzamboni@imsb.biol.ethz.ch|Institute of Biotechnology, ETH Zurich, 8093 Zurich, Switzerland. nzamboni@imsb.biol.ethz.ch', 'Switzerland|Switzerland|Switzerland', 0, 'Bacteria|Biomass|Carbon Radioisotopes|Computers, Molecular|Glucose|Glucose Clamp Technique|Models, Biological|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-209', '16122385', 'Quantitative knowledge of intracellular fluxes is important for a comprehensive characterization of metabolic networks and their functional operation. In contrast to direct assessment of metabolite concentrations, in vivo metabolite fluxes must be inferred indirectly from measurable quantities in 13C experiments. The required experience, the complicated network models, large and heterogeneous data sets, and the time-consuming set-up of highly controlled experimental conditions largely restricted metabolic flux analysis to few expert groups. A conceptual simplification of flux analysis is the analytical determination of metabolic flux ratios exclusively from MS data, which can then be used in a second step to estimate absolute in vivo fluxes.'),
(90535, 2005, 'bmc', 'Variation in structural location and amino acid conservation of functional sites in protein domain families', 'Pils, Birgit|Copley, Richard R|Schultz, Jörg', 'Department of Bioinformatics, University of Würzburg, Biocenter, Am Hubland, 97074 Würzburg, Germany. birgit.pils@biozentrum.uni-wuerzburg.de|Department of Bioinformatics, University of Würzburg, Biocenter, Am Hubland, 97074 Würzburg, Germany. birgit.pils@biozentrum.uni-wuerzburg.de|Department of Bioinformatics, University of Würzburg, Biocenter, Am Hubland, 97074 Würzburg, Germany. birgit.pils@biozentrum.uni-wuerzburg.de', 'Germany|Germany|Germany', 20, 'Amino Acid Sequence|Computational Biology|Computers, Molecular|Conserved Sequence|DNA Probes|Databases, Genetic|Ligands|Nucleotides|Peptides|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Homology', 'Journal Article', '10.1186/1471-2105-6-210', '16122386', 'The functional sites of a protein present important information for determining its cellular function and are fundamental in drug design. Accordingly, accurate methods for the prediction of functional sites are of immense value. Most available methods are based on a set of homologous sequences and structural or evolutionary information, and assume that functional sites are more conserved than the average. In the analysis presented here, we have investigated the conservation of location and type of amino acids at functional sites, and compared the behaviour of functional sites between different protein domains.'),
(90536, 2005, 'bmc', 'stam--a Bioconductor compliant R package for structured analysis of microarray data', 'Lottaz, Claudio|Spang, Rainer', 'Max Planck Institute for Molecular Genetics, Berlin Center for Genome Based Bioinformatics, Ihnestr. 73, D-14195 Berlin, Germany. Claudio.Lottaz@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Berlin Center for Genome Based Bioinformatics, Ihnestr. 73, D-14195 Berlin, Germany. Claudio.Lottaz@molgen.mpg.de', 'Germany|Germany', 1, 'Calibration|Cluster Analysis|Computers, Molecular|Gene Expression Profiling|Humans|Internet|Phenotype|Protein Array Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-211', '16122395', 'Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles. The definition of novel subclasses based on gene expression is a difficult problem not addressed systematically by currently available software tools.'),
(90537, 2005, 'bmc', 'A new dynamical layout algorithm for complex biochemical reaction networks', 'Wegner, Katja|Kummer, Ursula', 'Bioinformatics and Computational Biochemistry, EML Research, Schloss-Wolfsbrunnenweg 33, D-69118 Heidelberg, Germany. Katja.Wegner@eml-r.villa-bosch.de|Bioinformatics and Computational Biochemistry, EML Research, Schloss-Wolfsbrunnenweg 33, D-69118 Heidelberg, Germany. Katja.Wegner@eml-r.villa-bosch.de', 'Germany|Germany', 20, 'Algorithms|Biochemical Phenomena|Computational Biology|Computer Graphics|Computers, Molecular|Data Display', 'Journal Article', '10.1186/1471-2105-6-212', '16124872', 'To study complex biochemical reaction networks in living cells researchers more and more rely on databases and computational methods. In order to facilitate computational approaches, visualisation techniques are highly important. Biochemical reaction networks, e.g. metabolic pathways are often depicted as graphs and these graphs should be drawn dynamically to provide flexibility in the context of different data. Conventional layout algorithms are not sufficient for every kind of pathway in biochemical research. This is mainly due to certain conventions to which biochemists/biologists are used to and which are not in accordance to conventional layout algorithms. A number of approaches has been developed to improve this situation. Some of these are used in the context of biochemical databases and make more or less use of the information in these databases to aid the layout process. However, visualisation becomes also more and more important in modelling and simulation tools which mostly do not offer additional connections to databases. Therefore, layout algorithms used in these tools have to work independently of any databases. In addition, all of the existing algorithms face some limitations with respect to the number of edge crossings when it comes to larger biochemical systems due to the interconnectivity of these. Last but not least, in some cases, biochemical conventions are not met properly.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90538, 2005, 'bmc', 'Improved prediction of critical residues for protein function based on network and phylogenetic analyses', 'Thibert, Boris|Bredesen, Dale E|del Rio, Gabriel', 'Buck Institute For Age Research, 8001 Redwood Blvd, Novato, CA 94945, USA. thibert@math.univ-lyon1.fr|Buck Institute For Age Research, 8001 Redwood Blvd, Novato, CA 94945, USA. thibert@math.univ-lyon1.fr|Buck Institute For Age Research, 8001 Redwood Blvd, Novato, CA 94945, USA. thibert@math.univ-lyon1.fr', 'United States|United States|United States', 55, 'Computational Biology|Neural Networks (Computer)|Phylogeny|Protein Interaction Mapping|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1186/1471-2105-6-213', '16124876', 'Phylogenetic approaches are commonly used to predict which amino acid residues are critical to the function of a given protein. However, such approaches display inherent limitations, such as the requirement for identification of multiple homologues of the protein under consideration. Therefore, complementary or alternative approaches for the prediction of critical residues would be desirable. Network analyses have been used in the modelling of many complex biological systems, but only very recently have they been used to predict critical residues from a proteins three-dimensional structure. Here we compare a couple of phylogenetic approaches to several different network-based methods for the prediction of critical residues, and show that a combination of one phylogenetic method and one network-based method is superior to other methods previously employed.'),
(90539, 2005, 'bmc', 'Sources of variation in Affymetrix microarray experiments', 'Zakharkin, Stanislav O|Kim, Kyoungmi|Mehta, Tapan|Chen, Lang|Barnes, Stephen|Scheirer, Katherine E|Parrish, Rudolph S|Allison, David B|Page, Grier P', 'University of Alabama, Birmingham, Alabama, USA. szakharkin@ms.soph.uab.edu|University of Alabama, Birmingham, Alabama, USA. szakharkin@ms.soph.uab.edu|University of Alabama, Birmingham, Alabama, USA. szakharkin@ms.soph.uab.edu|University of Alabama, Birmingham, Alabama, USA. szakharkin@ms.soph.uab.edu|University of Alabama, Birmingham, Alabama, USA. szakharkin@ms.soph.uab.edu|University of Alabama, Birmingham, Alabama, USA. szakharkin@ms.soph.uab.edu|University of Alabama, Birmingham, Alabama, USA. szakharkin@ms.soph.uab.edu|University of Alabama, Birmingham, Alabama, USA. szakharkin@ms.soph.uab.edu|University of Alabama, Birmingham, Alabama, USA. szakharkin@ms.soph.uab.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 86, 'Animals|Computers, Molecular|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Quality Control|Rats|Rats, Sprague-Dawley|Reproducibility of Results', 'Evaluation Studies', '10.1186/1471-2105-6-214', '16124883', 'A typical microarray experiment has many sources of variation which can be attributed to biological and technical causes. Identifying sources of variation and assessing their magnitude, among other factors, are important for optimal experimental design. The objectives of this study were: (1) to estimate relative magnitudes of different sources of variation and (2) to evaluate agreement between biological and technical replicates.'),
(90540, 2005, 'bmc', 'Dynamic covariation between gene expression and proteome characteristics', 'Sharabiani, Mansour Taghavi Azar|Siermala, Markku|Lehtinen, Tommi O|Vihinen, Mauno', 'Institute of Medical Technology, FI-33014 University of Tampere, Finland. memata@gmail.com|Institute of Medical Technology, FI-33014 University of Tampere, Finland. memata@gmail.com|Institute of Medical Technology, FI-33014 University of Tampere, Finland. memata@gmail.com|Institute of Medical Technology, FI-33014 University of Tampere, Finland. memata@gmail.com', 'Finland|Finland|Finland|Finland', 8, 'Animals|B-Lymphocytes|Cell Cycle|Computational Biology|Data Display|Drosophila melanogaster|Electronic Data Processing|Gene Expression Profiling|Gene Frequency|Humans|Information Storage and Retrieval|Lymphocyte Activation|Markov Chains|Models, Biological|Oligonucleotide Array Sequence Analysis|Proteome|Saccharomyces cerevisiae|Sequence Analysis, Protein|Signal Transduction|Software|T-Lymphocytes', 'Journal Article', '10.1186/1471-2105-6-215', '16131395', 'Cells react to changing intra- and extracellular signals by dynamically modulating complex biochemical networks. Cellular responses to extracellular signals lead to changes in gene and protein expression. Since the majority of genes encode proteins, we investigated possible correlations between protein parameters and gene expression patterns to identify proteome-wide characteristics indicative of trends common to expressed proteins.'),
(90541, 2005, 'bmc', 'JACOP: a simple and robust method for the automated classification of protein sequences with modular architecture', 'Sperisen, Peter|Pagni, Marco', 'Swiss Institute of Bioinformatics, Computational Cancer Genomics Group-ISREC, Ch. des Boveresses 155, 1066 Epalinges, Switzerland. peter.sperisen@isb-sib.ch|Swiss Institute of Bioinformatics, Computational Cancer Genomics Group-ISREC, Ch. des Boveresses 155, 1066 Epalinges, Switzerland. peter.sperisen@isb-sib.ch', 'Switzerland|Switzerland', 18, 'Algorithms|Cluster Analysis|Lyases|Molecular Probes|Prokaryotic Cells|Reproducibility of Results|Sequence Analysis, Protein|Software|src Homology Domains', 'Journal Article', '10.1186/1471-2105-6-216', '16135248', 'Whole-genome sequencing projects are rapidly producing an enormous number of new sequences. Consequently almost every family of proteins now contains hundreds of members. It has thus become necessary to develop tools, which classify protein sequences automatically and also quickly and reliably. The difficulty of this task is intimately linked to the mechanism by which protein sequences diverge, i.e. by simultaneous residue substitutions, insertions and/or deletions and whole domain reorganisations (duplications/swapping/fusion).'),
(90542, 2005, 'bmc', 'Automation of gene assignments to metabolic pathways using high-throughput expression data', 'Popescu, Liviu|Yona, Golan', 'Department of Computer Science, Cornell University, Ithaca, NY, USA. liviup@cs.cornell.edu|Department of Computer Science, Cornell University, Ithaca, NY, USA. liviup@cs.cornell.edu', 'United States|United States', 9, 'Algorithms|Asparagine|Electronic Data Processing|Folic Acid|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-6-217', '16135255', 'Accurate assignment of genes to pathways is essential in order to understand the functional role of genes and to map the existing pathways in a given genome. Existing algorithms predict pathways by extrapolating experimental data in one organism to other organisms for which this data is not available. However, current systems classify all genes that belong to a specific EC family to all the pathways that contain the corresponding enzymatic reaction, and thus introduce ambiguity.'),
(90543, 2005, 'bmc', 'TmaDB: a repository for tissue microarray data', 'Sharma-Oates, Archana|Quirke, Philip|Westhead, David R', 'Academic Unit of Pathology, University of Leeds, Leeds, LS1 3EX, UK. a.sharmaoates@leeds.ac.uk|Academic Unit of Pathology, University of Leeds, Leeds, LS1 3EX, UK. a.sharmaoates@leeds.ac.uk|Academic Unit of Pathology, University of Leeds, Leeds, LS1 3EX, UK. a.sharmaoates@leeds.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 16, 'Data Interpretation, Statistical|Databases, Genetic|Decision Support Techniques|Electronic Data Processing|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-6-218', '16137321', 'Tissue microarray (TMA) technology has been developed to facilitate large, genome-scale molecular pathology studies. This technique provides a high-throughput method for analyzing a large cohort of clinical specimens in a single experiment thereby permitting the parallel analysis of molecular alterations (at the DNA, RNA, or protein level) in thousands of tissue specimens. As a vast quantity of data can be generated in a single TMA experiment a systematic approach is required for the storage and analysis of such data.'),
(90544, 2005, 'bmc', 'Generalizations of Markov model to characterize biological sequences', 'Wang, Junwen|Hannenhalli, Sridhar', 'Penn Center for Bioinformatics, Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104-6021, USA. junwen@pcbi.upenn.edu|Penn Center for Bioinformatics, Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104-6021, USA. junwen@pcbi.upenn.edu', 'United States|United States', 11, 'Base Sequence|Exons|Humans|Markov Chains|Models, Genetic|Models, Statistical|Nucleosomes|Promoter Regions, Genetic', 'Evaluation Studies', '10.1186/1471-2105-6-219', '16144548', 'The currently used kth order Markov models estimate the probability of generating a single nucleotide conditional upon the immediately preceding (gap = 0) k units. However, this neither takes into account the joint dependency of multiple neighboring nucleotides, nor does it consider the long range dependency with gap > 0.'),
(90545, 2005, 'bmc', 'A method for finding single-nucleotide polymorphisms with allele frequencies in sequences of deep coverage', 'Wang, Jianmin|Huang, Xiaoqiu', 'Department of Computer Science, Iowa State University, Ames, Iowa 50011, USA. wangjm@cs.iastate.edu|Department of Computer Science, Iowa State University, Ames, Iowa 50011, USA. wangjm@cs.iastate.edu', 'United States|United States', 6, 'Computers, Molecular|Expressed Sequence Tags|Gene Frequency|Humans|Information Storage and Retrieval|Polymorphism, Single Nucleotide|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-6-220', '16146575', 'The allele frequencies of single-nucleotide polymorphisms (SNPs) are needed to select an optimal subset of common SNPs for use in association studies. Sequence-based methods for finding SNPs with allele frequencies may need to handle thousands of sequences from the same genome location (sequences of deep coverage).'),
(90546, 2005, 'bmc', 'GASH: an improved algorithm for maximizing the number of equivalent residues between two protein structures', 'Standley, Daron M|Toh, Hiroyuki|Nakamura, Haruki', 'Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka 565-0871, Japan. standley@protein.osaka-u.ac.jp|Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka 565-0871, Japan. standley@protein.osaka-u.ac.jp|Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka 565-0871, Japan. standley@protein.osaka-u.ac.jp', 'Japan|Japan|Japan', 20, 'Algorithms|Proteins|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-6-221', '16146579', 'We introduce GASH, a new, publicly accessible program for structural alignment and superposition. Alignments are scored by the Number of Equivalent Residues (NER), a quantitative measure of structural similarity that can be applied to any structural alignment method. Multiple alignments are optimized by conjugate gradient maximization of the NER score within the genetic algorithm framework. Initial alignments are generated by the program Local ASH, and can be supplemented by alignments from any other program.'),
(90547, 2005, 'bmc', 'Micro-Mar: a database for dynamic representation of marine microbial biodiversity', 'Pushker, Ravindra|DAuria, Giuseppe|Alba-Casado, Jose Carlos|Rodríguez-Valera, Francisco', 'Evolutionary Genomics Group, Universidad Miguel Hernández, Apartado 18, 03550 San Juan de Alicante, Alicante, Spain. pushker@umh.es|Evolutionary Genomics Group, Universidad Miguel Hernández, Apartado 18, 03550 San Juan de Alicante, Alicante, Spain. pushker@umh.es|Evolutionary Genomics Group, Universidad Miguel Hernández, Apartado 18, 03550 San Juan de Alicante, Alicante, Spain. pushker@umh.es|Evolutionary Genomics Group, Universidad Miguel Hernández, Apartado 18, 03550 San Juan de Alicante, Alicante, Spain. pushker@umh.es', 'Spain|Spain|Spain|Spain', 7, 'Base Sequence|Biodiversity|Classification|Databases, Factual|Databases, Genetic|Ecosystem|Information Storage and Retrieval|Marine Biology|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-6-222', '16153293', 'The cataloging of marine prokaryotic DNA sequences is a fundamental aspect for bioprospecting and also for the development of evolutionary and speciation models. However, large amount of DNA sequences used to quantify prokaryotic biodiversity requires proper tools for storing, managing and analyzing these data for research purposes.'),
(90548, 2005, 'bmc', 'SUPERFICIAL--surface mapping of proteins via structure-based peptide library design', 'Goede, Andrean|Jaeger, Ines S|Preissner, Robert', 'Berlin Center for Genome Based Bioinformatics, 3D Data Mining Group, Institute of Biochemistry, Charité, Monbijoustr. 2, 10117 Berlin, Germany. Andrean.Goede@charite.de|Berlin Center for Genome Based Bioinformatics, 3D Data Mining Group, Institute of Biochemistry, Charité, Monbijoustr. 2, 10117 Berlin, Germany. Andrean.Goede@charite.de|Berlin Center for Genome Based Bioinformatics, 3D Data Mining Group, Institute of Biochemistry, Charité, Monbijoustr. 2, 10117 Berlin, Germany. Andrean.Goede@charite.de', 'Germany|Germany|Germany', 10, 'Binding Sites|Peptide Library|Peptide Mapping|Proteins|Software', 'Journal Article', '10.1186/1471-2105-6-223', '16153304', 'The determination of protein surfaces and the detection of binding sites are essential to our understanding of protein-protein interactions. Such binding sites can be characterised as linear and non-linear, the non-linear sites being prevailant. Conventional mapping techniques with arrays of synthetic peptides have limitations with regard to the location of discontinuous or non-linear binding sites of proteins.'),
(90549, 2005, 'bmc', 'Versatile and declarative dynamic programming using pair algebras', 'Steffen, Peter|Giegerich, Robert', 'Faculty of Technology, Bielefeld University, Postfach 10 01 31, 33501 Bielefeld, Germany. psteffen@techfak.uni-bielefeld.de|Faculty of Technology, Bielefeld University, Postfach 10 01 31, 33501 Bielefeld, Germany. psteffen@techfak.uni-bielefeld.de', 'Germany|Germany', 22, 'Algorithms|Computational Biology|Data Interpretation, Statistical|Mathematics|Models, Genetic|Protein Structure, Secondary|RNA|Software Design', 'Journal Article', '10.1186/1471-2105-6-224', '16156887', 'Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of textbook examples, implementing a dynamic programming algorithm for a novel and non-trivial application is a tedious and error prone task. The algebraic dynamic programming approach seeks to alleviate this situation by clearly separating the dynamic programming recurrences and scoring schemes.'),
(90550, 2005, 'bmc', 'Pathway level analysis of gene expression using singular value decomposition', 'Tomfohr, John|Lu, Jun|Kepler, Thomas B', 'Department of Biostatistics and Bioinformatics, Center for Bioinformatics and Computational Biology, Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina 27708, USA. tomfohr@duke.edu|Department of Biostatistics and Bioinformatics, Center for Bioinformatics and Computational Biology, Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina 27708, USA. tomfohr@duke.edu|Department of Biostatistics and Bioinformatics, Center for Bioinformatics and Computational Biology, Institute for Genome Sciences and Policy, Duke University, Durham, North Carolina 27708, USA. tomfohr@duke.edu', 'United States|United States|United States', 190, 'Blood Glucose|Cyclic AMP-Dependent Protein Kinases|Diabetes Mellitus, Type 2|Gene Expression Profiling|Glutathione|Humans|Muscle, Skeletal|Nicotine|Respiratory Mucosa|Smoking|Software|Up-Regulation', 'Journal Article', '10.1186/1471-2105-6-225', '16156896', 'A promising direction in the analysis of gene expression focuses on the changes in expression of specific predefined sets of genes that are known in advance to be related (e.g., genes coding for proteins involved in cellular pathways or complexes). Such an analysis can reveal features that are not easily visible from the variations in the individual genes and can lead to a picture of expression that is more biologically transparent and accessible to interpretation. In this article, we present a new method of this kind that operates by quantifying the level of activity of each pathway in different samples. The activity levels, which are derived from singular value decompositions, form the basis for statistical comparisons and other applications.'),
(90551, 2005, 'bmc', 'Assessing local structural perturbations in proteins', 'Lema, Martin A|Echave, Julian', 'Universidad Nacional de Quilmes, Roque Sáenz Peña 180, B1876BXD Bernal, Buenos Aires, Argentina. mlema@unq.edu.ar|Universidad Nacional de Quilmes, Roque Sáenz Peña 180, B1876BXD Bernal, Buenos Aires, Argentina. mlema@unq.edu.ar', 'Argentina|Argentina', 2, 'Algorithms|Data Display|Models, Molecular|Models, Structural|Proteins|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-6-226', '16159393', 'Protein structure research often deals with the comparison of two or more structures of the same protein, for instance when handling alternative structure models for the same protein, point mutants, molecule movements, structure predictions, etc. Often the difference between structures is small, restricted to a local neighborhood, and buried in structural noise due to trivial differences resulting from experimental artifacts. In such cases, whole-structure comparisons by means of structure superposition may be unsatisfactory and researchers have to perform a tedious process of manually superposing different segments individually and/or use different frames of reference, chosen roughly by educated guessing.'),
(90552, 2005, 'bmc', 'Systematic survey reveals general applicability of guilt-by-association within gene coexpression networks', 'Wolfe, Cecily J|Kohane, Isaac S|Butte, Atul J', 'Childrens Hospital Informatics Program and Harvard MIT Division of Health Sciences and Technology, 300 Longwood Avenue, Boston, MA 02115, USA. cecily@soest.hawaii.edu|Childrens Hospital Informatics Program and Harvard MIT Division of Health Sciences and Technology, 300 Longwood Avenue, Boston, MA 02115, USA. cecily@soest.hawaii.edu|Childrens Hospital Informatics Program and Harvard MIT Division of Health Sciences and Technology, 300 Longwood Avenue, Boston, MA 02115, USA. cecily@soest.hawaii.edu', 'United States|United States|United States', 233, 'Animals|Bone Development|Feeding Behavior|Gene Expression Profiling|Humans|Mice|Oligonucleotide Array Sequence Analysis|Phylogeny|Probability|ROC Curve|Rats|Receptors, Neuropeptide|Reproducibility of Results|Species Specificity|Synteny', 'Journal Article', '10.1186/1471-2105-6-227', '16162296', 'Biological processes are carried out by coordinated modules of interacting molecules. As clustering methods demonstrate that genes with similar expression display increased likelihood of being associated with a common functional module, networks of coexpressed genes provide one framework for assigning gene function. This has informed the guilt-by-association (GBA) heuristic, widely invoked in functional genomics. Yet although the idea of GBA is accepted, the breadth of GBA applicability is uncertain.'),
(90553, 2005, 'bmc', 'Modeling the emergence of multi-protein dynamic structures by principles of self-organization through the use of 3DSpi, a multi-agent-based software', 'Soula, Hédi|Robardet, Céline|Perrin, François|Gripon, Sébastien|Beslon, Guillaume|Gandrillon, Olivier', 'Laboratoire de Productique et dInformatique des Systèmes Manufacturiers, Institut National des Sciences Appliquées de Lyon, Villeurbanne, France. hedi.soula@insa-lyon.fr|Laboratoire de Productique et dInformatique des Systèmes Manufacturiers, Institut National des Sciences Appliquées de Lyon, Villeurbanne, France. hedi.soula@insa-lyon.fr|Laboratoire de Productique et dInformatique des Systèmes Manufacturiers, Institut National des Sciences Appliquées de Lyon, Villeurbanne, France. hedi.soula@insa-lyon.fr|Laboratoire de Productique et dInformatique des Systèmes Manufacturiers, Institut National des Sciences Appliquées de Lyon, Villeurbanne, France. hedi.soula@insa-lyon.fr|Laboratoire de Productique et dInformatique des Systèmes Manufacturiers, Institut National des Sciences Appliquées de Lyon, Villeurbanne, France. hedi.soula@insa-lyon.fr|Laboratoire de Productique et dInformatique des Systèmes Manufacturiers, Institut National des Sciences Appliquées de Lyon, Villeurbanne, France. hedi.soula@insa-lyon.fr', 'France|France|France|France|France|France', 8, 'Cellular Structures|Microscopy, Confocal|Models, Chemical|Models, Molecular|Molecular Structure|Proteins|Software', 'Journal Article', '10.1186/1471-2105-6-228', '16171521', 'There is an increasing need for computer-generated models that can be used for explaining the emergence and predicting the behavior of multi-protein dynamic structures in cells. Multi-agent systems (MAS) have been proposed as good candidates to achieve this goal.'),
(90554, 2005, 'bmc', 'ProbeMaker: an extensible framework for design of sets of oligonucleotide probes', 'Stenberg, Johan|Nilsson, Mats|Landegren, Ulf', 'Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Se-751 85, Uppsala, Sweden. johan.stenberg@genpat.uu.se|Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Se-751 85, Uppsala, Sweden. johan.stenberg@genpat.uu.se|Department of Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Se-751 85, Uppsala, Sweden. johan.stenberg@genpat.uu.se', 'Sweden|Sweden|Sweden', 0, 'Algorithms|Computer-Aided Design|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Software', 'Evaluation Studies', '10.1186/1471-2105-6-229', '16171527', 'Procedures for genetic analyses based on oligonucleotide probes are powerful tools that can allow highly parallel investigations of genetic material. Such procedures require the design of large sets of probes using application-specific design constraints.'),
(90555, 2005, 'bmc', 'Chromosomal clustering of a human transcriptome reveals regulatory background', 'Vogel, Jan H|von Heydebreck, Anja|Purmann, Antje|Sperling, Silke', 'Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. jan.vogel@gmail.com|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. jan.vogel@gmail.com|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. jan.vogel@gmail.com|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. jan.vogel@gmail.com', 'Germany|Germany|Germany|Germany', 30, 'Binding Sites|Chromosome Mapping|Gene Expression|Gene Order|Humans|Models, Biological|Multigene Family|Myocardium|Transcription Factors', 'Journal Article', '10.1186/1471-2105-6-230', '16171528', 'There has been much evidence recently for a link between transcriptional regulation and chromosomal gene order, but the relationship between genomic organization, regulation and gene function in higher eukaryotes remains to be precisely defined.'),
(90556, 2005, 'bmc', 'A linear memory algorithm for Baum-Welch training', 'Miklós, István|Meyer, Irmtraud M', 'MTA-ELTE Theoretical Biology and Ecology Group, Pázmány Péter sétány 1/c 1117 Budapest, Hungary. miklosi@ramet.elte.hu|MTA-ELTE Theoretical Biology and Ecology Group, Pázmány Péter sétány 1/c 1117 Budapest, Hungary. miklosi@ramet.elte.hu', 'Hungary|Hungary', 0, 'Algorithms|Data Interpretation, Statistical|Markov Chains|Mathematical Computing|Models, Statistical|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-6-231', '16171529', 'Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. It can be employed as long as a training set of annotated sequences is known, and provides a rigorous way to derive parameter values which are guaranteed to be at least locally optimal. For complex hidden Markov models such as pair hidden Markov models and very long training sequences, even the most efficient algorithms for Baum-Welch training are currently too memory-consuming. This has so far effectively prevented the automatic parameter training of hidden Markov models that are currently used for biological sequence analyses.'),
(90557, 2005, 'bmc', 'EXPANDER--an integrative program suite for microarray data analysis', 'Shamir, Ron|Maron-Katz, Adi|Tanay, Amos|Linhart, Chaim|Steinfeld, Israel|Sharan, Roded|Shiloh, Yosef|Elkon, Ran', 'School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. rshamir@tau.ac.il|School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. rshamir@tau.ac.il|School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. rshamir@tau.ac.il|School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. rshamir@tau.ac.il|School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. rshamir@tau.ac.il|School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. rshamir@tau.ac.il|School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. rshamir@tau.ac.il|School of Computer Science, Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. rshamir@tau.ac.il', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 0, 'Algorithms|Cluster Analysis|Data Interpretation, Statistical|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-6-232', '16176576', 'Gene expression microarrays are a prominent experimental tool in functional genomics which has opened the opportunity for gaining global, systems-level understanding of transcriptional networks. Experiments that apply this technology typically generate overwhelming volumes of data, unprecedented in biological research. Therefore the task of mining meaningful biological knowledge out of the raw data is a major challenge in bioinformatics. Of special need are integrative packages that provide biologist users with advanced but yet easy to use, set of algorithms, together covering the whole range of steps in microarray data analysis.'),
(90558, 2005, 'bmc', 'GeneRank: using search engine technology for the analysis of microarray experiments', 'Morrison, Julie L|Breitling, Rainer|Higham, Desmond J|Gilbert, David R', 'Bioinformatics Research Centre, University of Glasgow, Glasgow, UK. jmorriso@dcs.gla.ac.uk|Bioinformatics Research Centre, University of Glasgow, Glasgow, UK. jmorriso@dcs.gla.ac.uk|Bioinformatics Research Centre, University of Glasgow, Glasgow, UK. jmorriso@dcs.gla.ac.uk|Bioinformatics Research Centre, University of Glasgow, Glasgow, UK. jmorriso@dcs.gla.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Area Under Curve|Information Systems|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-6-233', '16176585', 'Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a treated sample where the treatment can be of many types from drug exposure to genetic variation. Interpretation of the results usually combines lists of differentially expressed genes with previous knowledge about their biological function. Here we evaluate a method--based on the PageRank algorithm employed by the popular search engine Google--that tries to automate some of this procedure to generate prioritized gene lists by exploiting biological background information.'),
(90559, 2005, 'bmc', 'Quality determination and the repair of poor quality spots in array experiments', 'Tom, Brian D M|Gilks, Walter R|Brooke-Powell, Elizabeth T|Ajioka, James W', 'Medical Research Council, Institute of Public Health, Robinson Way, Cambridge CB2 2SR, UK. brian.tom@mrc-bsu.cam.ac.uk|Medical Research Council, Institute of Public Health, Robinson Way, Cambridge CB2 2SR, UK. brian.tom@mrc-bsu.cam.ac.uk|Medical Research Council, Institute of Public Health, Robinson Way, Cambridge CB2 2SR, UK. brian.tom@mrc-bsu.cam.ac.uk|Medical Research Council, Institute of Public Health, Robinson Way, Cambridge CB2 2SR, UK. brian.tom@mrc-bsu.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 4, 'Algorithms|Female|HeLa Cells|Humans|Likelihood Functions|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Control|Uterine Cervical Neoplasms', 'Journal Article', '10.1186/1471-2105-6-234', '16185360', 'A common feature of microarray experiments is the occurrence of missing gene expression data. These missing values occur for a variety of reasons, in particular, because of the filtering of poor quality spots and the removal of undefined values when a logarithmic transformation is applied to negative background-corrected intensities. The efficiency and power of an analysis performed can be substantially reduced by having an incomplete matrix of gene intensities. Additionally, most statistical methods require a complete intensity matrix. Furthermore, biases may be introduced into analyses through missing information on some genes. Thus methods for appropriately replacing (imputing) missing data and/or weighting poor quality spots are required.'),
(90560, 2005, 'bmc', 'An analysis of extensible modelling for functional genomics data', 'Jones, Andrew R|Paton, Norman W', 'School of Computer Science, University of Manchester, Manchester, UK. ajones@cs.man.ac.uk|School of Computer Science, University of Manchester, Manchester, UK. ajones@cs.man.ac.uk', 'United Kingdom|United Kingdom', 0, 'Chemistry Techniques, Analytical|Computer Simulation|Data Collection|Genomics|Guidelines as Topic|Mass Spectrometry|Microarray Analysis|Models, Biological|Models, Molecular|Software|Vocabulary, Controlled', 'Evaluation Studies', '10.1186/1471-2105-6-235', '16188029', 'Several data formats have been developed for large scale biological experiments, using a variety of methodologies. Most data formats contain a mechanism for allowing extensions to encode unanticipated data types. Extensions to data formats are important because the experimental methodologies tend to be fairly diverse and rapidly evolving, which hinders the creation of formats that will be stable over time.'),
(90561, 2005, 'bmc', 'SIMPROT: using an empirically determined indel distribution in simulations of protein evolution', 'Pang, Andy|Smith, Andrew D|Nuin, Paulo A S|Tillier, Elisabeth R M', 'Ontario Cancer Institute, University Health Network, Toronto, Ontario, Canada. wcpang@mail.student.cs.uwaterloo.ca|Ontario Cancer Institute, University Health Network, Toronto, Ontario, Canada. wcpang@mail.student.cs.uwaterloo.ca|Ontario Cancer Institute, University Health Network, Toronto, Ontario, Canada. wcpang@mail.student.cs.uwaterloo.ca|Ontario Cancer Institute, University Health Network, Toronto, Ontario, Canada. wcpang@mail.student.cs.uwaterloo.ca', 'Canada|Canada|Canada|Canada', 30, 'Amino Acid Substitution|Computer Simulation|Evolution, Molecular|Models, Genetic|Models, Statistical|Monte Carlo Method|Phylogeny|Selection, Genetic|Sequence Analysis, Protein|Software|Software Design', 'Journal Article', '10.1186/1471-2105-6-236', '16188037', 'General protein evolution models help determine the baseline expectations for the evolution of sequences, and they have been extensively useful in sequence analysis and for the computer simulation of artificial sequence data sets.'),
(90562, 2005, 'bmc', 'Measuring similarities between transcription factor binding sites', 'Kielbasa, Szymon M|Gonze, Didier|Herzel, Hanspeter', 'Institute for Theoretical Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany. s.kielbasa@biologie.hu-berlin.de|Institute for Theoretical Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany. s.kielbasa@biologie.hu-berlin.de|Institute for Theoretical Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany. s.kielbasa@biologie.hu-berlin.de', 'Germany|Germany|Germany', 50, 'ARNTL Transcription Factors|Basic Helix-Loop-Helix Transcription Factors|Binding Sites|Chromosome Mapping|Circadian Rhythm|Databases, Nucleic Acid|E-Box Elements|Models, Biological|Nucleotides|Sensitivity and Specificity|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-6-237', '16191190', 'Collections of transcription factor binding profiles (Transfac, Jaspar) are essential to identify regulatory elements in DNA sequences. Subsets of highly similar profiles complicate large scale analysis of transcription factor binding sites.'),
(90563, 2005, 'bmc', 'Mathematical design of prokaryotic clone-based microarrays', 'Pieterse, Bart|Quirijns, Elisabeth J|Schuren, Frank H J|van der Werf, Mariët J', 'Wageningen Centre for Food Sciences, Diedenweg 20, 6700 AN Wageningen, The Netherlands. Bart.Pieterse@bds.nl|Wageningen Centre for Food Sciences, Diedenweg 20, 6700 AN Wageningen, The Netherlands. Bart.Pieterse@bds.nl|Wageningen Centre for Food Sciences, Diedenweg 20, 6700 AN Wageningen, The Netherlands. Bart.Pieterse@bds.nl|Wageningen Centre for Food Sciences, Diedenweg 20, 6700 AN Wageningen, The Netherlands. Bart.Pieterse@bds.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 3, 'Bacteria|Clone Cells|Gene Expression Profiling|Models, Genetic|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-6-238', '16191193', 'Clone-based microarrays, on which each spot represents a random genomic fragment, are a good alternative to open reading frame-based microarrays, especially for microorganisms for which the complete genome sequence is not available. Since the generation of a genomic DNA library is a random process, it is beforehand uncertain which genes are represented. Nevertheless, the genome coverage of such an array, which depends on different variables like the insert size and the number of clones in the library, can be predicted by mathematical approaches. When applying the classical formulas that determine the probability that a certain sequence is represented in a DNA library at the nucleotide level, massive amounts of clones would be necessary to obtain a proper coverage of the genome.'),
(90564, 2005, 'bmc', 'Optimized between-group classification: a new jackknife-based gene selection procedure for genome-wide expression data', 'Baty, Florent|Bihl, Michel P|Perrière, Guy|Culhane, Aedín C|Brutsche, Martin H', 'Pulmonary Gene Research, University Hospital Basel, CH-4031 Basel, Switzerland. florent.baty@unibas.ch|Pulmonary Gene Research, University Hospital Basel, CH-4031 Basel, Switzerland. florent.baty@unibas.ch|Pulmonary Gene Research, University Hospital Basel, CH-4031 Basel, Switzerland. florent.baty@unibas.ch|Pulmonary Gene Research, University Hospital Basel, CH-4031 Basel, Switzerland. florent.baty@unibas.ch|Pulmonary Gene Research, University Hospital Basel, CH-4031 Basel, Switzerland. florent.baty@unibas.ch', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 9, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Monte Carlo Method|Oligonucleotide Array Sequence Analysis|Phylogeny', 'Journal Article', '10.1186/1471-2105-6-239', '16191195', 'A recent publication described a supervised classification method for microarray data: Between Group Analysis (BGA). This method which is based on performing multivariate ordination of groups proved to be very efficient for both classification of samples into pre-defined groups and disease class prediction of new unknown samples. Classification and prediction with BGA are classically performed using the whole set of genes and no variable selection is required. We hypothesize that an optimized selection of highly discriminating genes might improve the prediction power of BGA.'),
(90565, 2005, 'bmc', 'Sequence variation in ligand binding sites in proteins', 'Magliery, Thomas J|Regan, Lynne', 'Department of Molecular Biophysics & Biochemistry, Yale University, PO Box 208114, New Haven, CT 06520-8114, USA. magliery@chemistry.ohio-state.edu|Department of Molecular Biophysics & Biochemistry, Yale University, PO Box 208114, New Haven, CT 06520-8114, USA. magliery@chemistry.ohio-state.edu', 'United States|United States', 58, 'Binding Sites|Conserved Sequence|Ligands|Nuclear Proteins|Peptides|Receptors, Cell Surface|Repetitive Sequences, Nucleic Acid|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-6-240', '16194281', 'The recent explosion in the availability of complete genome sequences has led to the cataloging of tens of thousands of new proteins and putative proteins. Many of these proteins can be structurally or functionally categorized from sequence conservation alone. In contrast, little attention has been given to the meaning of poorly-conserved sites in families of proteins, which are typically assumed to be of little structural or functional importance.'),
(90566, 2005, 'bmc', 'A comparison of RNA folding measures', 'Freyhult, Eva|Gardner, Paul P|Moulton, Vincent', 'The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden. eva.freyhult@lcb.uu.se|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden. eva.freyhult@lcb.uu.se|The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden. eva.freyhult@lcb.uu.se', 'Sweden|Sweden|Sweden', 0, 'Models, Molecular|Protein Folding|RNA, Untranslated|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-6-241', '16202126', 'In the last few decades there has been a great deal of discussion concerning whether or not noncoding RNA sequences (ncRNAs) fold in a more well-defined manner than random sequences. In this paper, we investigate several existing measures for how well an RNA sequence folds, and compare the behaviour of these measures over a large range of Rfam ncRNA families. Such measures can be useful in, for example, identifying novel ncRNAs, and indicating the presence of alternate RNA foldings.'),
(90567, 2005, 'bmc', 'Clustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural networks', 'Ma, Qicheng|Chirn, Gung-Wei|Cai, Richard|Szustakowski, Joseph D|Nirmala, N R', 'Biomedical Computing, Genome and Proteome Sciences, Novartis Institutes for BioMedical Research, Inc., Cambridge, MA 02139, USA. Qicheng.Ma@novartis.com|Biomedical Computing, Genome and Proteome Sciences, Novartis Institutes for BioMedical Research, Inc., Cambridge, MA 02139, USA. Qicheng.Ma@novartis.com|Biomedical Computing, Genome and Proteome Sciences, Novartis Institutes for BioMedical Research, Inc., Cambridge, MA 02139, USA. Qicheng.Ma@novartis.com|Biomedical Computing, Genome and Proteome Sciences, Novartis Institutes for BioMedical Research, Inc., Cambridge, MA 02139, USA. Qicheng.Ma@novartis.com|Biomedical Computing, Genome and Proteome Sciences, Novartis Institutes for BioMedical Research, Inc., Cambridge, MA 02139, USA. Qicheng.Ma@novartis.com', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Benchmarking|Cluster Analysis|Neural Networks (Computer)|ROC Curve|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software Validation', 'Journal Article', '10.1186/1471-2105-6-242', '16202129', 'The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of the approximately 30,000 known and predicted human coding genes are characterized and have been assigned at least one function, there remains a fair number of genes (about 12,000) for which no annotation has been made. The recent sequencing of other genomes has provided us with a huge amount of auxiliary sequence data which could help in the characterization of the human genes. Clustering these sequences into families is one of the first steps to perform comparative studies across several genomes.'),
(90568, 2005, 'bmc', 'Phylogenetic detection of conserved gene clusters in microbial genomes', 'Zheng, Yu|Anton, Brian P|Roberts, Richard J|Kasif, Simon', 'Bioinformatics Graduate Program, Boston University, Boston, MA, USA. zhengyu@alum.bu.edu|Bioinformatics Graduate Program, Boston University, Boston, MA, USA. zhengyu@alum.bu.edu|Bioinformatics Graduate Program, Boston University, Boston, MA, USA. zhengyu@alum.bu.edu|Bioinformatics Graduate Program, Boston University, Boston, MA, USA. zhengyu@alum.bu.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Bacteria|Conserved Sequence|Databases, Genetic|Models, Molecular|Models, Statistical|Multigene Family|Operon|Phylogeny', 'Journal Article', '10.1186/1471-2105-6-243', '16202130', 'Microbial genomes contain an abundance of genes with conserved proximity forming clusters on the chromosome. However, the conservation can be a result of many factors such as vertical inheritance, or functional selection. Thus, identification of conserved gene clusters that are under functional selection provides an effective channel for gene annotation, microarray screening, and pathway reconstruction. The problem of devising a robust method to identify these conserved gene clusters and to evaluate the significance of the conservation in multiple genomes has a number of implications for comparative, evolutionary and functional genomics as well as synthetic biology.'),
(90569, 2005, 'bmc', 'ASPIC: a novel method to predict the exon-intron structure of a gene that is optimally compatible to a set of transcript sequences', 'Bonizzoni, Paola|Rizzi, Raffaella|Pesole, Graziano', 'DISCo, University of Milan Bicocca, via Bicocca degli Arcimboldi, 8, Milan, 20135, Italy. bonizzoni@disco.unimib.it|DISCo, University of Milan Bicocca, via Bicocca degli Arcimboldi, 8, Milan, 20135, Italy. bonizzoni@disco.unimib.it|DISCo, University of Milan Bicocca, via Bicocca degli Arcimboldi, 8, Milan, 20135, Italy. bonizzoni@disco.unimib.it', 'Italy|Italy|Italy', 0, 'Algorithms|Animals|Benchmarking|Computers, Molecular|Exons|Gene Expression Profiling|Humans|Introns|Models, Molecular|Sequence Alignment|Software Design|Software Validation', 'Journal Article', '10.1186/1471-2105-6-244', '16207377', 'Currently available methods to predict splice sites are mainly based on the independent and progressive alignment of transcript data (mostly ESTs) to the genomic sequence. Apart from often being computationally expensive, this approach is vulnerable to several problems--hence the need to develop novel strategies.'),
(90570, 2005, 'bmc', 'Extension of Lander-Waterman theory for sequencing filtered DNA libraries', 'Wendl, Michael C|Barbazuk, W Brad', 'Genome Sequencing Center, Washington University, St. Louis, MO 63108, USA. mwendl@wustl.edu|Genome Sequencing Center, Washington University, St. Louis, MO 63108, USA. mwendl@wustl.edu', 'United States|United States', 0, 'Chromosome Mapping|Contig Mapping|Gene Library|Models, Genetic|Sequence Analysis, DNA|Sequence Tagged Sites', 'Journal Article', '10.1186/1471-2105-6-245', '16216129', 'The degree to which conventional DNA sequencing techniques will be successful for highly repetitive genomes is unclear. Investigators are therefore considering various filtering methods to select against high-copy sequence in DNA clone libraries. The standard model for random sequencing, Lander-Waterman theory, does not account for two important issues in such libraries, discontinuities and position-based sampling biases (the so-called edge effect). We report an extension of the theory for analyzing such configurations.'),
(90571, 2005, 'bmc', 'BioSysBio: Bioinformatics and Systems Biology Conference Edinburgh, UK 14-15 July 2005 Abstracts', '-', '-', '-', 0, 'Computational Biology|Systems Biology', 'Congress', '10.1186/1471-2105-6-245', '16219110', '-'),
(90572, 2005, 'bmc', 'TIMS: TaqMan Information Management System, tools to organize data flow in a genotyping laboratory', 'Monnier, Stéphanie|Cox, David G|Albion, Tim|Canzian, Federico', 'International Agency for Research on Cancer, F-69372, Lyon, France. monnier@iarc.fr|International Agency for Research on Cancer, F-69372, Lyon, France. monnier@iarc.fr|International Agency for Research on Cancer, F-69372, Lyon, France. monnier@iarc.fr|International Agency for Research on Cancer, F-69372, Lyon, France. monnier@iarc.fr', 'France|France|France|France', 0, 'Clinical Laboratory Information Systems|Genotype|Information Management|Information Storage and Retrieval|Polymorphism, Single Nucleotide|Programming Languages|Software|Statistics as Topic|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-246', '16221298', 'Single Nucleotide Polymorphism (SNP) genotyping is a major activity in biomedical research. The Taqman technology is one of the most commonly used approaches. It produces large amounts of data that are difficult to process by hand. Laboratories not equipped with a Laboratory Information Management System (LIMS) need tools to organize the data flow.'),
(90573, 2005, 'bmc', 'Phydbac Gene Function Predictor: a gene annotation tool based on genomic context analysis', 'Enault, François|Suhre, Karsten|Claverie, Jean-Michel', 'Structural and Genomic Information, CNRS-UPR 2589, 31 chemin Joseph Aiguier, 13009 Marseille, France. enault@igs.cnrs-mrs.fr|Structural and Genomic Information, CNRS-UPR 2589, 31 chemin Joseph Aiguier, 13009 Marseille, France. enault@igs.cnrs-mrs.fr|Structural and Genomic Information, CNRS-UPR 2589, 31 chemin Joseph Aiguier, 13009 Marseille, France. enault@igs.cnrs-mrs.fr', 'France|France|France', 46, 'Algorithms|Benchmarking|Chromosome Mapping|Databases, Protein|Escherichia coli K12|Escherichia coli Proteins|Gene Fusion|Internet|Models, Genetic|Multigene Family|Phylogeny|Sequence Alignment|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1186/1471-2105-6-247', '16221304', 'The large amount of completely sequenced genomes allows genomic context analysis to predict reliable functional associations between prokaryotic proteins. Major methods rely on the fact that genes encoding physically interacting partners or members of shared metabolic pathways tend to be proximate on the genome, to evolve in a correlated manner and to be fused as a single sequence in another organism.'),
(90574, 2005, 'bmc', 'Better prediction of protein contact number using a support vector regression analysis of amino acid sequence', 'Yuan, Zheng', 'Institute for Molecular Bioscience, ARC Centre in Bioinformatics, The University of Queensland, St. Lucia, 4072, Australia. z.yuan@imb.uq.edu.au', 'Australia', 49, 'Algorithms|Amino Acid Sequence|Models, Molecular|Models, Statistical|Predictive Value of Tests|Protein Folding|Proteins|Regression Analysis|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-6-248', '16221309', 'Protein tertiary structure can be partly characterized via each amino acids contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of Cbeta atoms in other residues within a sphere around the Cbeta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residues contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90575, 2005, 'bmc', 'SPdb--a signal peptide database', 'Choo, Khar Heng|Tan, Tin Wee|Ranganathan, Shoba', 'Department of Biochemistry, National University of Singapore, Singapore. justin@bic.nus.edu.sg|Department of Biochemistry, National University of Singapore, Singapore. justin@bic.nus.edu.sg|Department of Biochemistry, National University of Singapore, Singapore. justin@bic.nus.edu.sg', 'Singapore|Singapore|Singapore', 0, 'Databases, Nucleic Acid|Internet|Peptides|Protein Sorting Signals|Protein Transport|Sequence Analysis, Protein|Systems Integration|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-6-249', '16221310', 'The signal peptide plays an important role in protein targeting and protein translocation in both prokaryotic and eukaryotic cells. This transient, short peptide sequence functions like a postal address on an envelope by targeting proteins for secretion or for transfer to specific organelles for further processing. Understanding how signal peptides function is crucial in predicting where proteins are translocated. To support this understanding, we present SPdb signal peptide database http://proline.bic.nus.edu.sg/spdb, a repository of experimentally determined and computationally predicted signal peptides.'),
(90576, 2005, 'bmc', 'MASQOT: a method for cDNA microarray spot quality control', 'Bylesjö, Max|Eriksson, Daniel|Sjödin, Andreas|Sjöström, Michael|Jansson, Stefan|Antti, Henrik|Trygg, Johan', 'Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden. max.bylesjo@chem.umu.se|Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden. max.bylesjo@chem.umu.se|Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden. max.bylesjo@chem.umu.se|Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden. max.bylesjo@chem.umu.se|Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden. max.bylesjo@chem.umu.se|Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden. max.bylesjo@chem.umu.se|Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden. max.bylesjo@chem.umu.se', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 16, 'Data Interpretation, Statistical|Discriminant Analysis|Electronic Data Processing|Microarray Analysis|Multivariate Analysis|Oligonucleotide Array Sequence Analysis|Quality Control|ROC Curve|Software', 'Journal Article', '10.1186/1471-2105-6-250', '16223442', 'cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more.'),
(90577, 2005, 'bmc', 'Differentiation of regions with atypical oligonucleotide composition in bacterial genomes', 'Reva, Oleg N|Tümmler, Burkhard', 'Klinische Forschergruppe, OE6711, Medizinische Hochschule Hannover, Carl-Neuberg-Strasse 1, D-30625 Hannover, Germany. reva@serv.imv.kiev.ua|Klinische Forschergruppe, OE6711, Medizinische Hochschule Hannover, Carl-Neuberg-Strasse 1, D-30625 Hannover, Germany. reva@serv.imv.kiev.ua', 'Germany|Germany', 39, 'DNA, Bacterial|Data Interpretation, Statistical|Gene Expression Profiling|Genome, Bacterial|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Regulatory Sequences, Nucleic Acid|Terminology as Topic', 'Journal Article', '10.1186/1471-2105-6-251', '16225667', 'Complete sequencing of bacterial genomes has become a common technique of present day microbiology. Thereafter, data mining in the complete sequence is an essential step. New in silico methods are needed that rapidly identify the major features of genome organization and facilitate the prediction of the functional class of ORFs. We tested the usefulness of local oligonucleotide usage (OU) patterns to recognize and differentiate types of atypical oligonucleotide composition in DNA sequences of bacterial genomes.'),
(90578, 2005, 'bmc', 'CoaSim: a flexible environment for simulating genetic data under coalescent models', 'Mailund, Thomas|Schierup, Mikkel H|Pedersen, Christian N S|Mechlenborg, Peter J M|Madsen, Jesper N|Schauser, Leif', 'Bioinformatics Research Center, University of Aarhus, Høegh Guldbergsgade 10, 8000 Arhus C, Denmark. mailund@birc.au.dk|Bioinformatics Research Center, University of Aarhus, Høegh Guldbergsgade 10, 8000 Arhus C, Denmark. mailund@birc.au.dk|Bioinformatics Research Center, University of Aarhus, Høegh Guldbergsgade 10, 8000 Arhus C, Denmark. mailund@birc.au.dk|Bioinformatics Research Center, University of Aarhus, Høegh Guldbergsgade 10, 8000 Arhus C, Denmark. mailund@birc.au.dk|Bioinformatics Research Center, University of Aarhus, Høegh Guldbergsgade 10, 8000 Arhus C, Denmark. mailund@birc.au.dk|Bioinformatics Research Center, University of Aarhus, Høegh Guldbergsgade 10, 8000 Arhus C, Denmark. mailund@birc.au.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 50, 'Case-Control Studies|Computer Simulation|Data Interpretation, Statistical|Disease Susceptibility|Genetic Markers|Genetic Predisposition to Disease|Humans|Models, Genetic|Monte Carlo Method|Polymorphism, Genetic|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1186/1471-2105-6-252', '16225674', 'Coalescent simulations are playing a large role in interpreting large scale intra-specific sequence or polymorphism surveys and for planning and evaluating association studies. Coalescent simulations of data sets under different models can be compared to the actual data to test the importance of different evolutionary factors and thus get insight into these.'),
(90579, 2005, 'bmc', 'ProfNet, a method to derive profile-profile alignment scoring functions that improves the alignments of distantly related proteins', 'Ohlson, Tomas|Elofsson, Arne', 'Stockholm Blolnformatlcs Center, Stockholm University, SE-106 91 Stockholm, Sweden. tomasoh@sbc.su.se|Stockholm Blolnformatlcs Center, Stockholm University, SE-106 91 Stockholm, Sweden. tomasoh@sbc.su.se', 'Sweden|Sweden', 17, 'Models, Genetic|Neural Networks (Computer)|Proteins|ROC Curve|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-6-253', '16225676', 'Profile-profile methods have been used for some years now to detect and align homologous proteins. The best such methods use information from the background distribution of amino acids and substitution tables either when constructing the profiles or in the scoring. This makes the methods dependent on the quality and choice of substitution table as well as the construction of the profiles. Here, we introduce a novel method called ProfNet that is used to derive a profile-profile scoring function. The method optimizes the discrimination between scores of related and unrelated residues and it is fast and straightforward to use. This new method derives a scoring function that is mainly dependent on the actual alignment of residues from a training set, and it does not use any additional information about the background distribution.'),
(90580, 2005, 'bmc', 'Prediction of beta-barrel membrane proteins by searching for restricted domains', 'Mirus, Oliver|Schleiff, Enrico', 'Botanisches Institut der Ludwig-Maximilians-Universität München, Menzinger Str. 67, 80638 München, Germany. mirus@lrz.uni-muenchen.de|Botanisches Institut der Ludwig-Maximilians-Universität München, Menzinger Str. 67, 80638 München, Germany. mirus@lrz.uni-muenchen.de', 'Germany|Germany', 15, 'Algorithms|Bacterial Outer Membrane Proteins|Escherichia coli|False Negative Reactions|False Positive Reactions|Linear Models|Locus Control Region|Mitochondrial Membrane Transport Proteins|Proteome|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-6-254', '16225682', 'The identification of beta-barrel membrane proteins out of a genomic/proteomic background is one of the rapidly developing fields in bioinformatics. Our main goal is the prediction of such proteins in genome/proteome wide analyses.'),
(90581, 2005, 'bmc', 'The modeled structure of the RNA dependent RNA polymerase of GBV-C virus suggests a role for motif E in Flaviviridae RNA polymerases', 'Ferron, François|Bussetta, Cécile|Dutartre, Hélène|Canard, Bruno', 'Architecture et Fonction des Macromolécules Biologiques, UMR 6098 CNRS, Université Aix-Marseille I et II, ESIL, Campus de Luminy, 13288 Marseille Cedex 09, France. Ferron@bbri.org|Architecture et Fonction des Macromolécules Biologiques, UMR 6098 CNRS, Université Aix-Marseille I et II, ESIL, Campus de Luminy, 13288 Marseille Cedex 09, France. Ferron@bbri.org|Architecture et Fonction des Macromolécules Biologiques, UMR 6098 CNRS, Université Aix-Marseille I et II, ESIL, Campus de Luminy, 13288 Marseille Cedex 09, France. Ferron@bbri.org|Architecture et Fonction des Macromolécules Biologiques, UMR 6098 CNRS, Université Aix-Marseille I et II, ESIL, Campus de Luminy, 13288 Marseille Cedex 09, France. Ferron@bbri.org', 'France|France|France|France', 26, 'Binding Sites|GB virus C|Models, Biological|Models, Chemical|Phylogeny|Protein Structure, Secondary|RNA Replicase|Sequence Alignment|Sequence Analysis|Sequence Homology', 'Journal Article', '10.1186/1471-2105-6-255', '16225688', 'The Flaviviridae virus family includes major human and animal pathogens. The RNA dependent RNA polymerase (RdRp) plays a central role in the replication process, and thus is a validated target for antiviral drugs. Despite the increasing structural and enzymatic characterization of viral RdRps, detailed molecular replication mechanisms remain unclear. The hepatitis C virus (HCV) is a major human pathogen difficult to study in cultured cells. The bovine viral diarrhea virus (BVDV) is often used as a surrogate model to screen antiviral drugs against HCV. The structure of BVDV RdRp has been recently published. It presents several differences relative to HCV RdRp. These differences raise questions about the relevance of BVDV as a surrogate model, and cast novel interest on the GB virus C (GBV-C). Indeed, GBV-C is genetically closer to HCV than BVDV, and can lead to productive infection of cultured cells. There is no structural data for the GBV-C RdRp yet.'),
(90582, 2005, 'bmc', 'Evaluating eukaryotic secreted protein prediction', 'Klee, Eric W|Ellis, Lynda B M', 'Department of Laboratory Medicine and Pathology, University of Minnesota, Mayo Mail Code 609, Minneapolis, MN 55455, USA. klee0025@tc.umn.edu|Department of Laboratory Medicine and Pathology, University of Minnesota, Mayo Mail Code 609, Minneapolis, MN 55455, USA. klee0025@tc.umn.edu', 'United States|United States', 59, 'Animals|Humans|Models, Statistical|Neural Networks (Computer)|Predictive Value of Tests|Sensitivity and Specificity|Sequence Analysis, Protein|Software|Software Design|Terminology as Topic', 'Evaluation Studies', '10.1186/1471-2105-6-256', '16225690', 'Improvements in protein sequence annotation and an increase in the number of annotated protein databases has fueled development of an increasing number of software tools to predict secreted proteins. Six software programs capable of high throughput and employing a wide range of prediction methods, SignalP 3.0, SignalP 2.0, TargetP 1.01, PrediSi, Phobius, and ProtComp 6.0, are evaluated.'),
(90583, 2005, 'bmc', 'Statistical distributions of optimal global alignment scores of random protein sequences', 'Pang, Hongxia|Tang, Jiaowei|Chen, Su-Shing|Tao, Shiheng', 'School of Life Science, Northwest A&F University, Yangling, Shaanxi, China. hongxiapang@yahoo.com|School of Life Science, Northwest A&F University, Yangling, Shaanxi, China. hongxiapang@yahoo.com|School of Life Science, Northwest A&F University, Yangling, Shaanxi, China. hongxiapang@yahoo.com|School of Life Science, Northwest A&F University, Yangling, Shaanxi, China. hongxiapang@yahoo.com', 'China|China|China|China', 15, 'Algorithms|Computational Biology|Models, Statistical|Sequence Alignment|Sequence Homology', 'Journal Article', '10.1186/1471-2105-6-257', '16225696', 'The inference of homology from statistically significant sequence similarity is a central issue in sequence alignments. So far the statistical distribution function underlying the optimal global alignments has not been completely determined.'),
(90584, 2005, 'bmc', 'Dynamic modeling of cis-regulatory circuits and gene expression prediction via cross-gene identification', 'Lin, Li-Hsieh|Lee, Hsiao-Ching|Li, Wen-Hsiung|Chen, Bor-Sen', 'Lab. of System Biology, National Tsing Hua University, Hsinchu, 300, Taiwan. LHlin@moti.ee.nthu.edu.tw|Lab. of System Biology, National Tsing Hua University, Hsinchu, 300, Taiwan. LHlin@moti.ee.nthu.edu.tw|Lab. of System Biology, National Tsing Hua University, Hsinchu, 300, Taiwan. LHlin@moti.ee.nthu.edu.tw|Lab. of System Biology, National Tsing Hua University, Hsinchu, 300, Taiwan. LHlin@moti.ee.nthu.edu.tw', '-|-|-|-', 20, 'Cell Cycle|Cyclin B|Gene Expression Profiling|Lipoproteins|Models, Genetic|Multigene Family|Pheromones|Regulatory Elements, Transcriptional|Saccharomyces cerevisiae Proteins|Transcription Factors|Yeasts', 'Journal Article', '10.1186/1471-2105-6-258', '16232312', 'Gene expression programs depend on recognition of cis elements in promoter region of target genes by transcription factors (TFs), but how TFs regulate gene expression via recognition of cis elements is still not clear. To study this issue, we define the cis-regulatory circuit of a gene as a system that consists of its cis elements and the interactions among their recognizing TFs and develop a dynamic model to study the functional architecture and dynamics of the circuit. This is in contrast to traditional approaches where a cis-regulatory circuit is constructed by a mutagenesis or motif-deletion scheme. We estimate the regulatory functions of cis-regulatory circuits using microarray data.'),
(90585, 2005, 'bmc', 'Human promoter genomic composition demonstrates non-random groupings that reflect general cellular function', 'McNutt, Markey C|Tongbai, Ron|Cui, Wenwu|Collins, Irene|Freebern, Wendy J|Montano, Idalia|Haggerty, Cynthia M|Chandramouli, Gvr|Gardner, Kevin', 'The Advanced Technology Center, Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, Bethesda, Maryland 20892-4605, USA. markey.mcnutt@utsouthwestern.edu|The Advanced Technology Center, Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, Bethesda, Maryland 20892-4605, USA. markey.mcnutt@utsouthwestern.edu|The Advanced Technology Center, Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, Bethesda, Maryland 20892-4605, USA. markey.mcnutt@utsouthwestern.edu|The Advanced Technology Center, Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, Bethesda, Maryland 20892-4605, USA. markey.mcnutt@utsouthwestern.edu|The Advanced Technology Center, Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, Bethesda, Maryland 20892-4605, USA. markey.mcnutt@utsouthwestern.edu|The Advanced Technology Center, Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, Bethesda, Maryland 20892-4605, USA. markey.mcnutt@utsouthwestern.edu|The Advanced Technology Center, Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, Bethesda, Maryland 20892-4605, USA. markey.mcnutt@utsouthwestern.edu|The Advanced Technology Center, Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, Bethesda, Maryland 20892-4605, USA. markey.mcnutt@utsouthwestern.edu|The Advanced Technology Center, Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, Bethesda, Maryland 20892-4605, USA. markey.mcnutt@utsouthwestern.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 4, 'Binding Sites|Cell Physiological Phenomena|Gene Expression|Humans|Promoter Regions, Genetic|Terminology as Topic|Transcription Factors', 'Journal Article', '10.1186/1471-2105-6-259', '16232321', 'The purpose of this study is to determine whether or not there exists nonrandom grouping of cis-regulatory elements within gene promoters that can be perceived independent of gene expression data and whether or not there is any correlation between this grouping and the biological function of the gene.'),
(90586, 2005, 'bmc', 'SpectralNET--an application for spectral graph analysis and visualization', 'Forman, Joshua J|Clemons, Paul A|Schreiber, Stuart L|Haggarty, Stephen J', 'The Broad Institute of MIT & Harvard University, Cambridge, MA 02141, USA. jforman@broad.harvard.edu|The Broad Institute of MIT & Harvard University, Cambridge, MA 02141, USA. jforman@broad.harvard.edu|The Broad Institute of MIT & Harvard University, Cambridge, MA 02141, USA. jforman@broad.harvard.edu|The Broad Institute of MIT & Harvard University, Cambridge, MA 02141, USA. jforman@broad.harvard.edu', 'United States|United States|United States|United States', 25, 'Algorithms|Computational Biology|Data Display|Mathematical Computing|Software', 'Journal Article', '10.1186/1471-2105-6-260', '16236170', 'Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks.'),
(90587, 2005, 'bmc', 'A method of precise mRNA/DNA homology-based gene structure prediction', 'Churbanov, Alexander|Pauley, Mark|Quest, Daniel|Ali, Hesham', 'Department of Computer Science, College of Information Science and Technology, University of Nebraska, Omaha, NE 68182-0116, USA. achurbanov@mail.unomaha.edu|Department of Computer Science, College of Information Science and Technology, University of Nebraska, Omaha, NE 68182-0116, USA. achurbanov@mail.unomaha.edu|Department of Computer Science, College of Information Science and Technology, University of Nebraska, Omaha, NE 68182-0116, USA. achurbanov@mail.unomaha.edu|Department of Computer Science, College of Information Science and Technology, University of Nebraska, Omaha, NE 68182-0116, USA. achurbanov@mail.unomaha.edu', 'United States|United States|United States|United States', 6, 'Algorithms|Clone Cells|DNA|Predictive Value of Tests|RNA, Messenger|Sequence Alignment|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-6-261', '16242044', 'Accurate and automatic gene finding and structural prediction is a common problem in bioinformatics, and applications need to be capable of handling non-canonical splice sites, micro-exons and partial gene structure predictions that span across several genomic clones.'),
(90588, 2005, 'bmc', 'Using hexamers to predict cis-regulatory motifs in Drosophila', 'Chan, Bob Y|Kibler, Dennis', 'School of Information and Computer Science, University of California, Irvine, California, USA. bobc@ics.uci.edu|School of Information and Computer Science, University of California, Irvine, California, USA. bobc@ics.uci.edu', 'United States|United States', 34, 'Algorithms|Amino Acid Motifs|Animals|Drosophila|Gene Expression Regulation|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-6-262', '16253142', 'Cis-regulatory modules (CRMs) are short stretches of DNA that help regulate gene expression in higher eukaryotes. They have been found up to 1 megabase away from the genes they regulate and can be located upstream, downstream, and even within their target genes. Due to the difficulty of finding CRMs using biological and computational techniques, even well-studied regulatory systems may contain CRMs that have not yet been discovered.'),
(90589, 2005, 'bmc', 'Selecting additional tag SNPs for tolerating missing data in genotyping', 'Huang, Yao-Ting|Zhang, Kui|Chen, Ting|Chao, Kun-Mao', 'Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan. ythuang@acb.csie.ntu.edu.tw|Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan. ythuang@acb.csie.ntu.edu.tw|Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan. ythuang@acb.csie.ntu.edu.tw|Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan. ythuang@acb.csie.ntu.edu.tw', '-|-|-|-', 16, 'Algorithms|Chromosome Mapping|Computational Biology|Computer Simulation|DNA Mutational Analysis|Data Interpretation, Statistical|Databases, Genetic|Gene Frequency|Genetic Markers|Genetic Predisposition to Disease|Genome, Human|Genotype|Haplotypes|Humans|Models, Genetic|Polymorphism, Single Nucleotide|Research Design|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-6-263', '16259642', 'Recent studies have shown that the patterns of linkage disequilibrium observed in human populations have a block-like structure, and a small subset of SNPs (called tag SNPs) is sufficient to distinguish each pair of haplotype patterns in the block. In reality, some tag SNPs may be missing, and we may fail to distinguish two distinct haplotypes due to the ambiguity caused by missing data.'),
(90590, 2005, 'bmc', 'maxdLoad2 and maxdBrowse: standards-compliant tools for microarray experimental annotation, data management and dissemination', 'Hancock, David|Wilson, Michael|Velarde, Giles|Morrison, Norman|Hayes, Andrew|Hulme, Helen|Wood, A Joseph|Nashar, Karim|Kell, Douglas B|Brass, Andy', 'School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk|School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk|School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk|School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk|School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk|School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk|School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk|School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk|School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk|School of Computer Science, The University of Manchester, Kilburn Building, Oxford Road, Manchester, UK. d.hancock@cs.man.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Data Interpretation, Statistical|Information Dissemination|Internet|Microarray Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-264', '16269077', 'maxdLoad2 is a relational database schema and Java application for microarray experimental annotation and storage. It is compliant with all standards for microarray meta-data capture, including the specification of what data should be recorded, extensive use of standard ontologies and support for data exchange formats. The output from maxdLoad2 is of a form acceptable for submission to the ArrayExpress microarray repository at the European Bioinformatics Institute. maxdBrowse is a PHP web-application that makes contents of maxdLoad2 databases accessible via web-browser, the command-line and web-service environments. It thus acts as both a dissemination and data-mining tool.'),
(90591, 2005, 'bmc', 'Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes', 'Warnat, Patrick|Eils, Roland|Brors, Benedikt', 'Department of Theoretical Bioinformatics, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. p.warnat@dkfz.de|Department of Theoretical Bioinformatics, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. p.warnat@dkfz.de|Department of Theoretical Bioinformatics, German Cancer Research Center, Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany. p.warnat@dkfz.de', 'Germany|Germany|Germany', 0, 'Animals|Breast Neoplasms|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Leukemia, Myeloid|Male|Oligonucleotide Array Sequence Analysis|Phenotype|Prostatic Neoplasms', 'Journal Article', '10.1186/1471-2105-6-265', '16271137', 'The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods.'),
(90592, 2005, 'bmc', 'Alternative splicing and protein function', 'Neverov, A D|Artamonova, I I|Nurtdinov, R N|Frishman, D|Gelfand, M S|Mironov, A A', 'State Scientific Center GosNIIGenetika, 1st Dorozhny proezd 1, Moscow, 117545, Russia. neva_2000@mail.ru|State Scientific Center GosNIIGenetika, 1st Dorozhny proezd 1, Moscow, 117545, Russia. neva_2000@mail.ru|State Scientific Center GosNIIGenetika, 1st Dorozhny proezd 1, Moscow, 117545, Russia. neva_2000@mail.ru|State Scientific Center GosNIIGenetika, 1st Dorozhny proezd 1, Moscow, 117545, Russia. neva_2000@mail.ru|State Scientific Center GosNIIGenetika, 1st Dorozhny proezd 1, Moscow, 117545, Russia. neva_2000@mail.ru|State Scientific Center GosNIIGenetika, 1st Dorozhny proezd 1, Moscow, 117545, Russia. neva_2000@mail.ru', '-|-|-|-|-|-', 34, 'Algorithms|Alternative Splicing|Chromosome Mapping|Codon, Initiator|Computers, Molecular|Humans|Protein Biosynthesis|Protein Isoforms|RNA, Messenger|Software', 'Journal Article', '10.1186/1471-2105-6-266', '16274476', 'Alternative splicing is a major mechanism of generating protein diversity in higher eukaryotes. Although at least half, and probably more, of mammalian genes are alternatively spliced, it was not clear, whether the frequency of alternative splicing is the same in different functional categories. The problem is obscured by uneven coverage of genes by ESTs and a large number of artifacts in the EST data.'),
(90593, 2005, 'bmc', 'Identification of clustered microRNAs using an ab initio prediction method', 'Sewer, Alain|Paul, Nicodème|Landgraf, Pablo|Aravin, Alexei|Pfeffer, Sébastien|Brownstein, Michael J|Tuschl, Thomas|van Nimwegen, Erik|Zavolan, Mihaela', 'Biozentrum, Universität Basel, Basel, Switzerland. alain.sewer@unibas.ch|Biozentrum, Universität Basel, Basel, Switzerland. alain.sewer@unibas.ch|Biozentrum, Universität Basel, Basel, Switzerland. alain.sewer@unibas.ch|Biozentrum, Universität Basel, Basel, Switzerland. alain.sewer@unibas.ch|Biozentrum, Universität Basel, Basel, Switzerland. alain.sewer@unibas.ch|Biozentrum, Universität Basel, Basel, Switzerland. alain.sewer@unibas.ch|Biozentrum, Universität Basel, Basel, Switzerland. alain.sewer@unibas.ch|Biozentrum, Universität Basel, Basel, Switzerland. alain.sewer@unibas.ch|Biozentrum, Universität Basel, Basel, Switzerland. alain.sewer@unibas.ch', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 192, 'Algorithms|Animals|Chromosome Mapping|Cluster Analysis|Computational Biology|Genome|Humans|Internet|Mice|MicroRNAs|Models, Genetic|Multigene Family|Nucleic Acid Conformation|RNA|Rats|Sensitivity and Specificity|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-6-267', '16274478', 'MicroRNAs (miRNAs) are endogenous 21 to 23-nucleotide RNA molecules that regulate protein-coding gene expression in plants and animals via the RNA interference pathway. Hundreds of them have been identified in the last five years and very recent works indicate that their total number is still larger. Therefore miRNAs gene discovery remains an important aspect of understanding this new and still widely unknown regulation mechanism. Bioinformatics approaches have proved to be very useful toward this goal by guiding the experimental investigations.'),
(90594, 2005, 'bmc', 'MiMiR: a comprehensive solution for storage, annotation and exchange of microarray data', 'Navarange, Mahendra|Game, Laurence|Fowler, Derek|Wadekar, Vihar|Banks, Helen|Cooley, Nicola|Rahman, Fatimah|Hinshelwood, Justin|Broderick, Peter|Causton, Helen C', 'CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com|CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com|CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com|CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com|CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com|CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com|CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com|CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com|CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com|CSC-IC Microarray Centre, Imperial College, Hammersmith Campus, London W12 ONN, UK. mahendra.navarange@atosorigin.com', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 14, 'Data Collection|Data Display|Data Interpretation, Statistical|Databases, Genetic|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-268', '16280078', 'The generation of large amounts of microarray data presents challenges for data collection, annotation, exchange and analysis. Although there are now widely accepted formats, minimum standards for data content and ontologies for microarray data, only a few groups are using them together to build and populate large-scale databases. Structured environments for data management are crucial for making full use of these data.'),
(90595, 2005, 'bmc', 'ErmineJ: tool for functional analysis of gene expression data sets', 'Lee, Homin K|Braynen, William|Keshav, Kiran|Pavlidis, Paul', 'Columbia Genome Center, Columbia University, New York, NY 10032, USA. hkl7@columbia.edu|Columbia Genome Center, Columbia University, New York, NY 10032, USA. hkl7@columbia.edu|Columbia Genome Center, Columbia University, New York, NY 10032, USA. hkl7@columbia.edu|Columbia Genome Center, Columbia University, New York, NY 10032, USA. hkl7@columbia.edu', 'United States|United States|United States|United States', 195, 'Animals|Humans|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-269', '16280084', 'It is common for the results of a microarray study to be analyzed in the context of biologically-motivated groups of genes such as pathways or Gene Ontology categories. The most common method for such analysis uses the hypergeometric distribution (or a related technique) to look for over-representation of groups among genes selected as being differentially expressed or otherwise of interest based on a gene-by-gene analysis. However, this method suffers from some limitations, and biologist-friendly tools that implement alternatives have not been reported.'),
(90596, 2005, 'bmc', 'Commensurate distances and similar motifs in genetic congruence and protein interaction networks in yeast', 'Ye, Ping|Peyser, Brian D|Spencer, Forrest A|Bader, Joel S', 'The Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA. pye@jhu.edu|The Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA. pye@jhu.edu|The Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA. pye@jhu.edu|The Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA. pye@jhu.edu', 'United States|United States|United States|United States', 18, 'Protein Interaction Mapping|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-6-270', '16283923', 'In a genetic interaction, the phenotype of a double mutant differs from the combined phenotypes of the underlying single mutants. When the single mutants have no growth defect, but the double mutant is lethal or exhibits slow growth, the interaction is termed synthetic lethality or synthetic fitness. These genetic interactions reveal gene redundancy and compensating pathways. Recently available large-scale data sets of genetic interactions and protein interactions in Saccharomyces cerevisiae provide a unique opportunity to elucidate the topological structure of biological pathways and how genes function in these pathways.'),
(90597, 2005, 'bmc', 'The yeast kinome displays scale free topology with functional hub clusters', 'Lee, Robin E C|Megeney, Lynn A', 'Ottawa Health Research Institute, Molecular Medicine Program, Ottawa, Canada. rolee@ohri.ca|Ottawa Health Research Institute, Molecular Medicine Program, Ottawa, Canada. rolee@ohri.ca', 'Canada|Canada', 8, 'Multigene Family|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-6-271', '16283924', 'The availability of interaction databases provides an opportunity for researchers to utilize immense amounts of data exclusively in silico. Recently there has been an emphasis on studying the global properties of biological interactions using network analysis. While this type of analysis offers a wide variety of global insights it has surprisingly not been used to examine more localized interactions based on mechanism. In as such we have particular interest in the role of key topological components in signal transduction cascades as they are vital regulators of healthy and diseased cell states.'),
(90598, 2005, 'bmc', 'Automated methods of predicting the function of biological sequences using GO and BLAST', 'Jones, Craig E|Baumann, Ute|Brown, Alfred L', 'Australian Centre for Plant Functional Genomics, University of Adelaide, South Australia, 5064, Australia. craig@cs.adelaide.edu.au|Australian Centre for Plant Functional Genomics, University of Adelaide, South Australia, 5064, Australia. craig@cs.adelaide.edu.au|Australian Centre for Plant Functional Genomics, University of Adelaide, South Australia, 5064, Australia. craig@cs.adelaide.edu.au', 'Australia|Australia|Australia', 37, 'Benchmarking|Chi-Square Distribution|Data Collection|Databases, Genetic|Discriminant Analysis|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis|Software', 'Comparative Study', '10.1186/1471-2105-6-272', '16288652', 'With the exponential increase in genomic sequence data there is a need to develop automated approaches to deducing the biological functions of novel sequences with high accuracy. Our aim is to demonstrate how accuracy benchmarking can be used in a decision-making process evaluating competing designs of biological function predictors. We utilise the Gene Ontology, GO, a directed acyclic graph of functional terms, to annotate sequences with functional information describing their biological context. Initially we examine the effect on accuracy scores of increasing the allowed distance between predicted and a test set of curator assigned terms. Next we evaluate several annotator methods using accuracy benchmarking. Given an unannotated sequence we use the Basic Local Alignment Search Tool, BLAST, to find similar sequences that have already been assigned GO terms by curators. A number of methods were developed that utilise terms associated with the best five matching sequences. These methods were compared against a benchmark method of simply using terms associated with the best BLAST-matched sequence (best BLAST approach).'),
(90599, 2005, 'bmc', 'Ancestral sequence alignment under optimal conditions', 'Hudek, Alexander K|Brown, Daniel G', 'School of Computer Science, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada. akhudek@cs.uwaterloo.ca|School of Computer Science, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada. akhudek@cs.uwaterloo.ca', 'Canada|Canada', 11, 'Data Interpretation, Statistical|Evolution, Molecular|Likelihood Functions|Models, Molecular|Phylogeny|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-6-273', '16293191', 'Multiple genome alignment is an important problem in bioinformatics. An important subproblem used by many multiple alignment approaches is that of aligning two multiple alignments. Many popular alignment algorithms for DNA use the sum-of-pairs heuristic, where the score of a multiple alignment is the sum of its induced pairwise alignment scores. However, the biological meaning of the sum-of-pairs of pairs heuristic is not obvious. Additionally, many algorithms based on the sum-of-pairs heuristic are complicated and slow, compared to pairwise alignment algorithms. An alternative approach to aligning alignments is to first infer ancestral sequences for each alignment, and then align the two ancestral sequences. In addition to being fast, this method has a clear biological basis that takes into account the evolution implied by an underlying phylogenetic tree. In this study we explore the accuracy of aligning alignments by ancestral sequence alignment. We examine the use of both maximum likelihood and parsimony to infer ancestral sequences. Additionally, we investigate the effect on accuracy of allowing ambiguity in our ancestral sequences.'),
(90600, 2005, 'bmc', 'A stepwise framework for the normalization of array CGH data', 'Khojasteh, Mehrnoush|Lam, Wan L|Ward, Rabab K|MacAulay, Calum', 'British Columbia Cancer Research Centre, Vancouver, BC, Canada. mkhojast@bccrc.ca|British Columbia Cancer Research Centre, Vancouver, BC, Canada. mkhojast@bccrc.ca|British Columbia Cancer Research Centre, Vancouver, BC, Canada. mkhojast@bccrc.ca|British Columbia Cancer Research Centre, Vancouver, BC, Canada. mkhojast@bccrc.ca', 'Canada|Canada|Canada|Canada', 76, 'Calibration|DNA, Neoplasm|Female|Genetic Variation|Humans|Lung Neoplasms|Male|Nucleic Acid Hybridization|Observer Variation|Oligonucleotide Array Sequence Analysis|Reference Values|Reproducibility of Results|Sex Characteristics', 'Evaluation Studies', '10.1186/1471-2105-6-274', '16297240', 'In two-channel competitive genomic hybridization microarray experiments, the ratio of the two fluorescent signal intensities at each spot on the microarray is commonly used to infer the relative amounts of the test and reference sample DNA levels. This ratio may be influenced by systematic measurement effects from non-biological sources that can introduce biases in the estimated ratios. These biases should be removed before drawing conclusions about the relative levels of DNA. The performance of existing gene expression microarray normalization strategies has not been evaluated for removing systematic biases encountered in array-based comparative genomic hybridization (CGH), which aims to detect single copy gains and losses typically in samples with heterogeneous cell populations resulting in only slight shifts in signal ratios. The purpose of this work is to establish a framework for correcting the systematic sources of variation in high density CGH array images, while maintaining the true biological variations.'),
(90601, 2005, 'bmc', 'Genome-wide identification of the regulatory targets of a transcription factor using biochemical characterization and computational genomic analysis', 'Jolly, Emmitt R|Chin, Chen-Shan|Herskowitz, Ira|Li, Hao', 'Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94143, USA. emmitt.jolly@itsa.ucsf.edu|Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94143, USA. emmitt.jolly@itsa.ucsf.edu|Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94143, USA. emmitt.jolly@itsa.ucsf.edu|Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94143, USA. emmitt.jolly@itsa.ucsf.edu', 'United States|United States|United States|United States', 16, 'Amino Acid Motifs|Binding Sites|Chromatin Immunoprecipitation|Computational Biology|DNA-Binding Proteins|False Positive Reactions|Genome, Fungal|Genomics|Models, Genetic|Models, Statistical|Models, Theoretical|Open Reading Frames|Protein Binding|Recombinant Fusion Proteins|Saccharomyces cerevisiae Proteins|Software|Time Factors|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-6-275', '16297241', 'A major challenge in computational genomics is the development of methodologies that allow accurate genome-wide prediction of the regulatory targets of a transcription factor. We present a method for target identification that combines experimental characterization of binding requirements with computational genomic analysis.'),
(90602, 2005, 'bmc', 'Principal component analysis for predicting transcription-factor binding motifs from array-derived data', 'Liu, Yunlong|Vincenti, Matthew P|Yokota, Hiroki', 'Department of Biomedical Engineering, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA. yunliu@iupui.edu|Department of Biomedical Engineering, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA. yunliu@iupui.edu|Department of Biomedical Engineering, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46202, USA. yunliu@iupui.edu', 'India|India|India', 7, 'Algorithms|Amino Acid Motifs|Chondrocytes|Computational Biology|DNA|Gene Expression Regulation|Humans|Interleukin-1|Models, Statistical|Monte Carlo Method|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Promoter Regions, Genetic|Protein Array Analysis|Protein Binding|Sequence Analysis, DNA|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-6-276', '16297243', 'The responses to interleukin 1 (IL-1) in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to transcription-factor binding motifs (TFBMs). In order to select a critical set of TFBMs from genomic DNA information and an array-derived data, an efficient algorithm to solve a combinatorial optimization problem is required. Although computational approaches based on evolutionary algorithms are commonly employed, an analytical algorithm would be useful to predict TFBMs at nearly no computational cost and evaluate varying modelling conditions. Singular value decomposition (SVD) is a powerful method to derive primary components of a given matrix. Applying SVD to a promoter matrix defined from regulatory DNA sequences, we derived a novel method to predict the critical set of TFBMs.'),
(90603, 2005, 'bmc', 'Discover protein sequence signatures from protein-protein interaction data', 'Fang, Jianwen|Haasl, Ryan J|Dong, Yinghua|Lushington, Gerald H', 'Bioinformatics Core Facility, University of Kansas, Lawrence, KS 66045, USA. jwfang@ku.edu|Bioinformatics Core Facility, University of Kansas, Lawrence, KS 66045, USA. jwfang@ku.edu|Bioinformatics Core Facility, University of Kansas, Lawrence, KS 66045, USA. jwfang@ku.edu|Bioinformatics Core Facility, University of Kansas, Lawrence, KS 66045, USA. jwfang@ku.edu', 'United States|United States|United States|United States', 16, 'Binding Sites|Conserved Sequence|Information Storage and Retrieval|Models, Molecular|Molecular Structure|Protein Interaction Mapping|Saccharomyces cerevisiae|Sequence Analysis, Protein|Sequence Homology', 'Journal Article', '10.1186/1471-2105-6-277', '16305745', 'The development of high-throughput technologies such as yeast two-hybrid systems and mass spectrometry technologies has made it possible to generate large protein-protein interaction (PPI) datasets. Mining these datasets for underlying biological knowledge has, however, remained a challenge.'),
(90604, 2005, 'bmc', 'Multiple sequence alignment accuracy and evolutionary distance estimation', 'Rosenberg, Michael S', 'Center for Evolutionary Functional Genomics, The Biodesign Institute, and the School of Life Sciences, Arizona State University, Tempe, AZ 85287-4501, USA. msr@asu.edu', 'United States', 30, 'Algorithms|Amino Acid Motifs|Animals|Base Sequence|Computational Biology|Computer Simulation|Computing Methodologies|Databases, Protein|Evaluation Studies as Topic|Evolution, Molecular|Gene Expression Profiling|Genome|Humans|Proteins|Reproducibility of Results|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-6-278', '16305750', 'Sequence alignment is a common tool in bioinformatics and comparative genomics. It is generally assumed that multiple sequence alignment yields better results than pair wise sequence alignment, but this assumption has rarely been tested, and never with the control provided by simulation analysis. This study used sequence simulation to examine the gain in accuracy of adding a third sequence to a pair wise alignment, particularly concentrating on how the phylogenetic position of the additional sequence relative to the first pair changes the accuracy of the initial pairs alignment as well as their estimated evolutionary distance.'),
(90605, 2005, 'bmc', 'Computational identification of strain-, species- and genus-specific proteins', 'Mazumder, Raja|Natale, Darren A|Murthy, Sudhir|Thiagarajan, Rathi|Wu, Cathy H', 'Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057-1414, USA. rm285@georgetown.edu|Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057-1414, USA. rm285@georgetown.edu|Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057-1414, USA. rm285@georgetown.edu|Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057-1414, USA. rm285@georgetown.edu|Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057-1414, USA. rm285@georgetown.edu', 'United States|United States|United States|United States|United States', 13, 'Algorithms|Bacillus anthracis|Bacteria|Bacterial Proteins|Classification|Computational Biology|Evolution, Molecular|Information Storage and Retrieval|Proteins|Software|Species Specificity|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-279', '16305751', 'The identification of unique proteins at different taxonomic levels has both scientific and practical value. Strain-, species- and genus-specific proteins can provide insight into the criteria that define an organism and its relationship with close relatives. Such proteins can also serve as taxon-specific diagnostic targets.'),
(90606, 2005, 'bmc', 'The distance-profile representation and its application to detection of distantly related protein families', 'Ku, Chin-Jen|Yona, Golan', 'Department of Computer Science, Cornell University, Ithaca, NY, USA. kucj@ece.cornell.edu|Department of Computer Science, Cornell University, Ithaca, NY, USA. kucj@ece.cornell.edu', 'United States|United States', 0, 'Algorithms|Animals|Computational Biology|Databases, Protein|Genetic Vectors|Humans|Models, Statistical|Multigene Family|Probability|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-6-282', '16316461', 'Detecting homology between remotely related protein families is an important problem in computational biology since the biological properties of uncharacterized proteins can often be inferred from those of homologous proteins. Many existing approaches address this problem by measuring the similarity between proteins through sequence or structural alignment. However, these methods do not exploit collective aspects of the protein space and the computed scores are often noisy and frequently fail to recognize distantly related protein families.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90607, 2005, 'bmc', 'An algorithm for the determination and quantification of components of nucleic acid mixtures based on single sequencing reactions', 'Pozhitkov, Alexander|Stemshorn, Kathryn|Tautz, Diethard', 'Institut für Genetik, der Universität zu Köln, Zülpicherstrasse 47, 50674 Köln, Germany. pozhit@u.washington.edu|Institut für Genetik, der Universität zu Köln, Zülpicherstrasse 47, 50674 Köln, Germany. pozhit@u.washington.edu|Institut für Genetik, der Universität zu Köln, Zülpicherstrasse 47, 50674 Köln, Germany. pozhit@u.washington.edu', 'Germany|Germany|Germany', 0, 'Algorithms|Animals|Base Sequence|Computational Biology|Computer Simulation|DNA|DNA Probes|Gene Expression Profiling|Image Interpretation, Computer-Assisted|Models, Genetic|Models, Statistical|Molecular Sequence Data|Nucleic Acid Hybridization|Nucleic Acids|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-6-281', '16316462', 'Determination and quantification of nucleic acid components in a mixture is usually accomplished by microarray approaches, where the mixtures are hybridized against specific probes. As an alternative, we propose here that a single sequencing reaction from a mixture of nucleic acids holds enough information to potentially distinguish the different components, provided it is known which components can occur in the mixture.'),
(90608, 2005, 'bmc', 'Linking enzyme sequence to function using Conserved Property Difference Locator to identify and annotate positions likely to control specific functionality', 'Mayer, Kimberly M|McCorkle, Sean R|Shanklin, John', 'Biology Department, Brookhaven National Laboratory, Upton, NY 11973, USA. mayerk@uncw.edu|Biology Department, Brookhaven National Laboratory, Upton, NY 11973, USA. mayerk@uncw.edu|Biology Department, Brookhaven National Laboratory, Upton, NY 11973, USA. mayerk@uncw.edu', 'United States|United States|United States', 25, 'Algorithms|Amino Acid Sequence|Animals|Arabidopsis|Binding Sites|Computational Biology|Dipeptides|Genomics|Models, Biological|Models, Molecular|Molecular Sequence Data|Peptidoglycan|Programming Languages|Protein Structure, Tertiary|Software|Structure-Activity Relationship|Uridine Diphosphate N-Acetylmuramic Acid', 'Journal Article', '10.1186/1471-2105-6-284', '16318626', 'Families of homologous enzymes evolved from common progenitors. The availability of multiple sequences representing each activity presents an opportunity for extracting information specifying the functionality of individual homologs. We present a straightforward method for the identification of residues likely to determine class specific functionality in which multiple sequence alignments are converted to an annotated graphical form by the Conserved Property Difference Locator (CPDL) program.'),
(90609, 2005, 'bmc', 'Identification of significant periodic genes in microarray gene expression data', 'Chen, Jie', 'Department of Mathematics and Statistics, University of Missouri-Kansas City, 5100 Rockhill Road, Kansas City, MO, USA. chenj@umkc.edu', 'United States', 0, 'Algorithms|Cell Cycle|Cell Line, Tumor|Computational Biology|Data Interpretation, Statistical|False Positive Reactions|Fibroblasts|Gene Expression Profiling|Gene Expression Regulation|Genes, Bacterial|Genes, Fungal|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Time Factors', 'Journal Article', '10.1186/1471-2105-6-286', '16318631', 'One frequent application of microarray experiments is in the study of monitoring gene activities in a cell during cell cycle or cell division. A new challenge for analyzing the microarray experiments is to identify genes that are statistically significantly periodically expressed during the cell cycle. Such a challenge occurs due to the large number of genes that are simultaneously measured, a moderate to small number of measurements per gene taken at different time points, and high levels of non-normal random noises inherited in the data.'),
(90610, 2005, 'bmc', 'DSD--an integrated, web-accessible database of Dehydrogenase Enzyme Stereospecificities', 'Toseland, Christopher P|McSparron, Helen M|Flower, Darren R', 'The Jenner Institute, University of Oxford, Compton, Berkshire, RG20 7NN, UK.|The Jenner Institute, University of Oxford, Compton, Berkshire, RG20 7NN, UK.|The Jenner Institute, University of Oxford, Compton, Berkshire, RG20 7NN, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Databases, Factual|Databases, Nucleic Acid|Databases, Protein|Enzymes|Hydrogen|Information Services|Information Storage and Retrieval|Internet|Oxidoreductases|Protein Folding|Proteins|Stereoisomerism|Substrate Specificity', 'Journal Article', '10.1186/1471-2105-6-283', '16318635', 'Dehydrogenase enzymes belong to the oxidoreductase class and utilise the coenzymes NAD and NADP. Stereo-selectivity is focused on the C4 hydrogen atoms of the nicotinamide ring of NAD(P). Depending upon which hydrogen is transferred at the C4 location, the enzyme is designated as A or B stereospecific.'),
(90611, 2005, 'bmc', 'Transformation and other factors of the peptide mass spectrometry pairwise peak-list comparison process', 'Wolski, Witold E|Lalowski, Maciej|Martus, Peter|Herwig, Ralf|Giavalisco, Patrick|Gobom, Johan|Sickmann, Albert|Lehrach, Hans|Reinert, Knut', 'Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk|Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, D-14195 Berlin, Germany. w.e.wolski@ncl.ac.uk', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Analysis of Variance|Animals|Arabidopsis|Bacterial Proteins|Brain|Calibration|Computational Biology|Data Interpretation, Statistical|Mass Spectrometry|Mice|Models, Statistical|Peptides|Proteins|ROC Curve|Software', 'Journal Article', '10.1186/1471-2105-6-285', '16318636', 'Biological Mass Spectrometry is used to analyse peptides and proteins. A mass spectrum generates a list of measured mass to charge ratios and intensities of ionised peptides, which is called a peak-list. In order to classify the underlying amino acid sequence, the acquired spectra are usually compared with synthetic ones. Development of suitable methods of direct peak-list comparison may be advantageous for many applications.'),
(90612, 2005, 'bmc', 'ArrayQuest: a web resource for the analysis of DNA microarray data', 'Argraves, Gary L|Jani, Saurin|Barth, Jeremy L|Argraves, W Scott', 'Array Genetics, Inc,, 59 Great Quarter Road, Newtown, CT 06482, USA. argraves@musc.edu|Array Genetics, Inc,, 59 Great Quarter Road, Newtown, CT 06482, USA. argraves@musc.edu|Array Genetics, Inc,, 59 Great Quarter Road, Newtown, CT 06482, USA. argraves@musc.edu|Array Genetics, Inc,, 59 Great Quarter Road, Newtown, CT 06482, USA. argraves@musc.edu', 'United States|United States|United States|United States', 17, 'Algorithms|Cluster Analysis|Computational Biology|Computer Graphics|DNA|Data Interpretation, Statistical|Database Management Systems|Databases, Factual|Databases, Genetic|Databases, Nucleic Acid|Databases, Protein|Gene Expression Profiling|Gene Library|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-287', '16321157', 'Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools.'),
(90613, 2005, 'bmc', 'Genetic Interaction Motif Finding by expectation maximization--a novel statistical model for inferring gene modules from synthetic lethality', 'Qi, Yan|Ye, Ping|Bader, Joel S', 'Biomedical Engineering Department, Johns Hopkins University, Baltimore, MD 21218, USA. yanqi@jhu.edu|Biomedical Engineering Department, Johns Hopkins University, Baltimore, MD 21218, USA. yanqi@jhu.edu|Biomedical Engineering Department, Johns Hopkins University, Baltimore, MD 21218, USA. yanqi@jhu.edu', 'United States|United States|United States', 13, 'Algorithms|Amino Acid Motifs|Computational Biology|Data Interpretation, Statistical|Gene Expression Profiling|Genes, Fungal|Genomics|Models, Genetic|Models, Statistical|Probability|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software', 'Journal Article', '10.1186/1471-2105-6-288', '16332255', 'Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership in a single protein complex) may be inferred between genes that share synthetic lethal interaction partners than genes that are directly synthetic lethal. Probabilistic algorithms that identify gene modules based on motif discovery are highly appropriate for the analysis of synthetic lethal genetic interaction data and have great potential in integrative analysis of heterogeneous datasets.'),
(90614, 2005, 'bmc', 'GenClust: a genetic algorithm for clustering gene expression data', 'Di Gesú, Vito|Giancarlo, Raffaele|Lo Bosco, Giosué|Raimondi, Alessandra|Scaturro, Davide', 'Dipartimento di Matematica ed Applicazioni, Universitá di Palermo, Via Archirafi 34, 90123 Palermo, Italy. digesu@math.unipa.it|Dipartimento di Matematica ed Applicazioni, Universitá di Palermo, Via Archirafi 34, 90123 Palermo, Italy. digesu@math.unipa.it|Dipartimento di Matematica ed Applicazioni, Universitá di Palermo, Via Archirafi 34, 90123 Palermo, Italy. digesu@math.unipa.it|Dipartimento di Matematica ed Applicazioni, Universitá di Palermo, Via Archirafi 34, 90123 Palermo, Italy. digesu@math.unipa.it|Dipartimento di Matematica ed Applicazioni, Universitá di Palermo, Via Archirafi 34, 90123 Palermo, Italy. digesu@math.unipa.it', 'Italy|Italy|Italy|Italy|Italy', 33, 'Algorithms|Cluster Analysis|Computational Biology|DNA, Complementary|Gene Expression Profiling|Gene Expression Regulation|Models, Statistical|Mutation|Oligonucleotide Array Sequence Analysis|Oligonucleotides|Open Reading Frames|Pattern Recognition, Automated|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-6-289', '16336639', 'Clustering is a key step in the analysis of gene expression data, and in fact, many classical clustering algorithms are used, or more innovative ones have been designed and validated for the task. Despite the widespread use of artificial intelligence techniques in bioinformatics and, more generally, data analysis, there are very few clustering algorithms based on the genetic paradigm, yet that paradigm has great potential in finding good heuristic solutions to a difficult optimization problem such as clustering.'),
(90615, 2005, 'bmc', 'An SVM-based system for predicting protein subnuclear localizations', 'Lei, Zhengdeng|Dai, Yang', 'Department of Bioengineering (MC063), University of Illinois at Chicago, 851 South Morgan Street, Chicago IL 60607, USA. zlei2@uic.edu|Department of Bioengineering (MC063), University of Illinois at Chicago, 851 South Morgan Street, Chicago IL 60607, USA. zlei2@uic.edu', 'United States|United States', 0, 'Algorithms|Animals|Cell Nucleus|Computational Biology|Databases, Protein|Genome|Humans|Internet|Mice|Models, Statistical|Protein Conformation|Proteins|Proteomics|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-6-291', '16336650', 'The large gap between the number of protein sequences in databases and the number of functionally characterized proteins calls for the development of a fast computational tool for the prediction of subnuclear and subcellular localizations generally applicable to protein sequences. The information on localization may reveal the molecular function of novel proteins, in addition to providing insight on the biological pathways in which they function. The bulk of past work has been focused on protein subcellular localizations. Furthermore, no specific tool has been dedicated to prediction at the subnuclear level, despite its high importance. In order to design a suitable predictive system, the extraction of subtle sequence signals that can discriminate among proteins with different subnuclear localizations is the key.'),
(90616, 2005, 'bmc', 'Efficient analysis and extraction of MS/MS result data from Mascot result files', 'Grosse-Coosmann, Florian|Boehm, Andreas M|Sickmann, Albert', 'Protein Mass Spectrometry and Functional Proteomics Group, Rudolf-Virchow-Center for Experimental Biomedicine, Universitaet Wuerzburg, Versbacher Strasse 9, D-97078 Wuerzburg, Germany. florian.coosmann@virchow.uni-wuerzburg.de|Protein Mass Spectrometry and Functional Proteomics Group, Rudolf-Virchow-Center for Experimental Biomedicine, Universitaet Wuerzburg, Versbacher Strasse 9, D-97078 Wuerzburg, Germany. florian.coosmann@virchow.uni-wuerzburg.de|Protein Mass Spectrometry and Functional Proteomics Group, Rudolf-Virchow-Center for Experimental Biomedicine, Universitaet Wuerzburg, Versbacher Strasse 9, D-97078 Wuerzburg, Germany. florian.coosmann@virchow.uni-wuerzburg.de', 'Germany|Germany|Germany', 12, 'Databases, Factual|Databases, Protein|Mass Spectrometry|Proteins|Software', 'Journal Article', '10.1186/1471-2105-6-290', '16336652', 'Mascot is a commonly used protein identification program for MS as well as for tandem MS data. When analyzing huge shotgun proteomics datasets with Mascots native tools, limits of computing resources are easily reached. Up to now no application has been available as open source that is capable of converting the full content of Mascot result files from the original MIME format into a database-compatible tabular format, allowing direct import into database management systems and efficient handling of huge datasets analyzed by Mascot.'),
(90617, 2005, 'bmc', 'SNP-VISTA: an interactive SNP visualization tool', 'Shah, Nameeta|Teplitsky, Michael V|Minovitsky, Simon|Pennacchio, Len A|Hugenholtz, Philip|Hamann, Bernd|Dubchak, Inna L', 'Institute for Data Analysis and Visualization, (IDAV), Department of Computer Science, University of California, Davis, One ShieldsAve., Davis, CA 95616, USA. nyshah@ucdavis.edu|Institute for Data Analysis and Visualization, (IDAV), Department of Computer Science, University of California, Davis, One ShieldsAve., Davis, CA 95616, USA. nyshah@ucdavis.edu|Institute for Data Analysis and Visualization, (IDAV), Department of Computer Science, University of California, Davis, One ShieldsAve., Davis, CA 95616, USA. nyshah@ucdavis.edu|Institute for Data Analysis and Visualization, (IDAV), Department of Computer Science, University of California, Davis, One ShieldsAve., Davis, CA 95616, USA. nyshah@ucdavis.edu|Institute for Data Analysis and Visualization, (IDAV), Department of Computer Science, University of California, Davis, One ShieldsAve., Davis, CA 95616, USA. nyshah@ucdavis.edu|Institute for Data Analysis and Visualization, (IDAV), Department of Computer Science, University of California, Davis, One ShieldsAve., Davis, CA 95616, USA. nyshah@ucdavis.edu|Institute for Data Analysis and Visualization, (IDAV), Department of Computer Science, University of California, Davis, One ShieldsAve., Davis, CA 95616, USA. nyshah@ucdavis.edu', 'United States|United States|United States|United States|United States|United States|United States', 13, 'Algorithms|Alleles|Chromosome Mapping|Cluster Analysis|Computational Biology|Computer Graphics|DNA Mutational Analysis|Databases, Nucleic Acid|Expressed Sequence Tags|Genome, Human|Haplotypes|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-292', '16336665', 'Recent advances in sequencing technologies promise to provide a better understanding of the genetics of human disease as well as the evolution of microbial populations. Single Nucleotide Polymorphisms (SNPs) are established genetic markers that aid in the identification of loci affecting quantitative traits and/or disease in a wide variety of eukaryotic species. With todays technological capabilities, it has become possible to re-sequence a large set of appropriate candidate genes in individuals with a given disease in an attempt to identify causative mutations. In addition, SNPs have been used extensively in efforts to study the evolution of microbial populations, and the recent application of random shotgun sequencing to environmental samples enables more extensive SNP analysis of co-occurring and co-evolving microbial populations. The program is available at http://genome.lbl.gov/vista/snpvista1.'),
(90618, 2005, 'bmc', 'An algorithm for automatic evaluation of the spot quality in two-color DNA microarray experiments', 'Novikov, Eugene|Barillot, Emmanuel', 'Service Bioinformatique, Institut Curie, 26 Rue dUlm, 75248 Paris Cedex 05, France. Eugene.Novikov@curie.fr|Service Bioinformatique, Institut Curie, 26 Rue dUlm, 75248 Paris Cedex 05, France. Eugene.Novikov@curie.fr', 'France|France', 12, 'Algorithms|Artificial Intelligence|Image Enhancement|Image Interpretation, Computer-Assisted|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence, Multiphoton|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-6-293', '16336688', 'Although DNA microarray technologies are very powerful for the simultaneous quantitative characterization of thousands of genes, the quality of the obtained experimental data is often far from ideal. The measured microarrays images represent a regular collection of spots, and the intensity of light at each spot is proportional to the DNA copy number or to the expression level of the gene whose DNA clone is spotted. Spot quality control is an essential part of microarray image analysis, which must be carried out at the level of individual spot identification. The problem is difficult to formalize due to the diversity of instrumental and biological factors that can influence the result.'),
(90619, 2005, 'bmc', 'Harshlight: a corrective make-up program for microarray chips', 'Suárez-Fariñas, Mayte|Pellegrino, Maurizio|Wittkowski, Knut M|Magnasco, Marcelo O', 'Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Ave, Box 212, New York, NY 10021, USA. mayte@babel.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Ave, Box 212, New York, NY 10021, USA. mayte@babel.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Ave, Box 212, New York, NY 10021, USA. mayte@babel.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Ave, Box 212, New York, NY 10021, USA. mayte@babel.rockefeller.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Artifacts|Automation|Cluster Analysis|Computational Biology|Gene Expression Profiling|Humans|Image Processing, Computer-Assisted|Models, Statistical|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Oligonucleotides|Software', 'Journal Article', '10.1186/1471-2105-6-294', '16336691', 'Microscopists are familiar with many blemishes that fluorescence images can have due to dust and debris, glass flaws, uneven distribution of fluids or surface coatings, etc. Microarray scans do show similar artifacts, which might affect subsequent analysis. Although all but the starkest blemishes are hard to find by the unaided eye, particularly in high-density oligonucleotide arrays (HDONAs), few tools are available to help with the detection of those defects.'),
(90620, 2005, 'bmc', 'PSE: a tool for browsing a large amount of MEDLINE/PubMed abstracts with gene names and common words as the keywords', 'Yoneya, Takashi', 'Pharmaceutical Division, Kirin Brewery Co, Ltd., 3 Miyahara, Takasaki, Gunma 370-1295, Japan. t-yoneya@kirin.co.jp', 'Japan', 4, 'Abstracting and Indexing as Topic|Algorithms|Computational Biology|Databases, Bibliographic|Genes, Neoplasm|Humans|Information Storage and Retrieval|Information Systems|MEDLINE|Names|Natural Language Processing|Neoplasms|Pattern Recognition, Automated|Programming Languages|PubMed|Software|Subject Headings|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-6-295', '16336692', 'MEDLINE/PubMed (hereinafter called PubMed) is one of the most important literature databases for the biological and medical sciences, but it is impossible to read all related records due to the sheer size of the repository. We usually have to repeatedly enter keywords in a trial-and-error manner to extract useful records. Software which can reduce such a laborious task is therefore required.'),
(90621, 2005, 'bmc', 'Oligomeric protein structure networks: insights into protein-protein interactions', 'Brinda, K V|Vishveshwara, Saraswathi', 'Molecular Biophysics Unit, Indian Institute of Science, Bangalore, 560012, India. brinda@mbu.iisc.ernet.in|Molecular Biophysics Unit, Indian Institute of Science, Bangalore, 560012, India. brinda@mbu.iisc.ernet.in', 'India|India', 0, 'Animals|Arginine|Cluster Analysis|Computational Biology|Crystallography, X-Ray|Databases, Protein|Humans|Hydrogen Bonding|Kinetics|Models, Molecular|Mutation|Protein Binding|Protein Conformation|Protein Engineering|Protein Interaction Mapping|Proteins|Proteomics|Thermodynamics|Tyrosine', 'Journal Article', '10.1186/1471-2105-6-296', '16336694', 'Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues) with special emphasis to protein interfaces.'),
(90622, 2005, 'bmc', 'InterferenceAnalyzer: tools for the analysis and simulation of multi-locus genetic data', 'Viswanath, Lalitha|Housworth, Elizabeth A', 'School of Informatics, Indiana University, Bloomington, Indiana, 47405, USA. lviswana@indiana.edu|School of Informatics, Indiana University, Bloomington, Indiana, 47405, USA. lviswana@indiana.edu', 'India|India', 4, 'Algorithms|Arabidopsis|Computational Biology|Computer Graphics|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Genomics|Models, Genetic|Models, Statistical|Programming Languages|Saccharomyces cerevisiae|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-297', '16343334', 'Good statistical models for analyzing and simulating multilocus recombination data exist but are not accessible to many biologists because their use requires reasonably sophisticated mathematical and computational implementation. While some labs have direct access to statisticians or programmers competent to carry out such analyses, many labs do not. We have created a platform independent application with an easy-to-use graphical user interface that will carry out such analyses including the simulations needed to bootstrap confidence intervals for the parameters of interest. This software should make multi-locus techniques accessible to labs that previously relied on less powerful and potentially statistically confounded single interval or double interval techniques.'),
(90623, 2005, 'bmc', 'Kalign--an accurate and fast multiple sequence alignment algorithm', 'Lassmann, Timo|Sonnhammer, Erik L L', 'Center for Genomics and Bioinformatics, Karolinska Institutet, Berzelius vag 35, S-17177 Stockholm, Sweden. timo.lassmann@cgb.ki.se|Center for Genomics and Bioinformatics, Karolinska Institutet, Berzelius vag 35, S-17177 Stockholm, Sweden. timo.lassmann@cgb.ki.se', 'Sweden|Sweden', 454, 'Algorithms|Databases, Nucleic Acid|Databases, Protein|Genome|Genomics|Reproducibility of Results|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-6-298', '16343337', 'The alignment of multiple protein sequences is a fundamental step in the analysis of biological data. It has traditionally been applied to analyzing protein families for conserved motifs, phylogeny, structural properties, and to improve sensitivity in homology searching. The availability of complete genome sequences has increased the demands on multiple sequence alignment (MSA) programs. Current MSA methods suffer from being either too inaccurate or too computationally expensive to be applied effectively in large-scale comparative genomics.'),
(90624, 2005, 'bmc', 'A microarray data-based semi-kinetic method for predicting quantitative dynamics of genetic networks', 'Yugi, Katsuyuki|Nakayama, Yoichi|Kojima, Shigen|Kitayama, Tomoya|Tomita, Masaru', 'Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0035, Japan. chaos@sfc.keio.ac.jp|Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0035, Japan. chaos@sfc.keio.ac.jp|Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0035, Japan. chaos@sfc.keio.ac.jp|Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0035, Japan. chaos@sfc.keio.ac.jp|Institute for Advanced Biosciences, Keio University, Tsuruoka, 997-0035, Japan. chaos@sfc.keio.ac.jp', 'Japan|Japan|Japan|Japan|Japan', 0, 'Amino Acid Motifs|Computational Biology|Computer Simulation|Escherichia coli|Gene Expression Profiling|Gene Expression Regulation|Genomics|Kinetics|Models, Genetic|Oligonucleotide Array Sequence Analysis|Proteomics|Ribosomes|Saccharomyces cerevisiae|Software|Systems Biology', 'Journal Article', '10.1186/1471-2105-6-299', '16351711', 'Elucidating the dynamic behaviour of genetic regulatory networks is one of the most significant challenges in systems biology. However, conventional quantitative predictions have been limited to small networks because publicly available transcriptome data has not been extensively applied to dynamic simulation.'),
(90625, 2005, 'bmc', 'Gene capture prediction and overlap estimation in EST sequencing from one or multiple libraries', 'Wang, Ji-Ping Z|Lindsay, Bruce G|Cui, Liying|Wall, P Kerr|Marion, Josh|Zhang, Jiaxuan|dePamphilis, Claude W', 'Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu|Department of Statistics, Northwestern University, Evanston, IL 60208, USA. jzwang@northwestern.edu', 'United States|United States|United States|United States|United States|United States|United States', 23, 'Algorithms|Arabidopsis Proteins|Base Sequence|Computer Simulation|DNA, Plant|Expressed Sequence Tags|Gene Expression Profiling|Gene Library|Models, Genetic|Models, Statistical|Molecular Sequence Data|Poisson Distribution|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1186/1471-2105-6-300', '16351717', 'In expressed sequence tag (EST) sequencing, we are often interested in how many genes we can capture in an EST sample of a targeted size. This information provides insights to sequencing efficiency in experimental design, as well as clues to the diversity of expressed genes in the tissue from which the library was constructed.'),
(90626, 2005, 'bmc', 'Modelling the interaction of steroid receptors with endocrine disrupting chemicals', 'DUrsi, Pasqualina|Salvi, Erika|Fossa, Paola|Milanesi, Luciano|Rovida, Ermanna', 'Department of Biomedical Sciences and Technologies, University of Milan, Segrate, Milan, 20090, Italy. pasqualina.dursi@itb.cnr.it|Department of Biomedical Sciences and Technologies, University of Milan, Segrate, Milan, 20090, Italy. pasqualina.dursi@itb.cnr.it|Department of Biomedical Sciences and Technologies, University of Milan, Segrate, Milan, 20090, Italy. pasqualina.dursi@itb.cnr.it|Department of Biomedical Sciences and Technologies, University of Milan, Segrate, Milan, 20090, Italy. pasqualina.dursi@itb.cnr.it|Department of Biomedical Sciences and Technologies, University of Milan, Segrate, Milan, 20090, Italy. pasqualina.dursi@itb.cnr.it', 'Italy|Italy|Italy|Italy|Italy', 23, 'Amino Acid Sequence|Binding Sites|Chlorine|Databases, Protein|Drug Interactions|Endocrine Glands|Endocrine System|Estrogen Receptor alpha|Hormones|Humans|Hydrogen Bonding|Ligands|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Conformation|Protein Structure, Tertiary|Receptors, Steroid|Sequence Homology, Amino Acid|Software|Steroids', 'Journal Article', '10.1186/1471-2105-6-S4-S10', '16351736', 'The organic polychlorinated compounds like dichlorodiphenyltrichloroethane with its metabolites and polychlorinated biphenyls are a class of highly persistent environmental contaminants. They have been recognized to have detrimental health effects both on wildlife and humans acting as endocrine disrupters due to their ability of mimicking the action of the steroid hormones, and thus interfering with hormone response. There are several experimental evidences that they bind and activate human steroid receptors. However, despite the growing concern about the toxicological activity of endocrine disrupters, molecular data of the interaction of these compounds with biological targets are still lacking.'),
(90627, 2005, 'bmc', 'A quantization method based on threshold optimization for microarray short time series', 'Di Camillo, Barbara|Sanchez-Cabo, Fatima|Toffolo, Gianna|Nair, Sreekumaran K|Trajanoski, Zlatko|Cobelli, Claudio', 'Information Engineering Department, University of Padova, Padova, 35131, Italy. dicamill@dei.unipd.it|Information Engineering Department, University of Padova, Padova, 35131, Italy. dicamill@dei.unipd.it|Information Engineering Department, University of Padova, Padova, 35131, Italy. dicamill@dei.unipd.it|Information Engineering Department, University of Padova, Padova, 35131, Italy. dicamill@dei.unipd.it|Information Engineering Department, University of Padova, Padova, 35131, Italy. dicamill@dei.unipd.it|Information Engineering Department, University of Padova, Padova, 35131, Italy. dicamill@dei.unipd.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 28, 'Algorithms|Bayes Theorem|Cluster Analysis|Computational Biology|Computer Simulation|False Negative Reactions|False Positive Reactions|Gene Expression Profiling|Gene Expression Regulation|Likelihood Functions|Models, Biological|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Probability|Regression Analysis|Systems Biology', 'Journal Article', '10.1186/1471-2105-6-S4-S11', '16351737', 'Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often very limited compared to the number of genes, thus the use of discrete data may help reducing the probability of finding random associations between genes.'),
(90628, 2005, 'bmc', 'A new decoding algorithm for hidden Markov models improves the prediction of the topology of all-beta membrane proteins', 'Fariselli, Piero|Martelli, Pier Luigi|Casadio, Rita', 'Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero.fariselli@unibo.it|Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero.fariselli@unibo.it|Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy. piero.fariselli@unibo.it', 'Italy|Italy|Italy', 0, 'Algorithms|Bayes Theorem|Cell Membrane|Computational Biology|Computer Graphics|Databases, Protein|Internet|Markov Chains|Membrane Proteins|Models, Biological|Models, Chemical|Models, Molecular|Models, Statistical|Probability|Protein Structure, Secondary|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-6-S4-S12', '16351738', 'Structure prediction of membrane proteins is still a challenging computational problem. Hidden Markov models (HMM) have been successfully applied to the problem of predicting membrane protein topology. In a predictive task, the HMM is endowed with a decoding algorithm in order to assign the most probable state path, and in turn the labels, to an unknown sequence. The Viterbi and the posterior decoding algorithms are the most common. The former is very efficient when one path dominates, while the latter, even though does not guarantee to preserve the HMM grammar, is more effective when several concurring paths have similar probabilities. A third good alternative is 1-best, which was shown to perform equal or better than Viterbi.'),
(90629, 2005, 'bmc', 'A neural strategy for the inference of SH3 domain-peptide interaction specificity', 'Ferraro, Enrico|Via, Allegra|Ausiello, Gabriele|Helmer-Citterich, Manuela', 'Centre for Molecular Bioinformatics, Department of Biology, University of Tor Vergata, Rome, Italy. enrico@cbm.bio.uniroma2.it|Centre for Molecular Bioinformatics, Department of Biology, University of Tor Vergata, Rome, Italy. enrico@cbm.bio.uniroma2.it|Centre for Molecular Bioinformatics, Department of Biology, University of Tor Vergata, Rome, Italy. enrico@cbm.bio.uniroma2.it|Centre for Molecular Bioinformatics, Department of Biology, University of Tor Vergata, Rome, Italy. enrico@cbm.bio.uniroma2.it', 'Italy|Italy|Italy|Italy', 10, 'Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Computational Biology|Ligands|Models, Molecular|Neural Networks (Computer)|Peptide Library|Peptides|Protein Binding|Protein Conformation|Protein Structure, Tertiary|Proteins|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sensitivity and Specificity|Sequence Alignment|src Homology Domains', 'Journal Article', '10.1186/1471-2105-6-S4-S13', '16351739', 'The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that generally characterizes its ligands does not reflect the complex interaction spectrum of the over 1500 different SH3 domains, and the requirement of a more refined knowledge of their specificity implies the setting up of appropriate experimental and theoretical strategies. Due to the limitations of the current technology for peptide synthesis, several experimental high-throughput approaches have been devised to elucidate protein-protein interaction mechanisms. Such approaches can rely on and take advantage of computational techniques, such as regular expressions or position specific scoring matrices (PSSMs) to pre-process entire proteomes in the search for putative SH3 targets. In this regard, a reliable inference methodology to be used for reducing the sequence space of putative binding peptides represents a valuable support for molecular and cellular biologists.'),
(90630, 2005, 'bmc', 'Mining published lists of cancer related microarray experiments: identification of a gene expression signature having a critical role in cell-cycle control', 'Finocchiaro, Giacomo|Mancuso, Francesco|Muller, Heiko', 'European Institute of Oncology, Via Ripamonti 435, 20141 Milan, Italy. Giacomo.finocchiaro@ifom-ieo-campus.it|European Institute of Oncology, Via Ripamonti 435, 20141 Milan, Italy. Giacomo.finocchiaro@ifom-ieo-campus.it|European Institute of Oncology, Via Ripamonti 435, 20141 Milan, Italy. Giacomo.finocchiaro@ifom-ieo-campus.it', 'Italy|Italy|Italy', 16, 'Cell Cycle|Computational Biology|Cyclin-Dependent Kinase Inhibitor p16|Data Interpretation, Statistical|Databases, Factual|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Information Storage and Retrieval|Models, Statistical|Models, Theoretical|Neoplasms|Oligonucleotide Array Sequence Analysis|Oncogene Proteins, Fusion|Proto-Oncogene Protein c-fli-1|RNA-Binding Protein EWS|Research Design|Retinoblastoma Protein|Software|Statistics as Topic|Transcription Factors', 'Journal Article', '10.1186/1471-2105-6-S4-S14', '16351740', 'Routine application of gene expression microarray technology is rapidly producing large amounts of data that necessitate new approaches of analysis. The analysis of a specific microarray experiment profits enormously from cross-comparing to other experiments. This process is generally performed by numerical meta-analysis of published data where the researcher chooses the datasets to be analyzed based on assumptions about the biological relations of published datasets to his own data, thus severely limiting the possibility of finding surprising connections. Here we propose using a repository of published gene lists for the identification of interesting datasets to be subjected to more detailed numerical analysis.'),
(90631, 2005, 'bmc', 'In silico functional characterization of a double histone fold domain from the Heliothis zea virus 1', 'Greco, Claudio|Fantucci, Piercarlo|De Gioia, Luca', 'Dipartimento di Biotecnologie e Bioscienze, Università degli Studi Milano-Bicocca, P.zza della Scienza 2, 20126 Milan, Italy. claudio.greco@unimib.it|Dipartimento di Biotecnologie e Bioscienze, Università degli Studi Milano-Bicocca, P.zza della Scienza 2, 20126 Milan, Italy. claudio.greco@unimib.it|Dipartimento di Biotecnologie e Bioscienze, Università degli Studi Milano-Bicocca, P.zza della Scienza 2, 20126 Milan, Italy. claudio.greco@unimib.it', 'Italy|Italy|Italy', 0, 'Algorithms|Amino Acid Sequence|Chromatin|Chromosomal Proteins, Non-Histone|Computational Biology|Computer Simulation|DNA|Dimerization|Histones|Macromolecular Substances|Models, Molecular|Molecular Sequence Data|Nuclear Proteins|Nucleosomes|Protein Binding|Protein Conformation|Protein Folding|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Sequence Homology, Amino Acid|Static Electricity|Viral Proteins|Viruses', 'Journal Article', '10.1186/1471-2105-6-S4-S15', '16351741', 'Histones are short proteins involved in chromatin packaging, in eukaryotes, two H2a-H2b and H3-H4 histone dimers form the nucleosomal core, which acts as the fundamental DNA-packaging element. The double histone fold is a rare globular protein fold in which two consecutive regions characterized by the typical structure of histones assemble together, thus originating a histone pseudodimer. This fold is included in a few prokaryotic histones and in the regulatory region of guanine nucleotide exchange factors of the Sos family. For the prokaryotic histones, there is no direct structural counterpart in the nucleosomal core particle, while the pseudodimer from Sos proteins is very similar to the dimer formed by histones H2a and H2b.'),
(90632, 2005, 'bmc', 'ESTree db: a tool for peach functional genomics', 'Lazzari, Barbara|Caprera, Andrea|Vecchietti, Alberto|Stella, Alessandra|Milanesi, Luciano|Pozzi, Carlo', 'Parco Tecnologico Padano, Via Einstein, Località Cascina Codazza, 26900 Lodi, Italy. barbara.lazzari@tecnoparco.org|Parco Tecnologico Padano, Via Einstein, Località Cascina Codazza, 26900 Lodi, Italy. barbara.lazzari@tecnoparco.org|Parco Tecnologico Padano, Via Einstein, Località Cascina Codazza, 26900 Lodi, Italy. barbara.lazzari@tecnoparco.org|Parco Tecnologico Padano, Via Einstein, Località Cascina Codazza, 26900 Lodi, Italy. barbara.lazzari@tecnoparco.org|Parco Tecnologico Padano, Via Einstein, Località Cascina Codazza, 26900 Lodi, Italy. barbara.lazzari@tecnoparco.org|Parco Tecnologico Padano, Via Einstein, Località Cascina Codazza, 26900 Lodi, Italy. barbara.lazzari@tecnoparco.org', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Chromosome Mapping|Computational Biology|DNA, Complementary|Database Management Systems|Databases, Genetic|Expressed Sequence Tags|Gene Expression Regulation, Plant|Gene Library|Genes, Plant|Genome, Plant|Genomics|Internet|Polymorphism, Single Nucleotide|Programming Languages|Prunus|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-S4-S16', '16351742', 'The ESTree db http://www.itb.cnr.it/estree/ represents a collection of Prunus persica expressed sequenced tags (ESTs) and is intended as a resource for peach functional genomics. A total of 6,155 successful EST sequences were obtained from four in-house prepared cDNA libraries from Prunus persica mesocarps at different developmental stages. Another 12,475 peach EST sequences were downloaded from public databases and added to the ESTree db. An automated pipeline was prepared to process EST sequences using public software integrated by in-house developed Perl scripts and data were collected in a MySQL database. A php-based web interface was developed to query the database.'),
(90633, 2005, 'bmc', 'Browsing isolated population data', 'Mancosu, Gianmaria|Cosso, Massimiliano|Marras, Francesca|Borlino, Cesare Cappio|Ledda, Giuseppe|Manias, Teresa|Adamo, Mauro|Serra, Donatella|Melis, Paola|Pirastu, Mario', 'SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it|SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it|SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it|SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it|SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it|SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it|SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it|SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it|SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it|SharDNA Life Sciences, Cagliari, Italy. mancosu@shardna.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Chromosome Mapping|Computational Biology|Computer Graphics|Database Management Systems|Databases, Genetic|Female|Genetic Linkage|Genetic Markers|Genetics, Population|Humans|Information Storage and Retrieval|Internet|Italy|Linkage Disequilibrium|Male|Models, Genetic|Pedigree|Population|Population Groups|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-S4-S17', '16351743', 'In our studies of genetically isolated populations in a remote mountain area in the center of Sardinia (Italy), we found that 80-85% of the inhabitants of each village belong to a single huge pedigree with families strictly connected to each other through hundreds of loops. Moreover, intermarriages between villages join pedigrees of different villages through links that make family trees even more complicated. Unfortunately, none of the commonly used pedigree drawing tools are able to draw the complete pedigree, whereas it is commonly accepted that the visual representation of families is very important as it helps researchers in identifying clusters of inherited traits and genotypes. We had a representation issue that compels researchers to work with subsets extracted from the overall genealogy, causing a serious loss of information on familiar relationships. To visually explore such complex pedigrees, we developed PedNavigator, a browser for genealogical databases properly suited for genetic studies.'),
(90634, 2005, 'bmc', 'Inherited disorder phenotypes: controlled annotation and statistical analysis for knowledge mining from gene lists', 'Masseroli, Marco|Galati, Osvaldo|Manzotti, Mauro|Gibert, Karina|Pinciroli, Francesco', 'Bioengineering Department, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milan, Italy. masseroli@biomed.polimi.it|Bioengineering Department, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milan, Italy. masseroli@biomed.polimi.it|Bioengineering Department, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milan, Italy. masseroli@biomed.polimi.it|Bioengineering Department, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milan, Italy. masseroli@biomed.polimi.it|Bioengineering Department, Politecnico di Milano, piazza Leonardo da Vinci 32, 20133 Milan, Italy. masseroli@biomed.polimi.it', 'Italy|Italy|Italy|Italy|Italy', 0, 'Computational Biology|Database Management Systems|Databases, Genetic|Databases, Nucleic Acid|Gene Expression Profiling|Genetic Diseases, Inborn|Genetics, Medical|Genomics|Humans|Information Storage and Retrieval|Internet|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Phenotype|Phenylketonurias|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-S4-S18', '16351744', 'Analysis of inherited diseases and their associated phenotypes is of great importance to gain knowledge of underlying genetic interactions and could ultimately give clinically useful insights into disease processes, including complex diseases influenced by multiple genetic loci. Nevertheless, to date few computational contributions have been proposed for this purpose, mainly due to lack of controlled clinical information easily accessible and structured for computational genome-wise analyses. To allow performing phenotype analyses of inherited disorder related genes we implemented new original modules within GFINDer http://www.bioinformatics.polimi.it/GFINDer/, a Web system we previously developed that dynamically aggregates functional annotations of user uploaded gene lists and allows performing their statistical analysis and mining.'),
(90635, 2005, 'bmc', 'High performance workflow implementation for protein surface characterization using grid technology', 'Merelli, Ivan|Morra, Giulia|DAgostino, Daniele|Clematis, Andrea|Milanesi, Luciano', 'Istituto di Tecnologie Biomediche (ITB-CNR), via F.lli Cervi, Segrate, Milan, Italy. ivan.merelli@itb.cnr.it|Istituto di Tecnologie Biomediche (ITB-CNR), via F.lli Cervi, Segrate, Milan, Italy. ivan.merelli@itb.cnr.it|Istituto di Tecnologie Biomediche (ITB-CNR), via F.lli Cervi, Segrate, Milan, Italy. ivan.merelli@itb.cnr.it|Istituto di Tecnologie Biomediche (ITB-CNR), via F.lli Cervi, Segrate, Milan, Italy. ivan.merelli@itb.cnr.it|Istituto di Tecnologie Biomediche (ITB-CNR), via F.lli Cervi, Segrate, Milan, Italy. ivan.merelli@itb.cnr.it', 'Italy|Italy|Italy|Italy|Italy', 0, 'Automation|Computational Biology|Computer Graphics|Computer Systems|Computing Methodologies|Data Interpretation, Statistical|Database Management Systems|Databases, Genetic|Databases, Protein|Information Storage and Retrieval|Internet|Molecular Conformation|Proteins|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-S4-S19', '16351745', 'This study concerns the development of a high performance workflow that, using grid technology, correlates different kinds of Bioinformatics data, starting from the base pairs of the nucleotide sequence to the exposed residues of the protein surface. The implementation of this workflow is based on the Italian Grid.it project infrastructure, that is a network of several computational resources and storage facilities distributed at different grid sites.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90636, 2005, 'bmc', 'Regularized Least Squares Cancer classifiers from DNA microarray data', 'Ancona, Nicola|Maglietta, Rosalia|DAddabbo, Annarita|Liuni, Sabino|Pesole, Graziano', 'Istituto di Studi sui Sistemi Intelligenti per IAutomazione, CNR, Via Amendola 122/D-I, 70126 Bari, Italy. ancona@ba.issia.cnr.it|Istituto di Studi sui Sistemi Intelligenti per IAutomazione, CNR, Via Amendola 122/D-I, 70126 Bari, Italy. ancona@ba.issia.cnr.it|Istituto di Studi sui Sistemi Intelligenti per IAutomazione, CNR, Via Amendola 122/D-I, 70126 Bari, Italy. ancona@ba.issia.cnr.it|Istituto di Studi sui Sistemi Intelligenti per IAutomazione, CNR, Via Amendola 122/D-I, 70126 Bari, Italy. ancona@ba.issia.cnr.it|Istituto di Studi sui Sistemi Intelligenti per IAutomazione, CNR, Via Amendola 122/D-I, 70126 Bari, Italy. ancona@ba.issia.cnr.it', 'Italy|Italy|Italy|Italy|Italy', 26, 'Algorithms|Cluster Analysis|Computational Biology|Computer Simulation|Discriminant Analysis|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Least-Squares Analysis|Models, Genetic|Models, Statistical|Neoplasms|Nonlinear Dynamics|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-6-S4-S2', '16351746', 'The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information provided by DNA microarrays allows an approach to the problem of cancer analysis from a quantitative rather than qualitative point of view. Cancer classification requires well founded mathematical methods which are able to predict the status of new specimens with high significance levels starting from a limited number of data. In this paper we assess the performances of Regularized Least Squares (RLS) classifiers, originally proposed in regularization theory, by comparing them with Support Vector Machines (SVM), the state-of-the-art supervised learning technique for cancer classification by DNA microarray data. The performances of both approaches have been also investigated with respect to the number of selected genes and different gene selection strategies.'),
(90637, 2005, 'bmc', 'Systematic analysis of human kinase genes: a large number of genes and alternative splicing events result in functional and structural diversity', 'Milanesi, Luciano|Petrillo, Mauro|Sepe, Leandra|Boccia, Angelo|DAgostino, Nunzio|Passamano, Myriam|Di Nardo, Salvatore|Tasco, Gianluca|Casadio, Rita|Paolella, Giovanni', 'Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it|Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it|Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it|Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it|Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it|Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it|Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it|Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it|Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it|Biomedical Technologies Institute (ITB), National Research Council, Milan, Italy. luciano.milanesi@itb.cnr.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Alternative Splicing|Amino Acid Motifs|Animals|Apoptosis|Cell Proliferation|Chromosome Mapping|Computational Biology|Databases, Genetic|Databases, Protein|Disulfides|Exons|Gene Expression Regulation, Enzymologic|Genetic Variation|Genome|Humans|Internet|Mice|Models, Genetic|Molecular Sequence Data|Multigene Family|Phosphotransferases|Protein Structure, Tertiary|Proteome|Sequence Analysis|Software|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-6-S4-S20', '16351747', 'Protein kinases are a well defined family of proteins, characterized by the presence of a common kinase catalytic domain and playing a significant role in many important cellular processes, such as proliferation, maintenance of cell shape, apoptosis. In many members of the family, additional non-kinase domains contribute further specialization, resulting in subcellular localization, protein binding and regulation of activity, among others. About 500 genes encode members of the kinase family in the human genome, and although many of them represent well known genes, a larger number of genes code for proteins of more recent identification, or for unknown proteins identified as kinase only after computational studies.'),
(90638, 2005, 'bmc', 'HomoMINT: an inferred human network based on orthology mapping of protein interactions discovered in model organisms', 'Persico, Maria|Ceol, Arnaud|Gavrila, Caius|Hoffmann, Robert|Florio, Arnaldo|Cesareni, Gianni', 'Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy. maria@cbm.bio.uniroma2.it|Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy. maria@cbm.bio.uniroma2.it|Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy. maria@cbm.bio.uniroma2.it|Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy. maria@cbm.bio.uniroma2.it|Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy. maria@cbm.bio.uniroma2.it|Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy. maria@cbm.bio.uniroma2.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Computational Biology|Genome|Humans|Information Storage and Retrieval|Internet|Models, Statistical|Pattern Recognition, Automated|Protein Binding|Protein Structure, Tertiary|Proteins|Proteome|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-6-S4-S21', '16351748', 'The application of high throughput approaches to the identification of protein interactions has offered for the first time a glimpse of the global interactome of some model organisms. Until now, however, such genome-wide approaches have not been applied to the human proteome.'),
(90639, 2005, 'bmc', 'NemaFootPrinter: a web based software for the identification of conserved non-coding genome sequence regions between C elegans and C briggsae', 'Rambaldi, Davide|Guffanti, Alessandro|Morandi, Paolo|Cassata, Giuseppe', 'IFOM-FIRC Institute of Molecular Oncology Foundation, Milan, Italy. davide.rambaldi@ifom-ieo-campus.it|IFOM-FIRC Institute of Molecular Oncology Foundation, Milan, Italy. davide.rambaldi@ifom-ieo-campus.it|IFOM-FIRC Institute of Molecular Oncology Foundation, Milan, Italy. davide.rambaldi@ifom-ieo-campus.it|IFOM-FIRC Institute of Molecular Oncology Foundation, Milan, Italy. davide.rambaldi@ifom-ieo-campus.it', 'Italy|Italy|Italy|Italy', 0, 'Animals|Automation|Caenorhabditis|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Computational Biology|Computers|Conserved Sequence|Databases, Factual|Exons|Genome|Genomics|Internet|Sequence Alignment|Software|Species Specificity|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-6-S4-S22', '16351749', 'NemaFootPrinter (Nematode Transcription Factor Scan Through Philogenetic Footprinting) is a web-based software for interactive identification of conserved, non-exonic DNA segments in the genomes of C. elegans and C. briggsae. It has been implemented according to the following project specifications:a) Automated identification of orthologous gene pairs. b) Interactive selection of the boundaries of the genes to be compared. c) Pairwise sequence comparison with a range of different methods. d) Identification of putative transcription factor binding sites on conserved, non-exonic DNA segments.'),
(90640, 2005, 'bmc', 'Improving interoperability between microbial information and sequence databases', 'Romano, Paolo|Dawyndt, Peter|Piersigilli, Francesca|Swings, Jean', 'Bioinformatics and Structural Proteomics, National Cancer Research Institute, Largo Rosanna Benzi 10, I-16132, Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute, Largo Rosanna Benzi 10, I-16132, Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute, Largo Rosanna Benzi 10, I-16132, Genova, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute, Largo Rosanna Benzi 10, I-16132, Genova, Italy. paolo.romano@istge.it', 'Italy|Italy|Italy|Italy', 0, 'Base Sequence|Computational Biology|Database Management Systems|Databases as Topic|Databases, Factual|Databases, Genetic|Information Storage and Retrieval|Information Systems|Internet|Molecular Biology|Programming Languages|Sequence Alignment|Sequence Analysis|Software|Systems Integration', 'Journal Article', '10.1186/1471-2105-6-S4-S23', '16351750', 'Biological resources are essential tools for biomedical research. Their availability is promoted through on-line catalogues. Common Access to Biological Resources and Information (CABRI) is a service for distribution of biological resources and related data collected by 28 European culture collections. Linking this information to bioinformatics databanks can make the collections holdings more visible after a search in molecular biology databanks and vice-versa. Identification of links to sequence databases can be useful, but annotation and indexing problems, together with compilation errors, immediately arise. In this paper, we present our efforts for the identification of cross-references between CABRI catalogues and the EMBL Data Library and related results.'),
(90641, 2005, 'bmc', 'Web services and workflow management for biological resources', 'Romano, Paolo|Marra, Domenico|Milanesi, Luciano', 'Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, I-16132, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, I-16132, Italy. paolo.romano@istge.it|Bioinformatics and Structural Proteomics, National Cancer Research Institute (IST), Genova, I-16132, Italy. paolo.romano@istge.it', 'Italy|Italy|Italy', 0, 'Animals|Computational Biology|Computer Graphics|Computer User Training|Database Management Systems|Databases, Factual|Databases, Genetic|Databases, Nucleic Acid|Humans|Information Storage and Retrieval|Internet|Mutation|Online Systems|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-S4-S24', '16351751', 'The completion of the Human Genome Project has resulted in large quantities of biological data which are proving difficult to manage and integrate effectively. There is a need for a system that is able to automate accesses to remote sites and to understand the information that it is managing in order to link data properly. Workflow management systems combined with Web Services are promising Information and Communication Technologies (ICT) tools. Some have already been proposed and are being increasingly applied to the biomedical domain, especially as many biology-related Web Services are now becoming available. Information on biological resources and on genomic sequences mutations are two examples of very specialized datasets that are useful for specific research domains.'),
(90642, 2005, 'bmc', 'A hybrid genetic-neural system for predicting protein secondary structure', 'Armano, Giuliano|Mancosu, Gianmaria|Milanesi, Luciano|Orro, Alessandro|Saba, Massimiliano|Vargiu, Eloisa', 'Dept. of Electrical and Electronic Engineering, University of Cagliari Piazza dArmi, I-09123 Cagliari, Italy. armano@diee.unica.it|Dept. of Electrical and Electronic Engineering, University of Cagliari Piazza dArmi, I-09123 Cagliari, Italy. armano@diee.unica.it|Dept. of Electrical and Electronic Engineering, University of Cagliari Piazza dArmi, I-09123 Cagliari, Italy. armano@diee.unica.it|Dept. of Electrical and Electronic Engineering, University of Cagliari Piazza dArmi, I-09123 Cagliari, Italy. armano@diee.unica.it|Dept. of Electrical and Electronic Engineering, University of Cagliari Piazza dArmi, I-09123 Cagliari, Italy. armano@diee.unica.it|Dept. of Electrical and Electronic Engineering, University of Cagliari Piazza dArmi, I-09123 Cagliari, Italy. armano@diee.unica.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Computational Biology|Computer Simulation|Databases, Protein|Models, Chemical|Models, Molecular|Molecular Sequence Data|Neural Networks (Computer)|Protein Conformation|Protein Folding|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-6-S4-S3', '16351752', 'Due to the strict relation between protein function and structure, the prediction of protein 3D-structure has become one of the most important tasks in bioinformatics and proteomics. In fact, notwithstanding the increase of experimental data on protein structures available in public databases, the gap between known sequences and known tertiary structures is constantly increasing. The need for automatic methods has brought the development of several prediction and modelling tools, but a general methodology able to solve the problem has not yet been devised, and most methodologies concentrate on the simplified task of predicting secondary structure.'),
(90643, 2005, 'bmc', 'HmtDB, a human mitochondrial genomic resource based on variability studies supporting population genetics and biomedical research', 'Attimonelli, Marcella|Accetturo, Matteo|Santamaria, Monica|Lascaro, Daniela|Scioscia, Gaetano|Pappadà, Graziano|Russo, Luigi|Zanchetta, Luigi|Tommaseo-Ponzetta, Mila', 'Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, Via E. Orabona 4, 70126 Bari, Italy. m.attimonelli@biologia.uniba.it|Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, Via E. Orabona 4, 70126 Bari, Italy. m.attimonelli@biologia.uniba.it|Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, Via E. Orabona 4, 70126 Bari, Italy. m.attimonelli@biologia.uniba.it|Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, Via E. Orabona 4, 70126 Bari, Italy. m.attimonelli@biologia.uniba.it|Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, Via E. Orabona 4, 70126 Bari, Italy. m.attimonelli@biologia.uniba.it|Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, Via E. Orabona 4, 70126 Bari, Italy. m.attimonelli@biologia.uniba.it|Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, Via E. Orabona 4, 70126 Bari, Italy. m.attimonelli@biologia.uniba.it|Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, Via E. Orabona 4, 70126 Bari, Italy. m.attimonelli@biologia.uniba.it|Dipartimento di Biochimica e Biologia Molecolare, Università di Bari, Via E. Orabona 4, 70126 Bari, Italy. m.attimonelli@biologia.uniba.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Computational Biology|DNA, Mitochondrial|Databases, Factual|Databases, Genetic|Databases, Nucleic Acid|Databases, Protein|Genetics, Population|Genome|Genotype|Humans|Information Storage and Retrieval|Internet|Mitochondrial Proteins|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-6-S4-S4', '16351753', 'Population genetics studies based on the analysis of mtDNA and mitochondrial disease studies have produced a huge quantity of sequence data and related information. These data are at present worldwide distributed in differently organised databases and web sites not well integrated among them. Moreover it is not generally possible for the user to submit and contemporarily analyse its own data comparing them with the content of a given database, both for population genetics and mitochondrial disease data.'),
(90644, 2005, 'bmc', 'Query3d: a new method for high-throughput analysis of functional residues in protein structures', 'Ausiello, Gabriele|Via, Allegra|Helmer-Citterich, Manuela', 'Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy. ausiello@cbm.bio.uniroma2.it|Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy. ausiello@cbm.bio.uniroma2.it|Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica, 00133 Rome, Italy. ausiello@cbm.bio.uniroma2.it', 'Italy|Italy|Italy', 47, 'Algorithms|Automation|Computational Biology|Computer Simulation|Databases, Protein|Models, Molecular|Models, Statistical|Molecular Structure|Programming Languages|Protein Conformation|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-6-S4-S5', '16351754', 'The identification of local similarities between two protein structures can provide clues of a common function. Many different methods exist for searching for similar subsets of residues in proteins of known structure. However, the lack of functional and structural information on single residues, together with the low level of integration of this information in comparison methods, is a limitation that prevents these methods from being fully exploited in high-throughput analyses.'),
(90645, 2005, 'bmc', 'MicroGen: a MIAME compliant web system for microarray experiment information and workflow management', 'Burgarella, Sarah|Cattaneo, Dario|Pinciroli, Francesco|Masseroli, Marco', 'Bioengineering Department, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy. sarah_burgarella@virgilio.it|Bioengineering Department, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy. sarah_burgarella@virgilio.it|Bioengineering Department, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy. sarah_burgarella@virgilio.it|Bioengineering Department, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milan, Italy. sarah_burgarella@virgilio.it', 'Italy|Italy|Italy|Italy', 0, 'Computational Biology|Data Interpretation, Statistical|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Gene Library|Information Storage and Retrieval|Internet|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Programming Languages|Protein Array Analysis|Software|Software Design|Statistics as Topic|Toxicogenetics|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-S4-S6', '16351755', 'Improvements of bio-nano-technologies and biomolecular techniques have led to increasing production of high-throughput experimental data. Spotted cDNA microarray is one of the most diffuse technologies, used in single research laboratories and in biotechnology service facilities. Although they are routinely performed, spotted microarray experiments are complex procedures entailing several experimental steps and actors with different technical skills and roles. During an experiment, involved actors, who can also be located in a distance, need to access and share specific experiment information according to their roles. Furthermore, complete information describing all experimental steps must be orderly collected to allow subsequent correct interpretation of experimental results.'),
(90646, 2005, 'bmc', 'An integrated approach of immunogenomics and bioinformatics to identify new Tumor Associated Antigens (TAA) for mammary cancer immunological prevention', 'Cavallo, Federica|Astolfi, Annalisa|Iezzi, Manuela|Cordero, Francesca|Lollini, Pier-Luigi|Forni, Guido|Calogero, Raffaele', 'Dept. of Clinical and Biological Sciences, University of Torino, Az. Ospedaliera S. Luigi, Regione Gonzole 10, I-10043 Orbassano, Italy. federica.cavallo@unito.it|Dept. of Clinical and Biological Sciences, University of Torino, Az. Ospedaliera S. Luigi, Regione Gonzole 10, I-10043 Orbassano, Italy. federica.cavallo@unito.it|Dept. of Clinical and Biological Sciences, University of Torino, Az. Ospedaliera S. Luigi, Regione Gonzole 10, I-10043 Orbassano, Italy. federica.cavallo@unito.it|Dept. of Clinical and Biological Sciences, University of Torino, Az. Ospedaliera S. Luigi, Regione Gonzole 10, I-10043 Orbassano, Italy. federica.cavallo@unito.it|Dept. of Clinical and Biological Sciences, University of Torino, Az. Ospedaliera S. Luigi, Regione Gonzole 10, I-10043 Orbassano, Italy. federica.cavallo@unito.it|Dept. of Clinical and Biological Sciences, University of Torino, Az. Ospedaliera S. Luigi, Regione Gonzole 10, I-10043 Orbassano, Italy. federica.cavallo@unito.it|Dept. of Clinical and Biological Sciences, University of Torino, Az. Ospedaliera S. Luigi, Regione Gonzole 10, I-10043 Orbassano, Italy. federica.cavallo@unito.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Allergy and Immunology|Animals|Antigens, Neoplasm|Breast Neoplasms|Computational Biology|DNA|Gene Expression Regulation, Neoplastic|Genomics|Humans|Internet|Mice|Neoplasms|Oligonucleotide Array Sequence Analysis|Protein Array Analysis|Signal Transduction', 'Journal Article', '10.1186/1471-2105-6-S4-S7', '16351756', 'Neoplastic transformation is a multistep process in which distinct gene products of specific cell regulatory pathways are involved at each stage. Identification of overexpressed genes provides an unprecedented opportunity to address the immune system against antigens typical of defined stages of neoplastic transformation. HER-2/neu/ERBB2 (Her2) oncogene is a prototype of deregulated oncogenic protein kinase membrane receptors. Mice transgenic for rat Her2 (BALB-neuT mice) were studied to evaluate the stage in which vaccines can prevent the onset of Her2 driven mammary carcinomas. As Her2 is not overexpressed in all mammary carcinomas, definition of an additional set of tumor associated antigens (TAAs) expressed at defined stages by most breast carcinomas would allow a broader coverage of vaccination. To address this question, a meta-analysis was performed on two transcription profile studies to identify a set of new TAA targets to be used instead of or in conjunction with Her2.'),
(90647, 2005, 'bmc', 'Secondary structure assignment that accurately reflects physical and evolutionary characteristics', 'Cubellis, Maria Vittoria|Cailliez, Fabien|Lovell, Simon C', 'Biochemistry Dept, University of Cambridge, Cambridge CB2 1GA, UK. cubellis@unina.it|Biochemistry Dept, University of Cambridge, Cambridge CB2 1GA, UK. cubellis@unina.it|Biochemistry Dept, University of Cambridge, Cambridge CB2 1GA, UK. cubellis@unina.it', 'United Kingdom|United Kingdom|United Kingdom', 46, 'Algorithms|Biological Evolution|Computational Biology|Computer Simulation|Databases, Protein|Evolution, Molecular|Humans|Hydrogen Bonding|Models, Molecular|Models, Theoretical|Peptides|Proline|Protein Conformation|Protein Folding|Protein Structure, Secondary|Proteins|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-6-S4-S8', '16351757', 'Secondary structure is used in hierarchical classification of protein structures, identification of protein features, such as helix caps and loops, for fold recognition, and as a precursor to ab initio structure prediction. There are several methods available for assigning secondary structure if the three-dimensional structure of the protein is known. Unfortunately they differ in their definitions, particularly in the exact positions of the termini. Additionally, most existing methods rely on hydrogen bonding, which means that important secondary structural classes, such as isolated beta-strands and poly-proline helices cannot be identified as they do not have characteristic hydrogen-bonding patterns. For this reason we have developed a more accurate method for assigning secondary structure based on main chain geometry, which also allows a more comprehensive assignment of secondary structure.'),
(90648, 2005, 'bmc', 'ParPEST: a pipeline for EST data analysis based on parallel computing', 'DAgostino, Nunzio|Aversano, Mario|Chiusano, Maria Luisa', 'Department of Structural and Functional Biology, University Federico II, 80134 Naples, Italy. nunzio.dagostino@unina.it|Department of Structural and Functional Biology, University Federico II, 80134 Naples, Italy. nunzio.dagostino@unina.it|Department of Structural and Functional Biology, University Federico II, 80134 Naples, Italy. nunzio.dagostino@unina.it', 'Italy|Italy|Italy', 0, 'Algorithms|Base Sequence|Biotechnology|Cloning, Molecular|Cluster Analysis|Computational Biology|Computers|DNA, Complementary|Databases, Factual|Databases, Genetic|Electronic Data Processing|Expressed Sequence Tags|Gene Library|Genome, Human|Humans|Internet|Programming Languages|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-6-S4-S9', '16351758', 'Expressed Sequence Tags (ESTs) are short and error-prone DNA sequences generated from the 5 and 3 ends of randomly selected cDNA clones. They provide an important resource for comparative and functional genomic studies and, moreover, represent a reliable information for the annotation of genomic sequences. Because of the advances in biotechnologies, ESTs are daily determined in the form of large datasets. Therefore, suitable and efficient bioinformatic approaches are necessary to organize data related information content for further investigations.'),
(90649, 2005, 'bmc', 'Probabilistic annotation of protein sequences based on functional classifications', 'Levy, Emmanuel D|Ouzounis, Christos A|Gilks, Walter R|Audit, Benjamin', 'Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. elevy@mrc-lmb.cam.ac.uk|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. elevy@mrc-lmb.cam.ac.uk|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. elevy@mrc-lmb.cam.ac.uk|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. elevy@mrc-lmb.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Conserved Sequence|Documentation|Enzymes|Evolution, Molecular|Models, Biological|Models, Chemical|Models, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Evaluation Studies', '10.1186/1471-2105-6-302', '16354297', 'One of the most evident achievements of bioinformatics is the development of methods that transfer biological knowledge from characterised proteins to uncharacterised sequences. This mode of protein function assignment is mostly based on the detection of sequence similarity and the premise that functional properties are conserved during evolution. Most automatic approaches developed to date rely on the identification of clusters of homologous proteins and the mapping of new proteins onto these clusters, which are expected to share functional characteristics.'),
(90650, 2005, 'bmc', 'A decoy set for the thermostable subdomain from chicken villin headpiece, comparison of different free energy estimators', 'Fogolari, Federico|Tosatto, Silvio C E|Colombo, Giorgio', 'Dipartimento di Scienze e Tecnologie Biomediche, Università di Udine, P,le Kolbe 4, 33100 Udine, Italy. ffogolari@mail.dstb.uniud.it|Dipartimento di Scienze e Tecnologie Biomediche, Università di Udine, P,le Kolbe 4, 33100 Udine, Italy. ffogolari@mail.dstb.uniud.it|Dipartimento di Scienze e Tecnologie Biomediche, Università di Udine, P,le Kolbe 4, 33100 Udine, Italy. ffogolari@mail.dstb.uniud.it', 'Italy|Italy|Italy', 15, 'Animals|Chickens|Computational Biology|Computer Simulation|Databases, Protein|Entropy|Fluorescence Resonance Energy Transfer|Hot Temperature|Hydrogen Bonding|Microfilament Proteins|Models, Molecular|Models, Statistical|Molecular Conformation|Molecular Structure|Poisson Distribution|Protein Conformation|Protein Denaturation|Protein Folding|Proteins|Thermodynamics', 'Journal Article', '10.1186/1471-2105-6-301', '16354298', 'Estimators of free energies are routinely used to judge the quality of protein structural models. As these estimators still present inaccuracies, they are frequently evaluated by discriminating native or native-like conformations from large ensembles of so-called decoy structures.'),
(90651, 2005, 'bmc', 'Analysis of concordance of different haplotype block partitioning algorithms', 'Indap, Amit R|Marth, Gabor T|Struble, Craig A|Tonellato, Peter|Olivier, Michael', 'Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, USA. aindap@yahoo.com|Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, USA. aindap@yahoo.com|Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, USA. aindap@yahoo.com|Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, USA. aindap@yahoo.com|Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, USA. aindap@yahoo.com', 'United States|United States|United States|United States|United States', 0, 'African Continental Ancestry Group|Algorithms|Alleles|Asian Continental Ancestry Group|Chromosome Mapping|Computational Biology|Computer Simulation|European Continental Ancestry Group|Gene Frequency|Genetic Markers|Genetics, Population|Genome, Human|Haplotypes|Humans|Models, Genetic|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-6-303', '16356172', 'Different classes of haplotype block algorithms exist and the ideal dataset to assess their performance would be to comprehensively re-sequence a large genomic region in a large population. Such data sets are expensive to collect. Alternatively, we performed coalescent simulations to generate haplotypes with a high marker density and compared block partitioning results from diversity based, LD based, and information theoretic algorithms under different values of SNP density and allele frequency.'),
(90652, 2005, 'bmc', 'Internet-based Profiler system as integrative framework to support translational research', 'Kim, Robert|Demichelis, Francesca|Tang, Jeffery|Riva, Alberto|Shen, Ronglai|Gibbs, Doug F|Mahavishno, Vasudeva|Chinnaiyan, Arul M|Rubin, Mark A', 'Department of Pathology, Brigham and Womens Hospital, Boston, USA. rkim7@partners.org|Department of Pathology, Brigham and Womens Hospital, Boston, USA. rkim7@partners.org|Department of Pathology, Brigham and Womens Hospital, Boston, USA. rkim7@partners.org|Department of Pathology, Brigham and Womens Hospital, Boston, USA. rkim7@partners.org|Department of Pathology, Brigham and Womens Hospital, Boston, USA. rkim7@partners.org|Department of Pathology, Brigham and Womens Hospital, Boston, USA. rkim7@partners.org|Department of Pathology, Brigham and Womens Hospital, Boston, USA. rkim7@partners.org|Department of Pathology, Brigham and Womens Hospital, Boston, USA. rkim7@partners.org|Department of Pathology, Brigham and Womens Hospital, Boston, USA. rkim7@partners.org', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 9, 'Automation|Biomarkers|Biomarkers, Tumor|Computational Biology|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Humans|Image Processing, Computer-Assisted|Internet|Neoplasms|Oligonucleotide Array Sequence Analysis|Programming Languages|Software|Software Design', 'Journal Article', '10.1186/1471-2105-6-304', '16364175', 'Translational research requires taking basic science observations and developing them into clinically useful tests and therapeutics. We have developed a process to develop molecular biomarkers for diagnosis and prognosis by integrating tissue microarray (TMA) technology and an internet-database tool, Profiler. TMA technology allows investigators to study hundreds of patient samples on a single glass slide resulting in the conservation of tissue and the reduction in inter-experimental variability. The Profiler system allows investigator to reliably track, store, and evaluate TMA experiments. Here within we describe the process that has evolved through an empirical basis over the past 5 years at two academic institutions.'),
(90653, 2005, 'bmc', 'The Gene Set Builder: collation, curation, and distribution of sets of genes', 'Yusuf, Dimas|Lim, Jonathan S|Wasserman, Wyeth W', 'Centre for Molecular Medicine and Therapeutics (CMMT), Child & Family Research Institute, Vancouver, Canada. dyusuf@cmmt.ubc.ca|Centre for Molecular Medicine and Therapeutics (CMMT), Child & Family Research Institute, Vancouver, Canada. dyusuf@cmmt.ubc.ca|Centre for Molecular Medicine and Therapeutics (CMMT), Child & Family Research Institute, Vancouver, Canada. dyusuf@cmmt.ubc.ca', 'Canada|Canada|Canada', 2, 'Computational Biology|Database Management Systems|Databases, Factual|Databases, Genetic|Gene Expression Regulation|Genes, Fungal|Genome|Genomics|Humans|Internet|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-305', '16371163', 'In bioinformatics and genomics, there are many applications designed to investigate the common properties for a set of genes. Often, these multi-gene analysis tools attempt to reveal sequential, functional, and expressional ties. However, while tremendous effort has been invested in developing tools that can analyze a set of genes, minimal effort has been invested in developing tools that can help researchers compile, store, and annotate gene sets in the first place. As a result, the process of making or accessing a set often involves tedious and time consuming steps such as finding identifiers for each individual gene. These steps are often repeated extensively to shift from one identifier type to another, or to recreate a published set. In this paper, we present a simple online tool which - with the help of the gene catalogs Ensembl and GeneLynx - can help researchers build and annotate sets of genes quickly and easily.'),
(90654, 2005, 'bmc', 'WebArray: an online platform for microarray data analysis', 'Xia, Xiaoqin|McClelland, Michael|Wang, Yipeng', 'Genomic Core Facility, Sidney Kimmel Cancer Center, San Diego, CA 92121, USA. xxia@skcc.org|Genomic Core Facility, Sidney Kimmel Cancer Center, San Diego, CA 92121, USA. xxia@skcc.org|Genomic Core Facility, Sidney Kimmel Cancer Center, San Diego, CA 92121, USA. xxia@skcc.org', 'United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Chromosome Mapping|Computational Biology|Computer Graphics|Data Interpretation, Statistical|Gene Expression Profiling|Genome|Genomics|Internet|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-6-306', '16371165', 'Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments.'),
(90655, 2005, 'bmc', 'Avoiding inconsistencies over time and tracking difficulties in Applied Biosystems AB1700/Panther probe-to-gene annotations', 'Noth, Sebastian|Benecke, Arndt|Systems Epigenomics Group', 'Institut des Hautes Etudes Scientifiques, CNRS/INSERM, 35, route de Chartres, 91440 Bures sur Yvette, France. noth@ihes.fr|Institut des Hautes Etudes Scientifiques, CNRS/INSERM, 35, route de Chartres, 91440 Bures sur Yvette, France. noth@ihes.fr|Institut des Hautes Etudes Scientifiques, CNRS/INSERM, 35, route de Chartres, 91440 Bures sur Yvette, France. noth@ihes.fr', 'France|France|France', 0, 'Algorithms|Base Sequence|DNA Probes|Databases, Genetic|Equipment Design|Equipment Failure Analysis|Gene Expression Profiling|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Time Factors|Transcription Factors', 'Comparative Study', '10.1186/1471-2105-6-307', '16372901', 'Significant inconsistencies between probe-to-gene annotations between different releases of probe set identifiers by commercial microarray platform solutions have been reported. Such inconsistencies lead to misleading or ambiguous interpretation of published gene expression results.'),
(90656, 2005, 'bmc', 'Evolutionary programming as a platform for in silico metabolic engineering', 'Patil, Kiran Raosaheb|Rocha, Isabel|Förster, Jochen|Nielsen, Jens', 'Center for Microbial Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark. krp@biocentrum.dtu.dk|Center for Microbial Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark. krp@biocentrum.dtu.dk|Center for Microbial Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark. krp@biocentrum.dtu.dk|Center for Microbial Biotechnology, BioCentrum-DTU, Building 223, Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark. krp@biocentrum.dtu.dk', 'Denmark|Denmark|Denmark|Denmark', 0, 'Algorithms|Benzaldehydes|Computational Biology|Computer Simulation|Escherichia coli|Evolution, Molecular|Gene Expression Regulation|Genetic Engineering|Genome, Fungal|Glycerol|Models, Biological|Models, Genetic|Phenotype|Protein Engineering|Protein Interaction Mapping|Saccharomyces cerevisiae|Software|Succinic Acid', 'Journal Article', '10.1186/1471-2105-6-308', '16375763', 'Through genetic engineering it is possible to introduce targeted genetic changes and hereby engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, owing to the complexity of metabolic networks, both in terms of structure and regulation, it is often difficult to predict the effects of genetic modifications on the resulting phenotype. Recently genome-scale metabolic models have been compiled for several different microorganisms where structural and stoichiometric complexity is inherently accounted for. New algorithms are being developed by using genome-scale metabolic models that enable identification of gene knockout strategies for obtaining improved phenotypes. However, the problem of finding optimal gene deletion strategy is combinatorial and consequently the computational time increases exponentially with the size of the problem, and it is therefore interesting to develop new faster algorithms.'),
(90657, 2005, 'bmc', 'Comparison of normalization methods for CodeLink Bioarray data', 'Wu, Wei|Dave, Nilesh|Tseng, George C|Richards, Thomas|Xing, Eric P|Kaminski, Naftali', 'Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA. wuw2@upmc.edu|Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA. wuw2@upmc.edu|Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA. wuw2@upmc.edu|Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA. wuw2@upmc.edu|Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA. wuw2@upmc.edu|Dorothy P. and Richard P. Simmons Center for Interstitial Lung Disease, Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA. wuw2@upmc.edu', 'United States|United States|United States|United States|United States|United States', 52, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reference Standards|Software|Software Validation', 'Comparative Study', '10.1186/1471-2105-6-309', '16381608', 'The quality of microarray data can seriously affect the accuracy of downstream analyses. In order to reduce variability and enhance signal reproducibility in these data, many normalization methods have been proposed and evaluated, most of which are for data obtained from cDNA microarrays and Affymetrix GeneChips. CodeLink Bioarrays are a newly emerged, single-color oligonucleotide microarray platform. To date, there are no reported studies that evaluate normalization methods for CodeLink Bioarrays.'),
(90658, 2005, 'bmc', 'Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine', 'Xue, Chenghai|Li, Fei|He, Tao|Liu, Guo-Ping|Li, Yanda|Zhang, Xuegong', 'Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China. chenghai.xue@mail.ia.ac.cn|Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China. chenghai.xue@mail.ia.ac.cn|Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China. chenghai.xue@mail.ia.ac.cn|Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China. chenghai.xue@mail.ia.ac.cn|Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China. chenghai.xue@mail.ia.ac.cn|Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, China. chenghai.xue@mail.ia.ac.cn', 'China|China|China|China|China|China', 0, 'Animals|Base Sequence|Computational Biology|Computer Simulation|False Positive Reactions|Genome|Genomics|Humans|MicroRNAs|Models, Statistical|Molecular Sequence Data|Nucleic Acid Conformation|RNA, Messenger|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-6-310', '16381612', 'MicroRNAs (miRNAs) are a group of short (approximately 22 nt) non-coding RNAs that play important regulatory roles. MiRNA precursors (pre-miRNAs) are characterized by their hairpin structures. However, a large amount of similar hairpins can be folded in many genomes. Almost all current methods for computational prediction of miRNAs use comparative genomic approaches to identify putative pre-miRNAs from candidate hairpins. Ab initio method for distinguishing pre-miRNAs from sequence segments with pre-miRNA-like hairpin structures is lacking. Being able to classify real vs. pseudo pre-miRNAs is important both for understanding of the nature of miRNAs and for developing ab initio prediction methods that can discovery new miRNAs without known homology.'),
(90659, 2005, 'bmc', 'Construction and validation of the APOCHIP, a spotted oligo-microarray for the study of beta-cell apoptosis', 'Magnusson, Nils E|Cardozo, Alessandra K|Kruhøffer, Mogens|Eizirik, Decio L|Ørntoft, Torben F|Jensen, Jens L', 'Department of Clinical Biochemistry, Aarhus University Hospital, Denmark. nm@ki.au.dk|Department of Clinical Biochemistry, Aarhus University Hospital, Denmark. nm@ki.au.dk|Department of Clinical Biochemistry, Aarhus University Hospital, Denmark. nm@ki.au.dk|Department of Clinical Biochemistry, Aarhus University Hospital, Denmark. nm@ki.au.dk|Department of Clinical Biochemistry, Aarhus University Hospital, Denmark. nm@ki.au.dk|Department of Clinical Biochemistry, Aarhus University Hospital, Denmark. nm@ki.au.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 12, 'Algorithms|Animals|Apoptosis|Cells, Cultured|Cytokines|Diabetes Mellitus, Type 1|Equipment Design|Equipment Failure Analysis|Gene Expression Profiling|In Situ Hybridization, Fluorescence|Insulin-Secreting Cells|Oligonucleotide Array Sequence Analysis|Rats|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-6-311', '16384535', 'Type 1 diabetes mellitus (T1DM) is a autoimmune disease caused by a long-term negative balance between immune-mediated beta-cell damage and beta-cell repair/regeneration. Following immune-mediated damage the beta-cell fate depends on several genes up- or down-regulated in parallel and/or sequentially. Based on the information obtained by the analysis of several microarray experiments of beta-cells exposed to pro-apoptotic conditions (e.g. double stranded RNA (dsRNA) and cytokines), we have developed a spotted rat oligonucleotide microarray, the APOCHIP, containing 60-mer probes for 574 genes selected for the study of beta-cell apoptosis.'),
(90660, 2006, 'bmc', 'Fast-Find: a novel computational approach to analyzing combinatorial motifs', 'Hamady, Micah|Peden, Erin|Knight, Rob|Singh, Ravinder', 'Department of Computer Science, University of Colorado, Boulder, CO 80309, USA. hamady@colorado.edu|Department of Computer Science, University of Colorado, Boulder, CO 80309, USA. hamady@colorado.edu|Department of Computer Science, University of Colorado, Boulder, CO 80309, USA. hamady@colorado.edu|Department of Computer Science, University of Colorado, Boulder, CO 80309, USA. hamady@colorado.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Motifs|Animals|Binding Sites|Computational Biology|DNA, Complementary|Databases, Genetic|Drosophila|Expressed Sequence Tags|Genome|Internet|Polyadenylation|Protein Binding|RNA|RNA Splicing|RNA, Messenger|RNA-Binding Proteins|Sensitivity and Specificity|Software', 'Journal Article', '10.1186/1471-2105-7-1', '16393334', 'Many vital biological processes, including transcription and splicing, require a combination of short, degenerate sequence patterns, or motifs, adjacent to defined sequence features. Although these motifs occur frequently by chance, they only have biological meaning within a specific context. Identifying transcripts that contain meaningful combinations of patterns is thus an important problem, which existing tools address poorly.'),
(90661, 2006, 'bmc', 'Gene selection and classification of microarray data using random forest', 'Díaz-Uriarte, Ramón|Alvarez de Andrés, Sara', 'Bioinformatics Unit, Biotechnology Programme, Spanish National Cancer Centre (CNIO), Melchor Fernandez Almagro 3, Madrid, 28029, Spain. rdiaz@ligarto.org|Bioinformatics Unit, Biotechnology Programme, Spanish National Cancer Centre (CNIO), Melchor Fernandez Almagro 3, Madrid, 28029, Spain. rdiaz@ligarto.org', 'Spain|Spain', 1552, 'Algorithms|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Evaluation Studies', '10.1186/1471-2105-7-3', '16398926', 'Selection of relevant genes for sample classification is a common task in most gene expression studies, where researchers try to identify the smallest possible set of genes that can still achieve good predictive performance (for instance, for future use with diagnostic purposes in clinical practice). Many gene selection approaches use univariate (gene-by-gene) rankings of gene relevance and arbitrary thresholds to select the number of genes, can only be applied to two-class problems, and use gene selection ranking criteria unrelated to the classification algorithm. In contrast, random forest is a classification algorithm well suited for microarray data: it shows excellent performance even when most predictive variables are noise, can be used when the number of variables is much larger than the number of observations and in problems involving more than two classes, and returns measures of variable importance. Thus, it is important to understand the performance of random forest with microarray data and its possible use for gene selection.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90662, 2006, 'bmc', 'Cluster analysis of networks generated through homology: automatic identification of important protein communities involved in cancer metastasis', 'Jonsson, Pall F|Cavanna, Tamara|Zicha, Daniel|Bates, Paul A', 'Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, 44 Lincolns Inn Fields, London WC2A 3PX, UK. pall.jonsson@cancer.org.uk|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, 44 Lincolns Inn Fields, London WC2A 3PX, UK. pall.jonsson@cancer.org.uk|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, 44 Lincolns Inn Fields, London WC2A 3PX, UK. pall.jonsson@cancer.org.uk|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, 44 Lincolns Inn Fields, London WC2A 3PX, UK. pall.jonsson@cancer.org.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Artificial Intelligence|Biomarkers, Tumor|Cell Line, Tumor|Chromosome Mapping|Cluster Analysis|Diagnosis, Computer-Assisted|Gene Expression Profiling|Neoplasm Proteins|Pattern Recognition, Automated|Protein Interaction Mapping|Rats|Reproducibility of Results|Sarcoma|Sensitivity and Specificity|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Signal Transduction', 'Journal Article', '10.1186/1471-2105-7-2', '16398927', 'Protein-protein interactions have traditionally been studied on a small scale, using classical biochemical methods to investigate the proteins of interest. More recently large-scale methods, such as two-hybrid screens, have been utilised to survey extensive portions of genomes. Current high-throughput approaches have a relatively high rate of errors, whereas in-depth biochemical studies are too expensive and time-consuming to be practical for extensive studies. As a result, there are gaps in our knowledge of many key biological networks, for which computational approaches are particularly suitable.'),
(90663, 2006, 'bmc', 'Application of machine learning in SNP discovery', 'Matukumalli, Lakshmi K|Grefenstette, John J|Hyten, David L|Choi, Ik-Young|Cregan, Perry B|Van Tassell, Curtis P', 'Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, US Department of Agriculture, ARS, Beltsville, MD 20705, USA. lmatukum@gmu.edu|Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, US Department of Agriculture, ARS, Beltsville, MD 20705, USA. lmatukum@gmu.edu|Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, US Department of Agriculture, ARS, Beltsville, MD 20705, USA. lmatukum@gmu.edu|Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, US Department of Agriculture, ARS, Beltsville, MD 20705, USA. lmatukum@gmu.edu|Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, US Department of Agriculture, ARS, Beltsville, MD 20705, USA. lmatukum@gmu.edu|Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, US Department of Agriculture, ARS, Beltsville, MD 20705, USA. lmatukum@gmu.edu', 'United States|United States|United States|United States|United States|United States', 33, 'Algorithms|Artificial Intelligence|Base Sequence|Binding Sites|Computational Biology|Expressed Sequence Tags|Genetic Variation|Genome, Human|Genome, Plant|Haplotypes|Homozygote|Humans|Molecular Sequence Data|Polymorphism, Genetic|Polymorphism, Single Nucleotide|Predictive Value of Tests|Sequence Tagged Sites|Software|Soybeans|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-4', '16398931', 'Single nucleotide polymorphisms (SNP) constitute more than 90% of the genetic variation, and hence can account for most trait differences among individuals in a given species. Polymorphism detection software PolyBayes and PolyPhred give high false positive SNP predictions even with stringent parameter values. We developed a machine learning (ML) method to augment PolyBayes to improve its prediction accuracy. ML methods have also been successfully applied to other bioinformatics problems in predicting genes, promoters, transcription factor binding sites and protein structures.'),
(90664, 2006, 'bmc', 'The comprehensive updated regulatory network of Escherichia coli K-12', 'Salgado, Heladia|Santos-Zavaleta, Alberto|Gama-Castro, Socorro|Peralta-Gil, Martín|Peñaloza-Spínola, Mónica I|Martínez-Antonio, Agustino|Karp, Peter D|Collado-Vides, Julio', 'Bioinformatics Research Group, SRI International, 333 Ravenswood Ave EK207, Menlo Park CA 94025 USA. heladia@ccg.unam.mx|Bioinformatics Research Group, SRI International, 333 Ravenswood Ave EK207, Menlo Park CA 94025 USA. heladia@ccg.unam.mx|Bioinformatics Research Group, SRI International, 333 Ravenswood Ave EK207, Menlo Park CA 94025 USA. heladia@ccg.unam.mx|Bioinformatics Research Group, SRI International, 333 Ravenswood Ave EK207, Menlo Park CA 94025 USA. heladia@ccg.unam.mx|Bioinformatics Research Group, SRI International, 333 Ravenswood Ave EK207, Menlo Park CA 94025 USA. heladia@ccg.unam.mx|Bioinformatics Research Group, SRI International, 333 Ravenswood Ave EK207, Menlo Park CA 94025 USA. heladia@ccg.unam.mx|Bioinformatics Research Group, SRI International, 333 Ravenswood Ave EK207, Menlo Park CA 94025 USA. heladia@ccg.unam.mx|Bioinformatics Research Group, SRI International, 333 Ravenswood Ave EK207, Menlo Park CA 94025 USA. heladia@ccg.unam.mx', 'United States|United States|United States|United States|United States|United States|United States|United States', 45, 'Computer Simulation|Databases, Protein|Escherichia coli K12|Escherichia coli Proteins|Gene Expression Regulation, Bacterial|Models, Biological|Protein Interaction Mapping|Signal Transduction', 'Editorial', '10.1186/1471-2105-7-5', '16398937', 'Escherichia coli is the model organism for which our knowledge of its regulatory network is the most extensive. Over the last few years, our project has been collecting and curating the literature concerning E. coli transcription initiation and operons, providing in both the RegulonDB and EcoCyc databases the largest electronically encoded network available. A paper published recently by Ma et al. (2004) showed several differences in the versions of the network present in these two databases. Discrepancies have been corrected, annotations from this and other groups (Shen-Orr et al., 2002) have been added, making the RegulonDB and EcoCyc databases the largest comprehensive and constantly curated regulatory network of E. coli K-12.'),
(90665, 2006, 'bmc', 'Finding biological process modifications in cancer tissues by mining gene expression correlations', 'Gamberoni, Giacomo|Storari, Sergio|Volinia, Stefano', 'ENDIF-Dipartimento di Ingegneria, Università di Ferrara, Ferrara, Italy. ggamberoni@ing.unife.it|ENDIF-Dipartimento di Ingegneria, Università di Ferrara, Ferrara, Italy. ggamberoni@ing.unife.it|ENDIF-Dipartimento di Ingegneria, Università di Ferrara, Ferrara, Italy. ggamberoni@ing.unife.it', 'Italy|Italy|Italy', 0, 'Carcinoma, Hepatocellular|Computational Biology|Databases, Genetic|Gene Expression|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Liver|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-7-6', '16401337', 'Through the use of DNA microarrays it is now possible to obtain quantitative measurements of the expression of thousands of genes from a biological sample. This technology yields a global view of gene expression that can be used in several ways. Functional insight into expression profiles is routinely obtained by using Gene Ontology terms associated to the cellular genes. In this paper, we deal with functional data mining from expression profiles, proposing a novel approach that studies the correlations between genes and their relations to Gene Ontology (GO). By using this functional correlations comparison we explore all possible pairs of genes identifying the affected biological processes by analyzing in a pair-wise manner gene expression patterns and linking correlated pairs with Gene Ontology terms.'),
(90666, 2006, 'bmc', 'Approximation properties of haplotype tagging', 'Vinterbo, Staal A|Dreiseitl, Stephan|Ohno-Machado, Lucila', 'Decision Systems Group, Brigham and Womens Hospital, Boston, MA 02115, USA. staal@dsg.harvard.edu|Decision Systems Group, Brigham and Womens Hospital, Boston, MA 02115, USA. staal@dsg.harvard.edu|Decision Systems Group, Brigham and Womens Hospital, Boston, MA 02115, USA. staal@dsg.harvard.edu', 'United States|United States|United States', 2, 'Algorithms|Animals|Chromosome Mapping|Computational Biology|Genome, Human|Haplotypes|Humans|Models, Genetic|Models, Statistical|Models, Theoretical|Polymorphism, Single Nucleotide|Reproducibility of Results|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-7-8', '16401341', 'Single nucleotide polymorphisms (SNPs) are locations at which the genomic sequences of population members differ. Since these differences are known to follow patterns, disease association studies are facilitated by identifying SNPs that allow the unique identification of such patterns. This process, known as haplotype tagging, is formulated as a combinatorial optimization problem and analyzed in terms of complexity and approximation properties.'),
(90667, 2006, 'bmc', 'OligoSpawn: a software tool for the design of overgo probes from large unigene datasets', 'Zheng, Jie|Svensson, Jan T|Madishetty, Kavitha|Close, Timothy J|Jiang, Tao|Lonardi, Stefano', 'Department of Computer Science & Engineering, University of California, Riverside, CA 92521, USA. zjie@cs.ucr.edu|Department of Computer Science & Engineering, University of California, Riverside, CA 92521, USA. zjie@cs.ucr.edu|Department of Computer Science & Engineering, University of California, Riverside, CA 92521, USA. zjie@cs.ucr.edu|Department of Computer Science & Engineering, University of California, Riverside, CA 92521, USA. zjie@cs.ucr.edu|Department of Computer Science & Engineering, University of California, Riverside, CA 92521, USA. zjie@cs.ucr.edu|Department of Computer Science & Engineering, University of California, Riverside, CA 92521, USA. zjie@cs.ucr.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Base Sequence|Databases, Genetic|Equipment Design|Equipment Failure Analysis|Expressed Sequence Tags|Information Storage and Retrieval|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Sequence Alignment|Sequence Analysis, DNA|Software|Software Validation', 'Evaluation Studies', '10.1186/1471-2105-7-7', '16401345', 'Expressed sequence tag (EST) datasets represent perhaps the largest collection of genetic information. ESTs can be exploited in a variety of biological experiments and analysis. Here we are interested in the design of overlapping oligonucleotide (overgo) probes from large unigene (EST-contigs) datasets.'),
(90668, 2006, 'bmc', 'ZCURVE_V: a new self-training system for recognizing protein-coding genes in viral and phage genomes', 'Guo, Feng-Biao|Zhang, Chun-Ting', 'Department of Physics, Tianjin University, Tianjin 300072, China. guofengbiao@eyou.com|Department of Physics, Tianjin University, Tianjin 300072, China. guofengbiao@eyou.com', 'China|China', 9, 'Algorithms|Bacteriophages|Computational Biology|Data Interpretation, Statistical|Databases, Genetic|False Positive Reactions|Genome|Genome, Bacterial|Genome, Viral|HIV-1|Hepatitis B virus|Models, Statistical|Open Reading Frames|Software', 'Journal Article', '10.1186/1471-2105-7-9', '16401352', 'It necessary to use highly accurate and statistics-based systems for viral and phage genome annotations. The GeneMark systems for gene-finding in virus and phage genomes suffer from some basic drawbacks. This paper puts forward an alternative approach for viral and phage gene-finding to improve the quality of annotations, particularly for newly sequenced genomes.'),
(90669, 2006, 'bmc', 'SuperMimic--fitting peptide mimetics into protein structures', 'Goede, Andrean|Michalsky, Elke|Schmidt, Ulrike|Preissner, Robert', 'Berlin Center for Genome Based Bioinformatics, 3D Data Mining Group, Institute of Biochemistry, Charité, Monbijoustr.2, 10117 Berlin, Germany. andrean.goede@charite.de|Berlin Center for Genome Based Bioinformatics, 3D Data Mining Group, Institute of Biochemistry, Charité, Monbijoustr.2, 10117 Berlin, Germany. andrean.goede@charite.de|Berlin Center for Genome Based Bioinformatics, 3D Data Mining Group, Institute of Biochemistry, Charité, Monbijoustr.2, 10117 Berlin, Germany. andrean.goede@charite.de|Berlin Center for Genome Based Bioinformatics, 3D Data Mining Group, Institute of Biochemistry, Charité, Monbijoustr.2, 10117 Berlin, Germany. andrean.goede@charite.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Biomimetics|Combinatorial Chemistry Techniques|Computational Biology|Drug Design|Internet|Models, Molecular|Molecular Mimicry|Molecular Structure|Peptide Library|Peptides|Protein Conformation|Protein Structure, Secondary|Proteins|Software', 'Journal Article', '10.1186/1471-2105-7-11', '16403211', 'Various experimental techniques yield peptides that are biologically active but have unfavourable pharmacological properties. The design of structurally similar organic compounds, i.e. peptide mimetics, is a challenging field in medicinal chemistry.'),
(90670, 2006, 'bmc', 'A high level interface to SCOP and ASTRAL implemented in python', 'Casbon, James A|Crooks, Gavin E|Saqi, Mansoor A S', 'Bioinformatics, Institute of Cell and Molecular Science, School of Medicine and Dentistry, Queen Mary, University of London, London EC1 6BQ, UK. j.a.casbon@qmul.ac.uk|Bioinformatics, Institute of Cell and Molecular Science, School of Medicine and Dentistry, Queen Mary, University of London, London EC1 6BQ, UK. j.a.casbon@qmul.ac.uk|Bioinformatics, Institute of Cell and Molecular Science, School of Medicine and Dentistry, Queen Mary, University of London, London EC1 6BQ, UK. j.a.casbon@qmul.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 3, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Programming Languages|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-10', '16403221', 'Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP database is a manually curated structural classification which groups together proteins on the basis of structural similarity. The ASTRAL compendium provides non redundant subsets of SCOP domains on the basis of sequence similarity such that no two domains in a given subset share more than a defined degree of sequence similarity. Taken together these two resources provide a ground truth for assessing structural bioinformatics algorithms. We present a small and easy to use API written in python to enable construction of datasets from these resources.'),
(90671, 2006, 'bmc', 'Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip studies', 'Hu, Zihua|Willsky, Gail R', 'Center for Computational Research, Department of Biostatistics, University at Buffalo, Buffalo, NY 14260, USA. zihuahu@ccr.buffalo.edu|Center for Computational Research, Department of Biostatistics, University at Buffalo, Buffalo, NY 14260, USA. zihuahu@ccr.buffalo.edu', 'United States|United States', 0, 'Algorithms|DNA Probes|Data Interpretation, Statistical|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Software|Software Validation', 'Evaluation Studies', '10.1186/1471-2105-7-12', '16403228', 'The choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with known concentration are often used to assess the relative performance of probe set algorithms. Given the fact that the spiked-in cRNAs do not represent endogenously expressed genes in experiments, it becomes increasingly important to have methods to study whether a particular probe set algorithm is more appropriate for a specific dataset, without using such external reference data.'),
(90672, 2006, 'bmc', 'Construction of a nasopharyngeal carcinoma 2D/MS repository with Open Source XML database--Xindice', 'Li, Feng|Li, Maoyu|Xiao, Zhiqiang|Zhang, Pengfei|Li, Jianling|Chen, Zhuchu', 'Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, China. fengl@xysm.net|Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, China. fengl@xysm.net|Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, China. fengl@xysm.net|Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, China. fengl@xysm.net|Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, China. fengl@xysm.net|Key Laboratory of Cancer Proteomics of Chinese Ministry of Health, Xiangya Hospital, Central South University, Changsha, China. fengl@xysm.net', 'China|China|China|China|China|China', 14, 'Carcinoma|Computational Biology|Database Management Systems|Databases, Factual|Databases, Protein|Electrophoresis, Gel, Two-Dimensional|Gene Expression Regulation, Neoplastic|Gene Library|Genome|Humans|Hypermedia|Information Storage and Retrieval|Information Systems|Internet|Mass Spectrometry|Nasopharyngeal Neoplasms|Programming Languages|Proteomics|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-13', '16403238', 'Many proteomics initiatives require integration of all information with uniformcriteria from collection of samples and data display to publication of experimental results. The integration and exchanging of these data of different formats and structure imposes a great challenge to us. The XML technology presents a promise in handling this task due to its simplicity and flexibility. Nasopharyngeal carcinoma (NPC) is one of the most common cancers in southern China and Southeast Asia, which has marked geographic and racial differences in incidence. Although there are some cancer proteome databases now, there is still no NPC proteome database.'),
(90673, 2006, 'bmc', 'An improved procedure for gene selection from microarray experiments using false discovery rate criterion', 'Yang, James J|Yang, Mark C K', 'Biostatistics and Research Epidemiology, Henry Ford Health Sciences Center, Detroit, Michigan, USA. jyang2@hfhs.org|Biostatistics and Research Epidemiology, Henry Ford Health Sciences Center, Detroit, Michigan, USA. jyang2@hfhs.org', 'United States|United States', 14, 'Algorithms|Biomarkers, Tumor|False Positive Reactions|Gene Expression Profiling|Humans|Male|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Prostatic Neoplasms|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-7-15', '16405735', 'A large number of genes usually show differential expressions in a microarray experiment with two types of tissues, and the p-values of a proper statistical test are often used to quantify the significance of these differences. The genes with small p-values are then picked as the genes responsible for the differences in the tissue RNA expressions. One key question is what should be the threshold to consider the p-values small. There is always a trade off between this threshold and the rate of false claims. Recent statistical literature shows that the false discovery rate (FDR) criterion is a powerful and reasonable criterion to pick those genes with differential expression. Moreover, the power of detection can be increased by knowing the number of non-differential expression genes. While this number is unknown in practice, there are methods to estimate it from data. The purpose of this paper is to present a new method of estimating this number and use it for the FDR procedure construction.'),
(90674, 2006, 'bmc', 'Local protein structure prediction using discriminative models', 'Sander, Oliver|Sommer, Ingolf|Lengauer, Thomas', 'Max-Planck-Institute for Informatics, Department of Computational Biology and Applied Algorithmics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. osander@mpi-sb.mpg.de|Max-Planck-Institute for Informatics, Department of Computational Biology and Applied Algorithmics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. osander@mpi-sb.mpg.de|Max-Planck-Institute for Informatics, Department of Computational Biology and Applied Algorithmics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. osander@mpi-sb.mpg.de', 'Germany|Germany|Germany', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Discriminant Analysis|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-7-14', '16405736', 'In recent years protein structure prediction methods using local structure information have shown promising improvements. The quality of new fold predictions has risen significantly and in fold recognition incorporation of local structure predictions led to improvements in the accuracy of results. We developed a local structure prediction method to be integrated into either fold recognition or new fold prediction methods. For each local sequence window of a protein sequence the method predicts probability estimates for the sequence to attain particular local structures from a set of predefined local structure candidates. The first step is to define a set of local structure representatives based on clustering recurrent local structures. In the second step a discriminative model is trained to predict the local structure representative given local sequence information.'),
(90675, 2006, 'bmc', 'Automatic discovery of cross-family sequence features associated with protein function', 'Brameier, Markus|Haan, Josien|Krings, Andrea|MacCallum, Robert M', 'Stockholm Bioinformatics Center, Stockholm University, 106 91 Stockholm, Sweden. brameier@birc.au.dk|Stockholm Bioinformatics Center, Stockholm University, 106 91 Stockholm, Sweden. brameier@birc.au.dk|Stockholm Bioinformatics Center, Stockholm University, 106 91 Stockholm, Sweden. brameier@birc.au.dk|Stockholm Bioinformatics Center, Stockholm University, 106 91 Stockholm, Sweden. brameier@birc.au.dk', 'Sweden|Sweden|Sweden|Sweden', 7, 'Algorithms|Amino Acid Motifs|Artificial Intelligence|Catalysis|Computational Biology|Databases, Protein|Evolution, Molecular|Genomics|Humans|Models, Statistical|Models, Theoretical|Molecular Sequence Data|Pattern Recognition, Automated|Proteomics|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship|Ubiquitin', 'Journal Article', '10.1186/1471-2105-7-16', '16409628', 'Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterized protein families and in comparative genomics. Until now, this problem has been approached using machine learning techniques that attempt to predict membership, or otherwise, to predefined functional categories or subcellular locations. A potential drawback of this approach is that the human-designated functional classes may not accurately reflect the underlying biology, and consequently important sequence-to-function relationships may be missed.'),
(90676, 2006, 'bmc', 'An approach for clustering gene expression data with error information', 'Tjaden, Brian', 'Computer Science Department, Wellesley College, Wellesley, MA 02481, USA. btjaden@wellesley.edu', 'United States', 25, 'Algorithms|Cluster Analysis|Data Interpretation, Statistical|Escherichia coli|Gene Expression Regulation, Bacterial|Gene Expression Regulation, Fungal|Models, Statistical|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|ROC Curve|Reproducibility of Results|Saccharomyces cerevisiae|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-7-17', '16409635', 'Clustering of gene expression patterns is a well-studied technique for elucidating trends across large numbers of transcripts and for identifying likely co-regulated genes. Even the best clustering methods, however, are unlikely to provide meaningful results if too much of the data is unreliable. With the maturation of microarray technology, a wealth of research on statistical analysis of gene expression data has encouraged researchers to consider error and uncertainty in their microarray experiments, so that experiments are being performed increasingly with repeat spots per gene per chip and with repeat experiments. One of the challenges is to incorporate the measurement error information into downstream analyses of gene expression data, such as traditional clustering techniques.'),
(90677, 2006, 'bmc', 'In silico discovery of human natural antisense transcripts', 'Li, Yuan-Yuan|Qin, Lei|Guo, Zong-Ming|Liu, Lei|Xu, Hao|Hao, Pei|Su, Jiong|Shi, Yixiang|He, Wei-Zhong|Li, Yi-Xue', 'Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org|Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org|Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org|Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org|Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org|Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org|Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org|Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org|Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org|Shanghai Center for Bioinformation Technology, Shanghai 200235, China. yyli@scbit.org', 'China|China|China|China|China|China|China|China|China|China', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Databases, Protein|Humans|Molecular Sequence Data|Proteome|RNA, Antisense|Sequence Alignment|Sequence Analysis, RNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-18', '16409644', 'Several high-throughput searches for potential natural antisense transcripts (NATs) have been performed recently, but most of the reports were focused on cis type. A thorough in silico analysis of human transcripts will help expand our knowledge of NATs.'),
(90678, 2006, 'bmc', 'OpWise: operons aid the identification of differentially expressed genes in bacterial microarray experiments', 'Price, Morgan N|Arkin, Adam P|Alm, Eric J', 'Lawrence Berkeley Lab, Mailstop 977-152, Berkeley, CA 94720, USA. morgannprice@yahoo.com|Lawrence Berkeley Lab, Mailstop 977-152, Berkeley, CA 94720, USA. morgannprice@yahoo.com|Lawrence Berkeley Lab, Mailstop 977-152, Berkeley, CA 94720, USA. morgannprice@yahoo.com', 'United States|United States|United States', 14, 'Algorithms|Bacterial Proteins|Chromosome Mapping|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Operon|Reproducibility of Results|Sensitivity and Specificity|Software', 'Journal Article', '10.1186/1471-2105-7-19', '16412220', 'Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no systematic errors in the data even though several sources of systematic error are known.'),
(90679, 2006, 'bmc', 'Prediction of protein structural class with Rough Sets', 'Cao, Youfang|Liu, Shi|Zhang, Lida|Qin, Jie|Wang, Jiang|Tang, Kexuan', 'Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Institute of Systems Biology, Shanghai Jiao Tong University, Shanghai 200030, China. yfcao@sjtu.edu.cn|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Institute of Systems Biology, Shanghai Jiao Tong University, Shanghai 200030, China. yfcao@sjtu.edu.cn|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Institute of Systems Biology, Shanghai Jiao Tong University, Shanghai 200030, China. yfcao@sjtu.edu.cn|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Institute of Systems Biology, Shanghai Jiao Tong University, Shanghai 200030, China. yfcao@sjtu.edu.cn|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Institute of Systems Biology, Shanghai Jiao Tong University, Shanghai 200030, China. yfcao@sjtu.edu.cn|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Institute of Systems Biology, Shanghai Jiao Tong University, Shanghai 200030, China. yfcao@sjtu.edu.cn', 'China|China|China|China|China|China', 117, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Evaluation Studies', '10.1186/1471-2105-7-20', '16412240', 'A new method for the prediction of protein structural classes is constructed based on Rough Sets algorithm, which is a rule-based data mining method. Amino acid compositions and 8 physicochemical properties data are used as conditional attributes for the construction of decision system. After reducing the decision system, decision rules are generated, which can be used to classify new objects.'),
(90680, 2006, 'bmc', 'Evaluation of methods for oligonucleotide array data via quantitative real-time PCR', 'Qin, Li-Xuan|Beyer, Richard P|Hudson, Francesca N|Linford, Nancy J|Morris, Daryl E|Kerr, Kathleen F', 'Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. qinl@mskcc.org|Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. qinl@mskcc.org|Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. qinl@mskcc.org|Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. qinl@mskcc.org|Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. qinl@mskcc.org|Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. qinl@mskcc.org', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Computational Biology|DNA Primers|DNA Probes|Data Interpretation, Statistical|Evaluation Studies as Topic|Gene Expression|Gene Expression Profiling|Gene Expression Regulation|Mice|Models, Statistical|Oligonucleotide Array Sequence Analysis|Oligonucleotides|Polymerase Chain Reaction|RNA|Reproducibility of Results|Reverse Transcriptase Polymerase Chain Reaction|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-7-23', '16417622', 'There are currently many different methods for processing and summarizing probe-level data from Affymetrix oligonucleotide arrays. It is of great interest to validate these methods and identify those that are most effective. There is no single best way to do this validation, and a variety of approaches is needed. Moreover, gene expression data are collected to answer a variety of scientific questions, and the same method may not be best for all questions. Only a handful of validation studies have been done so far, most of which rely on spike-in datasets and focus on the question of detecting differential expression. Here we seek methods that excel at estimating relative expression. We evaluate methods by identifying those that give the strongest linear association between expression measurements by array and the gold-standard assay. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) is generally considered the gold-standard assay for measuring gene expression by biologists and is often used to confirm findings from microarray data. Here we use qRT-PCR measurements to validate methods for the components of processing oligo array data: background adjustment, normalization, mismatch adjustment, and probeset summary. An advantage of our approach over spike-in studies is that methods are validated on a real dataset that was collected to address a scientific question.'),
(90681, 2006, 'bmc', 'GenoLink: a graph-based querying and browsing system for investigating the function of genes and proteins', 'Durand, Patrick|Labarre, Laurent|Meil, Alain|Divo, Jean-Louis|Vandenbrouck, Yves|Viari, Alain|Wojcik, Jérôme', 'Hybrigenics SA, 3-5 Impasse Reille, 75014 Paris, France. Patrick.Durand@inria.fr|Hybrigenics SA, 3-5 Impasse Reille, 75014 Paris, France. Patrick.Durand@inria.fr|Hybrigenics SA, 3-5 Impasse Reille, 75014 Paris, France. Patrick.Durand@inria.fr|Hybrigenics SA, 3-5 Impasse Reille, 75014 Paris, France. Patrick.Durand@inria.fr|Hybrigenics SA, 3-5 Impasse Reille, 75014 Paris, France. Patrick.Durand@inria.fr|Hybrigenics SA, 3-5 Impasse Reille, 75014 Paris, France. Patrick.Durand@inria.fr|Hybrigenics SA, 3-5 Impasse Reille, 75014 Paris, France. Patrick.Durand@inria.fr', 'France|France|France|France|France|France|France', 17, 'Computer Graphics|Computer Simulation|Database Management Systems|Databases, Genetic|Gene Expression|Genes|Proteins|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-21', '16417636', 'A large variety of biological data can be represented by graphs. These graphs can be constructed from heterogeneous data coming from genomic and post-genomic technologies, but there is still need for tools aiming at exploring and analysing such graphs. This paper describes GenoLink, a software platform for the graphical querying and exploration of graphs.'),
(90682, 2006, 'bmc', 'preAssemble: a tool for automatic sequencer trace data processing', 'Adzhubei, Alexei A|Laerdahl, Jon K|Vlasova, Anna V', 'Norwegian School of Veterinary Science, BasAM-Genetics, PO Box 8146 Dep, NO-0033 Oslo, Norway. a.a.adjoubei@biotek.uio.no|Norwegian School of Veterinary Science, BasAM-Genetics, PO Box 8146 Dep, NO-0033 Oslo, Norway. a.a.adjoubei@biotek.uio.no|Norwegian School of Veterinary Science, BasAM-Genetics, PO Box 8146 Dep, NO-0033 Oslo, Norway. a.a.adjoubei@biotek.uio.no', 'Norway|Norway|Norway', 8, 'Algorithms|Animals|Automation|Chromatography|Cluster Analysis|Computational Biology|Computer Graphics|DNA|Data Interpretation, Statistical|Database Management Systems|Electronic Data Processing|Genome|Salmon|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-7-22', '16417643', 'Trace or chromatogram files (raw data) are produced by automatic nucleic acid sequencing equipment or sequencers. Each file contains information which can be interpreted by specialised software to reveal the sequence (base calling). This is done by the sequencer proprietary software or publicly available programs. Depending on the size of a sequencing project the number of trace files can vary from just a few to thousands of files. Sequencing quality assessment on various criteria is important at the stage preceding clustering and contig assembly. Two major publicly available packages--Phred and Staden are used by preAssemble to perform sequence quality processing.'),
(90683, 2006, 'bmc', 'Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan', 'Ting, Jason C|Ye, Ying|Thomas, George H|Ruczinski, Ingo|Pevsner, Jonathan', 'Department of Neurology, Kennedy Krieger Institute, Baltimore, Maryland 21205, USA. ting@kennedykrieger.org|Department of Neurology, Kennedy Krieger Institute, Baltimore, Maryland 21205, USA. ting@kennedykrieger.org|Department of Neurology, Kennedy Krieger Institute, Baltimore, Maryland 21205, USA. ting@kennedykrieger.org|Department of Neurology, Kennedy Krieger Institute, Baltimore, Maryland 21205, USA. ting@kennedykrieger.org|Department of Neurology, Kennedy Krieger Institute, Baltimore, Maryland 21205, USA. ting@kennedykrieger.org', 'United States|United States|United States|United States|United States', 31, 'Base Sequence|Chromosome Aberrations|Chromosome Disorders|Chromosome Mapping|Computer Graphics|DNA Mutational Analysis|Databases, Genetic|Humans|Molecular Sequence Data|Polymorphism, Single Nucleotide|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-25', '16420694', 'A variety of diseases are caused by chromosomal abnormalities such as aneuploidies (having an abnormal number of chromosomes), microdeletions, microduplications, and uniparental disomy. High density single nucleotide polymorphism (SNP) microarrays provide information on chromosomal copy number changes, as well as genotype (heterozygosity and homozygosity). SNP array studies generate multiple types of data for each SNP site, some with more than 100,000 SNPs represented on each array. The identification of different classes of anomalies within SNP data has been challenging.'),
(90684, 2006, 'bmc', 'Metabolic pathways variability and sequence/networks comparisons', 'Tun, Kyaw|Dhar, Pawan K|Palumbo, Maria Concetta|Giuliani, Alessandro', 'Systems Biology Group, Bioinformatics Institute, 30 Biopolis Way, 138671, Singapore. kyawtun@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Way, 138671, Singapore. kyawtun@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Way, 138671, Singapore. kyawtun@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Way, 138671, Singapore. kyawtun@bii.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore', 35, 'Algorithms|Bacterial Physiological Phenomena|Bacterial Proteins|Cell Physiological Phenomena|Computational Biology|Computer Graphics|Computer Simulation|Genome, Bacterial|Genomics|Genotype|Gluconeogenesis|Glycolysis|Models, Biological|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Phenotype|Protein Interaction Mapping|Reproducibility of Results|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-7-24', '16420696', 'In this work a simple method for the computation of relative similarities between homologous metabolic network modules is presented. The method is similar to classical sequence alignment and allows for the generation of phenotypic trees amenable to be compared with correspondent sequence based trees. The procedure can be applied to both single metabolic modules and whole metabolic network data without the need of any specific assumption.'),
(90685, 2006, 'bmc', 'Discovery of Time-Delayed Gene Regulatory Networks based on temporal gene expression profiling', 'Li, Xia|Rao, Shaoqi|Jiang, Wei|Li, Chuanxing|Xiao, Yun|Guo, Zheng|Zhang, Qingpu|Wang, Lihong|Du, Lei|Li, Jing|Li, Li|Zhang, Tianwen|Wang, Qing K', 'Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn|Department of Bioinformatics, Harbin Medical University, Harbin 150086, PR China. lixia@ems.hrbmu.edu.cn', 'China|China|China|China|China|China|China|China|China|China|China|China|China', 59, 'Algorithms|Cell Physiological Phenomena|Computer Simulation|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software|Time Factors|Transcription Factors', 'Evaluation Studies', '10.1186/1471-2105-7-26', '16420705', 'It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks.'),
(90686, 2006, 'bmc', 'WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data', 'Yi, Ming|Horton, Jay D|Cohen, Jonathan C|Hobbs, Helen H|Stephens, Robert M', 'Advanced Biomedical Computing Center, National Cancer Institute-Frederick/SAIC-Frederick Inc., Frederick, MD 21702, USA. myi@ncifcrf.gov|Advanced Biomedical Computing Center, National Cancer Institute-Frederick/SAIC-Frederick Inc., Frederick, MD 21702, USA. myi@ncifcrf.gov|Advanced Biomedical Computing Center, National Cancer Institute-Frederick/SAIC-Frederick Inc., Frederick, MD 21702, USA. myi@ncifcrf.gov|Advanced Biomedical Computing Center, National Cancer Institute-Frederick/SAIC-Frederick Inc., Frederick, MD 21702, USA. myi@ncifcrf.gov|Advanced Biomedical Computing Center, National Cancer Institute-Frederick/SAIC-Frederick Inc., Frederick, MD 21702, USA. myi@ncifcrf.gov', 'United States|United States|United States|United States|United States', 186, 'Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-30', '16423281', 'Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data.'),
(90687, 2006, 'bmc', 'Similarity-based gene detection: using COGs to find evolutionarily-conserved ORFs', 'Powell, Bradford C|Hutchison, Clyde A', 'Curriculum in Genetics and Molecular Biology, University of North Carolina, Chapel Hill, North Carolina, USA. bradford_powell@unc.edu|Curriculum in Genetics and Molecular Biology, University of North Carolina, Chapel Hill, North Carolina, USA. bradford_powell@unc.edu', 'United States|United States', 5, 'Algorithms|Chromosome Mapping|Conserved Sequence|DNA, Bacterial|Evolution, Molecular|Genetic Variation|Genome, Bacterial|Open Reading Frames|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-7-31', '16423288', 'Experimental verification of gene products has not kept pace with the rapid growth of microbial sequence information. However, existing annotations of gene locations contain sufficient information to screen for probable errors. Furthermore, comparisons among genomes become more informative as more genomes are examined. We studied all open reading frames (ORFs) of at least 30 codons from the genomes of 27 sequenced bacterial strains. We grouped the potential peptide sequences encoded from the ORFs by forming Clusters of Orthologous Groups (COGs). We used this grouping in order to find homologous relationships that would not be distinguishable from noise when using simple BLAST searches. Although COG analysis was initially developed to group annotated genes, we applied it to the task of grouping anonymous DNA sequences that may encode proteins.'),
(90688, 2006, 'bmc', 'NOXclass: prediction of protein-protein interaction types', 'Zhu, Hongbo|Domingues, Francisco S|Sommer, Ingolf|Lengauer, Thomas', 'Max-Planck-lnstitut für Informatik, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. hzhu@mpi-sb.mpg.de|Max-Planck-lnstitut für Informatik, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. hzhu@mpi-sb.mpg.de|Max-Planck-lnstitut für Informatik, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. hzhu@mpi-sb.mpg.de|Max-Planck-lnstitut für Informatik, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. hzhu@mpi-sb.mpg.de', 'Germany|Germany|Germany|Germany', 3, 'Algorithms|Artificial Intelligence|Binding Sites|Computer Simulation|Crystallography|Models, Chemical|Models, Molecular|Online Systems|Pattern Recognition, Automated|Protein Binding|Protein Conformation|Protein Interaction Mapping|Protein Structure, Quaternary|Proteins|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1186/1471-2105-7-27', '16423290', 'Structural models determined by X-ray crystallography play a central role in understanding protein-protein interactions at the molecular level. Interpretation of these models requires the distinction between non-specific crystal packing contacts and biologically relevant interactions. This has been investigated previously and classification approaches have been proposed. However, less attention has been devoted to distinguishing different types of biological interactions. These interactions are classified as obligate and non-obligate according to the effect of the complex formation on the stability of the protomers. So far no automatic classification methods for distinguishing obligate, non-obligate and crystal packing interactions have been made available.'),
(90689, 2006, 'bmc', 'A new pooling strategy for high-throughput screening: the Shifted Transversal Design', 'Thierry-Mieg, Nicolas', 'Laboratoire Logiciels-Systèmes-Réseaux, IMAG Institute, BP53, 38041 Grenoble Cedex 9, France. Nicolas.Thierry-Mieg@imag.fr', 'France', 47, 'Algorithms|Animals|Chromosome Mapping|Computer Simulation|Gene Expression Profiling|Humans|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping', 'Journal Article', '10.1186/1471-2105-7-28', '16423300', 'In binary high-throughput screening projects where the goal is the identification of low-frequency events, beyond the obvious issue of efficiency, false positives and false negatives are a major concern. Pooling constitutes a natural solution: it reduces the number of tests, while providing critical duplication of the individual experiments, thereby correcting for experimental noise. The main difficulty consists in designing the pools in a manner that is both efficient and robust: few pools should be necessary to correct the errors and identify the positives, yet the experiment should not be too vulnerable to biological shakiness. For example, some information should still be obtained even if there are slightly more positives or errors than expected. This is known as the group testing problem, or pooling problem.'),
(90690, 2006, 'bmc', 'Recrafting the neighbor-joining method', 'Mailund, Thomas|Brodal, Gerth S|Fagerberg, Rolf|Pedersen, Christian N S|Phillips, Derek', 'Bioinformatics Research Center, University of Aarhus, Denmark. mailund@birc.dk|Bioinformatics Research Center, University of Aarhus, Denmark. mailund@birc.dk|Bioinformatics Research Center, University of Aarhus, Denmark. mailund@birc.dk|Bioinformatics Research Center, University of Aarhus, Denmark. mailund@birc.dk|Bioinformatics Research Center, University of Aarhus, Denmark. mailund@birc.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark', 28, 'Algorithms|Animals|Cluster Analysis|Computational Biology|Computer Simulation|Evolution, Molecular|Humans|Likelihood Functions|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-7-29', '16423304', 'The neighbor-joining method by Saitou and Nei is a widely used method for constructing phylogenetic trees. The formulation of the method gives rise to a canonical Theta(n3) algorithm upon which all existing implementations are based.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90691, 2006, 'bmc', 'Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding scheme', 'Wang, Xian|Li, Ao|Jiang, Zhaohui|Feng, Huanqing', 'Department of Electronic Science and Technology, University of Science and Technology of China, USTC, Hefei, PR China. xwang36@mail.ustc.edu.cn|Department of Electronic Science and Technology, University of Science and Technology of China, USTC, Hefei, PR China. xwang36@mail.ustc.edu.cn|Department of Electronic Science and Technology, University of Science and Technology of China, USTC, Hefei, PR China. xwang36@mail.ustc.edu.cn|Department of Electronic Science and Technology, University of Science and Technology of China, USTC, Hefei, PR China. xwang36@mail.ustc.edu.cn', 'China|China|China|China', 0, 'Algorithms|Artificial Intelligence|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-7-32', '16426462', 'Gene expression profiling has become a useful biological resource in recent years, and it plays an important role in a broad range of areas in biology. The raw gene expression data, usually in the form of large matrix, may contain missing values. The downstream analysis methods that postulate complete matrix input are thus not applicable. Several methods have been developed to solve this problem, such as K nearest neighbor impute method, Bayesian principal components analysis impute method, etc. In this paper, we introduce a novel imputing approach based on the Support Vector Regression (SVR) method. The proposed approach utilizes an orthogonal coding input scheme, which makes use of multi-missing values in one row of a certain gene expression profile and imputes the missing value into a much higher dimensional space, to obtain better performance.'),
(90692, 2006, 'bmc', 'Djinn Lite: a tool for customised gene transcript modelling, annotation-data enrichment and exploration', 'Teber, Erdahl T|Crawford, Edward|Bolton, Kent B|Van Dyk, Derek|Schofield, Peter R|Kapoor, Vimal|Church, W Bret', 'School of Medical Sciences, University of New South Wales, NSW 2052, Australia. e.teber@pharm.usyd.edu.au|School of Medical Sciences, University of New South Wales, NSW 2052, Australia. e.teber@pharm.usyd.edu.au|School of Medical Sciences, University of New South Wales, NSW 2052, Australia. e.teber@pharm.usyd.edu.au|School of Medical Sciences, University of New South Wales, NSW 2052, Australia. e.teber@pharm.usyd.edu.au|School of Medical Sciences, University of New South Wales, NSW 2052, Australia. e.teber@pharm.usyd.edu.au|School of Medical Sciences, University of New South Wales, NSW 2052, Australia. e.teber@pharm.usyd.edu.au|School of Medical Sciences, University of New South Wales, NSW 2052, Australia. e.teber@pharm.usyd.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Alternative Splicing|Animals|Base Sequence|Computational Biology|Computer Graphics|DNA, Complementary|Data Interpretation, Statistical|Database Management Systems|Databases, Genetic|Databases, Protein|Exons|Genome|Humans|Introns|Molecular Sequence Data|Proteomics|RNA, Messenger|Sequence Analysis, Protein|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-33', '16426464', 'There is an ever increasing rate of data made available on genetic variation, transcriptomes and proteomes. Similarly, a growing variety of bioinformatic programs are becoming available from many diverse sources, designed to identify a myriad of sequence patterns considered to have potential biological importance within inter-genic regions, genes, transcripts, and proteins. However, biologists require easy to use, uncomplicated tools to integrate this information, visualise and print gene annotations. Integrating this information usually requires considerable informatics skills, and comprehensive knowledge of the data format to make full use of this information. Tools are needed to explore gene model variants by allowing users the ability to create alternative transcript models using novel combinations of exons not necessarily represented in current database deposits of mRNA/cDNA sequences.'),
(90693, 2006, 'bmc', 'A proposed metric for assessing the measurement quality of individual microarrays', 'Kim, Kyoungmi|Page, Grier P|Beasley, T Mark|Barnes, Stephen|Scheirer, Katherine E|Allison, David B', 'Department of Biostatistics, University of Alabama, Birmingham, Alabama, USA. kkim@ms.soph.aub.edu|Department of Biostatistics, University of Alabama, Birmingham, Alabama, USA. kkim@ms.soph.aub.edu|Department of Biostatistics, University of Alabama, Birmingham, Alabama, USA. kkim@ms.soph.aub.edu|Department of Biostatistics, University of Alabama, Birmingham, Alabama, USA. kkim@ms.soph.aub.edu|Department of Biostatistics, University of Alabama, Birmingham, Alabama, USA. kkim@ms.soph.aub.edu|Department of Biostatistics, University of Alabama, Birmingham, Alabama, USA. kkim@ms.soph.aub.edu', 'United States|United States|United States|United States|United States|United States', 10, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Equipment Failure Analysis|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Assurance, Health Care|Quality Control|Reference Standards', 'Evaluation Studies', '10.1186/1471-2105-7-35', '16430768', 'High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface.'),
(90694, 2006, 'bmc', 'A domain-oriented approach to the reduction of combinatorial complexity in signal transduction networks', 'Conzelmann, Holger|Saez-Rodriguez, Julio|Sauter, Thomas|Kholodenko, Boris N|Gilles, Ernst D', 'Institute for System Dynamics and Control Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany. Conzelmann@isr.uni-stuttgart.de|Institute for System Dynamics and Control Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany. Conzelmann@isr.uni-stuttgart.de|Institute for System Dynamics and Control Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany. Conzelmann@isr.uni-stuttgart.de|Institute for System Dynamics and Control Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany. Conzelmann@isr.uni-stuttgart.de|Institute for System Dynamics and Control Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany. Conzelmann@isr.uni-stuttgart.de', 'Germany|Germany|Germany|Germany|Germany', 67, 'Binding Sites|Combinatorial Chemistry Techniques|Computer Simulation|Models, Biological|Models, Chemical|Protein Binding|Protein Interaction Mapping|Receptors, Cell Surface|Signal Transduction|Structure-Activity Relationship', 'Evaluation Studies', '10.1186/1471-2105-7-34', '16430778', 'Receptors and scaffold proteins possess a number of distinct domains and bind multiple partners. A common problem in modeling signaling systems arises from a combinatorial explosion of different states generated by feasible molecular species. The number of possible species grows exponentially with the number of different docking sites and can easily reach several millions. Models accounting for this combinatorial variety become impractical for many applications.'),
(90695, 2006, 'bmc', 'CoSMoS: Conserved Sequence Motif Search in the proteome', 'Liu, Xiao I|Korde, Neeraj|Jakob, Ursula|Leichert, Lars I', 'Department of Molecular, Cellular & Developmental Biology, University of Michigan, Ann Arbor, MI 48109-1048, USA. catqliu@umich.edu|Department of Molecular, Cellular & Developmental Biology, University of Michigan, Ann Arbor, MI 48109-1048, USA. catqliu@umich.edu|Department of Molecular, Cellular & Developmental Biology, University of Michigan, Ann Arbor, MI 48109-1048, USA. catqliu@umich.edu|Department of Molecular, Cellular & Developmental Biology, University of Michigan, Ann Arbor, MI 48109-1048, USA. catqliu@umich.edu', 'United States|United States|United States|United States', 0, 'Amino Acid Motifs|Amino Acid Sequence|Base Sequence|Computational Biology|Conserved Sequence|DNA Mutational Analysis|Databases, Protein|Escherichia coli|Escherichia coli Proteins|Evolution, Molecular|Genome, Bacterial|Internet|Molecular Sequence Data|Proteins|Proteome|Proteomics|Sequence Alignment|Sequence Analysis|Sequence Homology, Amino Acid|Software|Thioredoxins|Time Factors', 'Journal Article', '10.1186/1471-2105-7-37', '16433915', 'With the ever-increasing number of gene sequences in the public databases, generating and analyzing multiple sequence alignments becomes increasingly time consuming. Nevertheless it is a task performed on a regular basis by researchers in many labs.'),
(90696, 2006, 'bmc', 'MitoRes: a resource of nuclear-encoded mitochondrial genes and their products in Metazoa', 'Catalano, Domenico|Licciulli, Flavio|Turi, Antonio|Grillo, Giorgio|Saccone, Cecilia|DElia, Domenica', 'Institute of Biomedical Technologies, CNR, Via Amendola 122/D, 70126 Bari, Italy. domenico.catalano@ba.itb.cnr.it|Institute of Biomedical Technologies, CNR, Via Amendola 122/D, 70126 Bari, Italy. domenico.catalano@ba.itb.cnr.it|Institute of Biomedical Technologies, CNR, Via Amendola 122/D, 70126 Bari, Italy. domenico.catalano@ba.itb.cnr.it|Institute of Biomedical Technologies, CNR, Via Amendola 122/D, 70126 Bari, Italy. domenico.catalano@ba.itb.cnr.it|Institute of Biomedical Technologies, CNR, Via Amendola 122/D, 70126 Bari, Italy. domenico.catalano@ba.itb.cnr.it|Institute of Biomedical Technologies, CNR, Via Amendola 122/D, 70126 Bari, Italy. domenico.catalano@ba.itb.cnr.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 22, 'Animals|Anopheles|Cell Nucleus|Chromosome Mapping|Cluster Analysis|Computational Biology|DNA, Mitochondrial|Databases, Factual|Databases, Genetic|Databases, Nucleic Acid|Databases, Protein|Drosophila|Drosophila melanogaster|Evolution, Molecular|Exons|Genome|Internet|Introns|Mitochondria|Mitochondrial Proteins|Models, Biological|Protein Sorting Signals|Sequence Analysis, DNA', 'Comparative Study', '10.1186/1471-2105-7-36', '16433928', 'Mitochondria are sub-cellular organelles that have a central role in energy production and in other metabolic pathways of all eukaryotic respiring cells. In the last few years, with more and more genomes being sequenced, a huge amount of data has been generated providing an unprecedented opportunity to use the comparative analysis approach in studies of evolution and functional genomics with the aim of shedding light on molecular mechanisms regulating mitochondrial biogenesis and metabolism. In this context, the problem of the optimal extraction of representative datasets of genomic and proteomic data assumes a crucial importance. Specialised resources for nuclear-encoded mitochondria-related proteins already exist, however, no mitochondrial database is currently available with the same features of MitoRes, which is an update of the MitoNuc database extensively modified in its structure, data sources and graphical interface. It contains data on nuclear-encoded mitochondria-related products for any metazoan species for which this type of data is available and also provides comprehensive sequence datasets (gene, transcript and protein) as well as useful tools for their extraction and export.'),
(90697, 2006, 'bmc', 'A reinforced merging methodology for mapping unique peptide motifs in members of protein families', 'Chang, Hao-Teng|Pai, Tun-Wen|Fan, Tan-chi|Su, Bo-Han|Wu, Pei-Chih|Tang, Chuan-Yi|Chang, Chun-Tien|Liu, Shi-Hwei|Chang, Margaret Dah-Tsyr', 'Institute of Molecular and Cellular Biology, Department of Life Science, National Tsing Hua University, Hsinchu, 30013, ROC, Taiwan. d898209@life.nthu.edu.tw|Institute of Molecular and Cellular Biology, Department of Life Science, National Tsing Hua University, Hsinchu, 30013, ROC, Taiwan. d898209@life.nthu.edu.tw|Institute of Molecular and Cellular Biology, Department of Life Science, National Tsing Hua University, Hsinchu, 30013, ROC, Taiwan. d898209@life.nthu.edu.tw|Institute of Molecular and Cellular Biology, Department of Life Science, National Tsing Hua University, Hsinchu, 30013, ROC, Taiwan. d898209@life.nthu.edu.tw|Institute of Molecular and Cellular Biology, Department of Life Science, National Tsing Hua University, Hsinchu, 30013, ROC, Taiwan. d898209@life.nthu.edu.tw|Institute of Molecular and Cellular Biology, Department of Life Science, National Tsing Hua University, Hsinchu, 30013, ROC, Taiwan. d898209@life.nthu.edu.tw|Institute of Molecular and Cellular Biology, Department of Life Science, National Tsing Hua University, Hsinchu, 30013, ROC, Taiwan. d898209@life.nthu.edu.tw|Institute of Molecular and Cellular Biology, Department of Life Science, National Tsing Hua University, Hsinchu, 30013, ROC, Taiwan. d898209@life.nthu.edu.tw|Institute of Molecular and Cellular Biology, Department of Life Science, National Tsing Hua University, Hsinchu, 30013, ROC, Taiwan. d898209@life.nthu.edu.tw', '-|-|-|-|-|-|-|-|-', 11, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Conserved Sequence|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Evaluation Studies', '10.1186/1471-2105-7-38', '16433931', 'Members of a protein family often have highly conserved sequences, most of these sequences carry identical biological functions and possess similar three-dimensional (3-D) structures. However, enzymes with high sequence identity may acquire differential functions other than the common catalytic ability. It is probable that each of their variable regions consists of a unique peptide motif (UPM), which selectively interacts with other cellular proteins, rendering additional biological activities. The ability to identify and localize such UPMs is paramount in recognizing the characteristic role of each member of a protein family.'),
(90698, 2006, 'bmc', 'GPNN: power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease', 'Motsinger, Alison A|Lee, Stephen L|Mellick, George|Ritchie, Marylyn D', 'Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN 37232-0700, USA. alison.a.motsinger@vanderbilt.edu|Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN 37232-0700, USA. alison.a.motsinger@vanderbilt.edu|Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN 37232-0700, USA. alison.a.motsinger@vanderbilt.edu|Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN 37232-0700, USA. alison.a.motsinger@vanderbilt.edu', 'United States|United States|United States|United States', 61, 'Algorithms|Chromosome Mapping|Diagnosis, Computer-Assisted|Gene Expression Profiling|Genetic Predisposition to Disease|Genetic Testing|Humans|Multigene Family|Neural Networks (Computer)|Parkinson Disease|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Protein Interaction Mapping', 'Evaluation Studies', '10.1186/1471-2105-7-39', '16436204', 'The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinsons disease.'),
(90699, 2006, 'bmc', 'Protein structure similarity from Principle Component Correlation analysis', 'Zhou, Xiaobo|Chou, James|Wong, Stephen T C', 'Center for Neurodegeneration and Repair, Center for Bioinformatics, Harvard Medical School, Boston, MA 02215, USA. zhou@crystal.harvard.edu|Center for Neurodegeneration and Repair, Center for Bioinformatics, Harvard Medical School, Boston, MA 02215, USA. zhou@crystal.harvard.edu|Center for Neurodegeneration and Repair, Center for Bioinformatics, Harvard Medical School, Boston, MA 02215, USA. zhou@crystal.harvard.edu', 'United States|United States|United States', 16, 'Algorithms|Cluster Analysis|Computer Simulation|Crystallography|Databases, Protein|Models, Chemical|Models, Molecular|Models, Statistical|Pattern Recognition, Automated|Principal Component Analysis|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Statistics as Topic', 'Journal Article', '10.1186/1471-2105-7-40', '16436213', 'Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD) in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical, it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities.'),
(90700, 2006, 'bmc', 'Discovering semantic features in the literature: a foundation for building functional associations', 'Chagoyen, Monica|Carmona-Saez, Pedro|Shatkay, Hagit|Carazo, Jose M|Pascual-Montano, Alberto', 'Biocomputing Unit, Centro Nacional de Biotecnologia-CSIC, Madrid, Spain. monica.chagoyen@cnb.uam.es|Biocomputing Unit, Centro Nacional de Biotecnologia-CSIC, Madrid, Spain. monica.chagoyen@cnb.uam.es|Biocomputing Unit, Centro Nacional de Biotecnologia-CSIC, Madrid, Spain. monica.chagoyen@cnb.uam.es|Biocomputing Unit, Centro Nacional de Biotecnologia-CSIC, Madrid, Spain. monica.chagoyen@cnb.uam.es|Biocomputing Unit, Centro Nacional de Biotecnologia-CSIC, Madrid, Spain. monica.chagoyen@cnb.uam.es', 'Spain|Spain|Spain|Spain|Spain', 0, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Bibliometrics|Databases, Bibliographic|Genes|MEDLINE|Natural Language Processing|Periodicals as Topic|Proteins|Semantics|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-7-41', '16438716', 'Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics, among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental approach, it is necessary to analyze these data in the context of previously known information about the biological entities under study. The literature is a particularly valuable source of information for experiment validation and interpretation. Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research.'),
(90701, 2006, 'bmc', 'SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms', 'Van den Bulcke, Tim|Van Leemput, Koenraad|Naudts, Bart|van Remortel, Piet|Ma, Hongwu|Verschoren, Alain|De Moor, Bart|Marchal, Kathleen', 'ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium. tim.vandenbulcke@esat.kuleuven.be|ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium. tim.vandenbulcke@esat.kuleuven.be|ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium. tim.vandenbulcke@esat.kuleuven.be|ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium. tim.vandenbulcke@esat.kuleuven.be|ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium. tim.vandenbulcke@esat.kuleuven.be|ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium. tim.vandenbulcke@esat.kuleuven.be|ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium. tim.vandenbulcke@esat.kuleuven.be|ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, B-3001 Heverlee, Belgium. tim.vandenbulcke@esat.kuleuven.be', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Algorithms|Artificial Intelligence|Benchmarking|Computer Simulation|Databases, Factual|Gene Expression Regulation|Models, Biological|Signal Transduction|Software|Software Validation|Transcription Factors', 'Evaluation Studies', '10.1186/1471-2105-7-43', '16438721', 'The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validation of these algorithms requires benchmark data sets for which the underlying network is known. Since experimental data sets of the appropriate size and design are usually not available, there is a clear need to generate well-characterized synthetic data sets that allow thorough testing of learning algorithms in a fast and reproducible manner.'),
(90702, 2006, 'bmc', 'MassSorter: a tool for administrating and analyzing data from mass spectrometry experiments on proteins with known amino acid sequences', 'Barsnes, Harald|Mikalsen, Svein-Ole|Eidhammer, Ingvar', 'Department of informatics, University of Bergen, PB. 7800, N-5020 Bergen, Norway. haraldb@ii.uib.no|Department of informatics, University of Bergen, PB. 7800, N-5020 Bergen, Norway. haraldb@ii.uib.no|Department of informatics, University of Bergen, PB. 7800, N-5020 Bergen, Norway. haraldb@ii.uib.no', 'Norway|Norway|Norway', 7, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Mass Spectrometry|Molecular Sequence Data|Peptide Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-42', '16438723', 'Proteomics is the study of the proteome, and is critical to the understanding of cellular processes. Two central and related tasks of proteomics are protein identification and protein characterization. Many small laboratories are interested in the characterization of a small number of proteins, e.g., how posttranslational modifications change under different conditions.'),
(90703, 2006, 'bmc', 'An improved distance measure between the expression profiles linking co-expression and co-regulation in mouse', 'Kim, Ryung S|Ji, Hongkai|Wong, Wing H', 'Department of Neurology, Harvard Medical School, Boston, MA 02115, USA. ryung_kim@dfci.harvard.edu|Department of Neurology, Harvard Medical School, Boston, MA 02115, USA. ryung_kim@dfci.harvard.edu|Department of Neurology, Harvard Medical School, Boston, MA 02115, USA. ryung_kim@dfci.harvard.edu', 'United States|United States|United States', 0, 'Algorithms|Animals|Chromosome Mapping|Gene Expression Regulation|Linkage Disequilibrium|Mice|Multigene Family|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-44', '16438730', 'Many statistical algorithms combine microarray expression data and genome sequence data to identify transcription factor binding motifs in the low eukaryotic genomes. Finding cis-regulatory elements in higher eukaryote genomes, however, remains a challenge, as searching in the promoter regions of genes with similar expression patterns often fails. The difficulty is partially attributable to the poor performance of the similarity measures for comparing expression profiles. The widely accepted measures are inadequate for distinguishing genes transcribed from distinct regulatory mechanisms in the complicated genomes of higher eukaryotes.'),
(90704, 2006, 'bmc', 'Querying the public databases for sequences using complex keywords contained in the feature lines', 'Croce, Olivier|Lamarre, Michaël|Christen, Richard', 'Laboratoire de Biologie Virtuelle, UMR 6543, CNRS & University of Nice Sophia-Antipolis, Centre de Biochimie, Parc Valrose, Nice, F06108, France. croce@unice.fr|Laboratoire de Biologie Virtuelle, UMR 6543, CNRS & University of Nice Sophia-Antipolis, Centre de Biochimie, Parc Valrose, Nice, F06108, France. croce@unice.fr|Laboratoire de Biologie Virtuelle, UMR 6543, CNRS & University of Nice Sophia-Antipolis, Centre de Biochimie, Parc Valrose, Nice, F06108, France. croce@unice.fr', 'France|France|France', 6, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Natural Language Processing|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Vocabulary, Controlled', 'Comparative Study', '10.1186/1471-2105-7-45', '16441875', 'High throughput technologies often require the retrieval of large data sets of sequences. Retrieval of EMBL or GenBank entries using keywords is easy using tools such as ACNUC, Entrez or SRS, but has some limitations, in particular when querying with complex keywords.'),
(90705, 2006, 'bmc', 'Rapid and asymmetric divergence of duplicate genes in the human gene coexpression network', 'Chung, Wen-Yu|Albert, Reka|Albert, Istvan|Nekrutenko, Anton|Makova, Kateryna D', 'Department of Biology, Penn State University, University Park, PA 16802, USA. wuc114@psu.edu|Department of Biology, Penn State University, University Park, PA 16802, USA. wuc114@psu.edu|Department of Biology, Penn State University, University Park, PA 16802, USA. wuc114@psu.edu|Department of Biology, Penn State University, University Park, PA 16802, USA. wuc114@psu.edu|Department of Biology, Penn State University, University Park, PA 16802, USA. wuc114@psu.edu', 'United States|United States|United States|United States|United States', 38, 'Chromosome Mapping|Evolution, Molecular|Gene Expression Regulation|Genes, Duplicate|Genetic Variation|Genome, Human|Humans|Models, Genetic|Multigene Family|Signal Transduction|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-46', '16441884', 'While gene duplication is known to be one of the most common mechanisms of genome evolution, the fates of genes after duplication are still being debated. In particular, it is presently unknown whether most duplicate genes preserve (or subdivide) the functions of the parental gene or acquire new functions. One aspect of gene function, that is the expression profile in gene coexpression network, has been largely unexplored for duplicate genes.'),
(90706, 2006, 'bmc', 'Protein kinases associated with the yeast phosphoproteome', 'Brinkworth, Ross I|Munn, Alan L|Kobe, Bostjan', 'School of Molecular and Microbial Sciences, University of Queensland, Brisbane 4072, Australia. r.brinkworth1@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, Brisbane 4072, Australia. r.brinkworth1@uq.edu.au|School of Molecular and Microbial Sciences, University of Queensland, Brisbane 4072, Australia. r.brinkworth1@uq.edu.au', 'Australia|Australia|Australia', 0, 'Amino Acid Sequence|Fungal Proteins|Molecular Sequence Data|Phosphoproteins|Phosphorylation|Protein Interaction Mapping|Protein Kinases|Proteome|Saccharomyces cerevisiae|Sequence Alignment|Sequence Analysis, Protein|Substrate Specificity', 'Journal Article', '10.1186/1471-2105-7-47', '16445868', 'Protein phosphorylation is an extremely important mechanism of cellular regulation. A large-scale study of phosphoproteins in a whole-cell lysate of Saccharomyces cerevisiae has previously identified 383 phosphorylation sites in 216 peptide sequences. However, the protein kinases responsible for the phosphorylation of the identified proteins have not previously been assigned.'),
(90707, 2006, 'bmc', 'On single and multiple models of protein families for the detection of remote sequence relationships', 'Casbon, James A|Saqi, Mansoor A S', 'Bioinformatics Group, Institute of Cell and Molecular Science, The Genome Centre, Queen Marys School of Medicine and Dentistry, Charterhouse Square, London, EC1M 6BQ, UK. j.a.casbon@qmul.ac.uk|Bioinformatics Group, Institute of Cell and Molecular Science, The Genome Centre, Queen Marys School of Medicine and Dentistry, Charterhouse Square, London, EC1M 6BQ, UK. j.a.casbon@qmul.ac.uk', 'United Kingdom|United Kingdom', 0, 'Amino Acid Sequence|Gene Expression Profiling|Markov Chains|Models, Chemical|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-7-48', '16448555', 'The detection of relationships between a protein sequence of unknown function and a sequence whose function has been characterised enables the transfer of functional annotation. However in many cases these relationships can not be identified easily from direct comparison of the two sequences. Methods which compare sequence profiles have been shown to improve the detection of these remote sequence relationships. However, the best method for building a profile of a known set of sequences has not been established. Here we examine how the type of profile built affects its performance, both in detecting remote homologs and in the resulting alignment accuracy. In particular, we consider whether it is better to model a protein superfamily using a single structure-based alignment that is representative of all known cases of the superfamily, or to use multiple sequence-based profiles each representing an individual member of the superfamily.'),
(90708, 2006, 'bmc', 'Effects of filtering by Present call on analysis of microarray experiments', 'McClintick, Jeanette N|Edenberg, Howard J', 'Department of Medical and Molecular Genetics, Indiana University, Indianapolis, Indiana, USA. jnmcclin@iupui.edu|Department of Medical and Molecular Genetics, Indiana University, Indianapolis, Indiana, USA. jnmcclin@iupui.edu', 'India|India', 181, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Signal Processing, Computer-Assisted|Software', 'Evaluation Studies', '10.1186/1471-2105-7-49', '16448562', 'Affymetrix GeneChips are widely used for expression profiling of tens of thousands of genes. The large number of comparisons can lead to false positives. Various methods have been used to reduce false positives, but they have rarely been compared or quantitatively evaluated. Here we describe and evaluate a simple method that uses the detection (Present/Absent) call generated by the Affymetrix microarray suite version 5 software (MAS5) to remove data that is not reliably detected before further analysis, and compare this with filtering by expression level. We explore the effects of various thresholds for removing data in experiments of different size (from 3 to 10 arrays per treatment), as well as their relative power to detect significant differences in expression.'),
(90709, 2006, 'bmc', 'Assessing stability of gene selection in microarray data analysis', 'Qiu, Xing|Xiao, Yuanhui|Gordon, Alexander|Yakovlev, Andrei', 'Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. xqiu@bst.rochester.edu|Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. xqiu@bst.rochester.edu|Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. xqiu@bst.rochester.edu|Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. xqiu@bst.rochester.edu', 'United States|United States|United States|United States', 58, 'Biomarkers, Tumor|Child|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Genetic Variation|Humans|Leukemia|Models, Genetic|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-7-50', '16451725', 'The number of genes declared differentially expressed is a random variable and its variability can be assessed by resampling techniques. Another important stability indicator is the frequency with which a given gene is selected across subsamples. We have conducted studies to assess stability and some other properties of several gene selection procedures with biological and simulated data.'),
(90710, 2006, 'bmc', 'Detection of compound mode of action by computational integration of whole-genome measurements and genetic perturbations', 'Hallén, Kristofer|Björkegren, Johan|Tegnér, Jesper', 'Division of Computational Biology, The Department of Physics and Measurement Technology, Biology and Chemistry, Institute of Technology, Linköping University, S-581 83 Linköping, Sweden. hallen@ifm.liu.se|Division of Computational Biology, The Department of Physics and Measurement Technology, Biology and Chemistry, Institute of Technology, Linköping University, S-581 83 Linköping, Sweden. hallen@ifm.liu.se|Division of Computational Biology, The Department of Physics and Measurement Technology, Biology and Chemistry, Institute of Technology, Linköping University, S-581 83 Linköping, Sweden. hallen@ifm.liu.se', 'Sweden|Sweden|Sweden', 16, 'Algorithms|Chromosome Mapping|Drug Delivery Systems|Drug Design|Drug Evaluation|Gene Expression Profiling|Gene Expression Regulation|Genetic Variation|Proteome|Systems Integration', 'Journal Article', '10.1186/1471-2105-7-51', '16451737', 'A key problem of drug development is to decide which compounds to evaluate further in expensive clinical trials (Phase I- III). This decision is primarily based on the primary targets and mechanisms of action of the chemical compounds under consideration. Whole-genome expression measurements have shown to be useful for this process but current approaches suffer from requiring either a large number of mutant experiments or a detailed understanding of the regulatory networks.'),
(90711, 2006, 'bmc', 'On the attenuation and amplification of molecular noise in genetic regulatory networks', 'Chen, Bor-Sen|Wang, Yu-Chao', 'Lab of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan. bschen@ee.nthu.edu.tw|Lab of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan. bschen@ee.nthu.edu.tw', '-|-', 58, 'Animals|Cell Physiological Phenomena|Computer Simulation|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|Proteome|Signal Transduction|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-7-52', '16457708', 'Noise has many important roles in cellular genetic regulatory functions at the nanomolar scale. At present, no good theory exists for identifying all possible mechanisms of genetic regulatory networks to attenuate the molecular noise to achieve regulatory ability or to amplify the molecular noise to randomize outcomes to the advantage of diversity. Therefore, the noise filtering of genetic regulatory network is an important topic for gene networks under intrinsic fluctuation and extrinsic noise.'),
(90712, 2006, 'bmc', 'PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics', 'von Grotthuss, Marcin|Plewczynski, Dariusz|Ginalski, Krzysztof|Rychlewski, Leszek|Shakhnovich, Eugene I', 'Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA. mvg@paradox.harvard.edu|Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA. mvg@paradox.harvard.edu|Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA. mvg@paradox.harvard.edu|Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA. mvg@paradox.harvard.edu|Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, Massachusetts 02138, USA. mvg@paradox.harvard.edu', 'United States|United States|United States|United States|United States', 0, 'Chromosome Mapping|Computer Simulation|Database Management Systems|Databases, Protein|Enzyme Activation|Enzymes|Information Storage and Retrieval|Models, Chemical|Models, Molecular|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-53', '16460560', 'The number of protein structures from structural genomics centers dramatically increases in the Protein Data Bank (PDB). Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity.'),
(90713, 2006, 'bmc', 'A methodology for the structural and functional analysis of signaling and regulatory networks', 'Klamt, Steffen|Saez-Rodriguez, Julio|Lindquist, Jonathan A|Simeoni, Luca|Gilles, Ernst D', 'Max-Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max-Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max-Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max-Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de|Max-Planck Institute for Dynamics of Complex Technical Systems, Sandtorstrasse 1, D-39106 Magdeburg, Germany. klamt@mpi-magdeburg.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 265, 'Animals|Cell Physiological Phenomena|Feedback, Physiological|Gene Expression Regulation|Humans|Logistic Models|Models, Biological|Neural Networks (Computer)|Protein Interaction Mapping|Proteome|Receptors, Antigen, T-Cell|Signal Transduction|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-56', '16464248', 'Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functional capabilities. While the structural analysis of metabolic networks is a well-established field, similar methodologies have been scarcely developed and applied to signaling and regulatory networks.'),
(90714, 2006, 'bmc', 'PathSys: integrating molecular interaction graphs for systems biology', 'Baitaluk, Michael|Qian, Xufei|Godbole, Shubhada|Raval, Alpan|Ray, Animesh|Gupta, Amarnath', 'San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA. baitaluk@sdsc.edu.|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA. baitaluk@sdsc.edu.|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA. baitaluk@sdsc.edu.|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA. baitaluk@sdsc.edu.|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA. baitaluk@sdsc.edu.|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA. baitaluk@sdsc.edu.', 'United States|United States|United States|United States|United States|United States', 40, 'Computer Graphics|Computer Simulation|Databases, Protein|Information Storage and Retrieval|Models, Biological|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins|Signal Transduction|Software|Systems Biology|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-55', '16464251', 'The goal of information integration in systems biology is to combine information from a number of databases and data sets, which are obtained from both high and low throughput experiments, under one data management scheme such that the cumulative information provides greater biological insight than is possible with individual information sources considered separately.'),
(90715, 2006, 'bmc', 'FastGroupII: a web-based bioinformatics platform for analyses of large 16S rDNA libraries', 'Yu, Yanan|Breitbart, Mya|McNairnie, Pat|Rohwer, Forest', 'Department of Biology, San Diego State University, San Diego, CA, USA. yyu@rohan.sdsu.edu|Department of Biology, San Diego State University, San Diego, CA, USA. yyu@rohan.sdsu.edu|Department of Biology, San Diego State University, San Diego, CA, USA. yyu@rohan.sdsu.edu|Department of Biology, San Diego State University, San Diego, CA, USA. yyu@rohan.sdsu.edu', 'United States|United States|United States|United States', 189, 'Algorithms|Computational Biology|DNA, Bacterial|Databases, Nucleic Acid|Gene Library|Internet|Online Systems|RNA, Ribosomal, 16S|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-57', '16464253', 'High-throughput sequencing makes it possible to rapidly obtain thousands of 16S rDNA sequences from environmental samples. Bioinformatic tools for the analyses of large 16S rDNA sequence databases are needed to comprehensively describe and compare these datasets.'),
(90716, 2006, 'bmc', 'Integrated analysis of gene expression by Association Rules Discovery', 'Carmona-Saez, Pedro|Chagoyen, Monica|Rodriguez, Andres|Trelles, Oswaldo|Carazo, Jose M|Pascual-Montano, Alberto', 'BioComputing Unit, National Center for Biotechnology (CNB-CSIC), Cantoblanco, 28049, Madrid, Spain. pcarmona@cnb.uam.es|BioComputing Unit, National Center for Biotechnology (CNB-CSIC), Cantoblanco, 28049, Madrid, Spain. pcarmona@cnb.uam.es|BioComputing Unit, National Center for Biotechnology (CNB-CSIC), Cantoblanco, 28049, Madrid, Spain. pcarmona@cnb.uam.es|BioComputing Unit, National Center for Biotechnology (CNB-CSIC), Cantoblanco, 28049, Madrid, Spain. pcarmona@cnb.uam.es|BioComputing Unit, National Center for Biotechnology (CNB-CSIC), Cantoblanco, 28049, Madrid, Spain. pcarmona@cnb.uam.es|BioComputing Unit, National Center for Biotechnology (CNB-CSIC), Cantoblanco, 28049, Madrid, Spain. pcarmona@cnb.uam.es', 'Spain|Spain|Spain|Spain|Spain|Spain', 91, 'Algorithms|Artificial Intelligence|Databases, Protein|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteins|Systems Integration|Transcription Factors', 'Evaluation Studies', '10.1186/1471-2105-7-54', '16464256', 'Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process.'),
(90717, 2006, 'bmc', 'BAMarraytrade mark: Java software for Bayesian analysis of variance for microarray data', 'Ishwaran, Hemant|Rao, J Sunil|Kogalur, Udaya B', 'Department of Quantitative Health Sciences, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland OH 44195, USA. hemant.ishwaran@gmail.com|Department of Quantitative Health Sciences, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland OH 44195, USA. hemant.ishwaran@gmail.com|Department of Quantitative Health Sciences, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland OH 44195, USA. hemant.ishwaran@gmail.com', 'United States|United States|United States', 26, 'Algorithms|Analysis of Variance|Bayes Theorem|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Programming Languages|Reproducibility of Results|Sensitivity and Specificity|Software', 'Journal Article', '10.1186/1471-2105-7-59', '16466568', 'DNA microarrays open up a new horizon for studying the genetic determinants of disease. The high throughput nature of these arrays creates an enormous wealth of information, but also poses a challenge to data analysis. Inferential problems become even more pronounced as experimental designs used to collect data become more complex. An important example is multigroup data collected over different experimental groups, such as data collected from distinct stages of a disease process. We have developed a method specifically addressing these issues termed Bayesian ANOVA for microarrays (BAM). The BAM approach uses a special inferential regularization known as spike-and-slab shrinkage that provides an optimal balance between total false detections and total false non-detections. This translates into more reproducible differential calls. Spike and slab shrinkage is a form of regularization achieved by using information across all genes and groups simultaneously.'),
(90718, 2006, 'bmc', 'Identifying biological concepts from a protein-related corpus with a probabilistic topic model', 'Zheng, Bin|McLean, David C|Lu, Xinghua', 'Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29405, USA. zheng@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29405, USA. zheng@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, SC 29405, USA. zheng@musc.edu', 'United States|United States|United States', 43, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|MEDLINE|Models, Biological|Models, Statistical|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Proteins|Terminology as Topic|Vocabulary, Controlled', 'Evaluation Studies', '10.1186/1471-2105-7-58', '16466569', 'Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE titles and abstracts by applying a probabilistic topic model.'),
(90719, 2006, 'bmc', 'JLIN: a java based linkage disequilibrium plotter', 'Carter, Kim W|McCaskie, Pamela A|Palmer, Lyle J', 'Laboratory for Genetic Epidemiology, Western Australian Institute for Medical Research and UWA Centre for Medical Research, University of Western Australia, Nedlands, 6009, Western Australia . kcarter@cyllene.uwa.edu.au|Laboratory for Genetic Epidemiology, Western Australian Institute for Medical Research and UWA Centre for Medical Research, University of Western Australia, Nedlands, 6009, Western Australia . kcarter@cyllene.uwa.edu.au|Laboratory for Genetic Epidemiology, Western Australian Institute for Medical Research and UWA Centre for Medical Research, University of Western Australia, Nedlands, 6009, Western Australia . kcarter@cyllene.uwa.edu.au', 'Australia|Australia|Australia', 100, 'Algorithms|Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Genetic|Linkage Disequilibrium|Polymorphism, Genetic|Polymorphism, Single Nucleotide|Programming Languages|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-60', '16466584', 'A great deal of effort and expense are being expended internationally in attempts to detect genetic polymorphisms contributing to susceptibility to complex human disease. Techniques such as Linkage Disequilibrium mapping are being increasingly used to examine and compare markers across increasingly large datasets. Visualisation techniques are becoming essential to analyse the ever-growing volume of data and results available with any given analysis.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90720, 2006, 'bmc', 'Comparative analysis of haplotype association mapping algorithms', 'McClurg, Phillip|Pletcher, Mathew T|Wiltshire, Tim|Su, Andrew I', 'Genomics Institute of the Novartis Research Foundation, San Diego, USA. pmcclurg@gnf.org|Genomics Institute of the Novartis Research Foundation, San Diego, USA. pmcclurg@gnf.org|Genomics Institute of the Novartis Research Foundation, San Diego, USA. pmcclurg@gnf.org|Genomics Institute of the Novartis Research Foundation, San Diego, USA. pmcclurg@gnf.org', 'United States|United States|United States|United States', 46, 'Algorithms|Animals|Chromosome Mapping|DNA Mutational Analysis|Genetic Variation|Haplotypes|Mice|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1186/1471-2105-7-61', '16466585', 'Finding the genetic causes of quantitative traits is a complex and difficult task. Classical methods for mapping quantitative trail loci (QTL) in miceuse an F2 cross between two strains with substantially different phenotype and an interval mapping method to compute confidence intervals at each position in the genome. This process requires significant resources for breeding and genotyping, and the data generated are usually only applicable to one phenotype of interest. Recently, we reported the application of a haplotype association mapping method which utilizes dense genotyping data across a diverse panel of inbred mouse strains and a marker association algorithm that is independent of any specific phenotype. As the availability of genotyping data grows in size and density, analysis of these haplotype association mapping methods should be of increasing value to the statistical genetics community.'),
(90721, 2005, 'bmc', 'A critical assessment of text mining methods in molecular biology Proceedings of a workshop March 28-31, 2004 Granada, Spain', '-', '-', '-', 46, 'Animals|Computational Biology|Data Collection|Database Management Systems|Genes|Humans|Information Storage and Retrieval|Molecular Biology|Proteins', 'Congress', '10.1186/1471-2105-7-61', '16468169', '-'),
(90722, 2006, 'bmc', 'HotSwap for bioinformatics: a STRAP tutorial', 'Gille, Christoph|Robinson, Peter N', 'Institute for Biochemistry, Charité University Hospital, Humboldt University, Berlin, Germany. christoph.gille@charite.de|Institute for Biochemistry, Charité University Hospital, Humboldt University, Berlin, Germany. christoph.gille@charite.de', 'Germany|Germany', 8, 'Algorithms|Computational Biology|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Programming Languages|Sequence Alignment|Sequence Analysis|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-64', '16469097', 'Bioinformatics applications are now routinely used to analyze large amounts of data. Application development often requires many cycles of optimization, compiling, and testing. Repeatedly loading large datasets can significantly slow down the development process. We have incorporated HotSwap functionality into the protein workbench STRAP, allowing developers to create plugins using the Java HotSwap technique.'),
(90723, 2006, 'bmc', 'Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources', 'Stanke, Mario|Schöffmann, Oliver|Morgenstern, Burkhard|Waack, Stephan', 'lnstitut für Mikrobiologie und Genetik, Universität Göttingen, Göttingen, Germany. mstanke@gwdg.de|lnstitut für Mikrobiologie und Genetik, Universität Göttingen, Göttingen, Germany. mstanke@gwdg.de|lnstitut für Mikrobiologie und Genetik, Universität Göttingen, Göttingen, Germany. mstanke@gwdg.de|lnstitut für Mikrobiologie und Genetik, Universität Göttingen, Göttingen, Germany. mstanke@gwdg.de', 'Germany|Germany|Germany|Germany', 406, 'Algorithms|Animals|Artificial Intelligence|Base Sequence|Chromosome Mapping|Computer Simulation|Databases, Genetic|Genetic Variation|Humans|Information Storage and Retrieval|Markov Chains|Models, Genetic|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-7-62', '16469098', 'In order to improve gene prediction, extrinsic evidence on the gene structure can be collected from various sources of information such as genome-genome comparisons and EST and protein alignments. However, such evidence is often incomplete and usually uncertain. The extrinsic evidence is usually not sufficient to recover the complete gene structure of all genes completely and the available evidence is often unreliable. Therefore extrinsic evidence is most valuable when it is balanced with sequence-intrinsic evidence.'),
(90724, 2006, 'bmc', 'Bayesian detection of periodic mRNA time profiles without use of training examples', 'Andersson, Claes R|Isaksson, Anders|Gustafsson, Mats G', 'The Linnaeus Centre for Bioinformatics, BMC, Uppsala University, Box 598, S-751 24 Uppsala, Sweden. canders@lcb.uu.se|The Linnaeus Centre for Bioinformatics, BMC, Uppsala University, Box 598, S-751 24 Uppsala, Sweden. canders@lcb.uu.se|The Linnaeus Centre for Bioinformatics, BMC, Uppsala University, Box 598, S-751 24 Uppsala, Sweden. canders@lcb.uu.se', 'Sweden|Sweden|Sweden', 13, 'Algorithms|Artificial Intelligence|Bayes Theorem|Cell Cycle Proteins|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Periodicity|RNA, Messenger|Saccharomyces cerevisiae Proteins', 'Evaluation Studies', '10.1186/1471-2105-7-63', '16469110', 'Detection of periodically expressed genes from microarray data without use of known periodic and non-periodic training examples is an important problem, e.g. for identifying genes regulated by the cell-cycle in poorly characterised organisms. Commonly the investigator is only interested in genes expressed at a particular frequency that characterizes the process under study but this frequency is seldom exactly known. Previously proposed detector designs require access to labelled training examples and do not allow systematic incorporation of diffuse prior knowledge available about the period time.'),
(90725, 2006, 'bmc', 'Computational models with thermodynamic and composition features improve siRNA design', 'Shabalina, Svetlana A|Spiridonov, Alexey N|Ogurtsov, Aleksey Y', 'National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, MD 20894, USA. shabalin@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, MD 20894, USA. shabalin@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, MD 20894, USA. shabalin@ncbi.nlm.nih.gov', 'United States|United States|United States', 0, 'Artificial Intelligence|Base Pairing|Computer Simulation|Computer-Aided Design|Gene Silencing|Models, Chemical|Models, Genetic|Pattern Recognition, Automated|RNA, Small Interfering|Sequence Alignment|Sequence Analysis, RNA|Thermodynamics', 'Journal Article', '10.1186/1471-2105-7-65', '16472402', 'Small interfering RNAs (siRNAs) have become an important tool in cell and molecular biology. Reliable design of siRNA molecules is essential for the needs of large functional genomics projects.'),
(90726, 2006, 'bmc', 'RibAlign: a software tool and database for eubacterial phylogeny based on concatenated ribosomal protein subunits', 'Teeling, Hanno|Gloeckner, Frank Oliver', 'Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. hteeling@mpi-bremen.de|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. hteeling@mpi-bremen.de', 'Germany|Germany', 0, 'Algorithms|Bacteria|Databases, Protein|Phylogeny|RNA, Ribosomal, 16S|Ribosomal Proteins|Sequence Alignment|Sequence Analysis, RNA|Software', 'Evaluation Studies', '10.1186/1471-2105-7-66', '16476165', 'Until today, analysis of 16S ribosomal RNA (rRNA) sequences has been the de-facto gold standard for the assessment of phylogenetic relationships among prokaryotes. However, the branching order of the individual phlya is not well-resolved in 16S rRNA-based trees. In search of an improvement, new phylogenetic methods have been developed alongside with the growing availability of complete genome sequences. Unfortunately, only a few genes in prokaryotic genomes qualify as universal phylogenetic markers and almost all of them have a lower information content than the 16S rRNA gene. Therefore, emphasis has been placed on methods that are based on multiple genes or even entire genomes. The concatenation of ribosomal protein sequences is one method which has been ascribed an improved resolution. Since there is neither a comprehensive database for ribosomal protein sequences nor a tool that assists in sequence retrieval and generation of respective input files for phylogenetic reconstruction programs, RibAlign has been developed to fill this gap.'),
(90727, 2006, 'bmc', 'Algebraic comparison of metabolic networks, phylogenetic inference, and metabolic innovation', 'Forst, Christian V|Flamm, Christoph|Hofacker, Ivo L|Stadler, Peter F', 'Bioscience Division, Los Alamos National Laboratory, Mailstop M888, PO Box 1663, Los Alamos, NM 87545, USA. chris@lanl.gov|Bioscience Division, Los Alamos National Laboratory, Mailstop M888, PO Box 1663, Los Alamos, NM 87545, USA. chris@lanl.gov|Bioscience Division, Los Alamos National Laboratory, Mailstop M888, PO Box 1663, Los Alamos, NM 87545, USA. chris@lanl.gov|Bioscience Division, Los Alamos National Laboratory, Mailstop M888, PO Box 1663, Los Alamos, NM 87545, USA. chris@lanl.gov', 'United States|United States|United States|United States', 35, 'Algorithms|Computer Simulation|Evolution, Molecular|Models, Biological|Numerical Analysis, Computer-Assisted|Phylogeny|Signal Transduction', 'Comparative Study', '10.1186/1471-2105-7-67', '16478540', 'Comparison of metabolic networks is typically performed based on the organisms enzyme contents. This approach disregards functional replacements as well as orthologies that are misannotated. Direct comparison of the structure of metabolic networks can circumvent these problems.'),
(90728, 2006, 'bmc', 'Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures', 'Bodén, Mikael|Yuan, Zheng|Bailey, Timothy L', 'School of Information Technology and Electrical Engineering, The University of Queensland, QLD 4072, St Lucia, Australia. mikael@itee.uq.edu.au|School of Information Technology and Electrical Engineering, The University of Queensland, QLD 4072, St Lucia, Australia. mikael@itee.uq.edu.au|School of Information Technology and Electrical Engineering, The University of Queensland, QLD 4072, St Lucia, Australia. mikael@itee.uq.edu.au', 'Australia|Australia|Australia', 0, 'Algorithms|Computer Simulation|Crystallography|Magnetic Resonance Spectroscopy|Models, Chemical|Models, Molecular|Models, Statistical|Neural Networks (Computer)|Protein Structure, Secondary|Proteins|Sequence Analysis, Protein', 'Evaluation Studies', '10.1186/1471-2105-7-68', '16478545', 'The structure of proteins may change as a result of the inherent flexibility of some protein regions. We develop and explore probabilistic machine learning methods for predicting a continuum secondary structure, i.e. assigning probabilities to the conformational states of a residue. We train our methods using data derived from high-quality NMR models.'),
(90729, 2006, 'bmc', 'In search of functional association from time-series microarray data based on the change trend and level of gene expression', 'He, Feng|Zeng, An-Ping', 'Research Group Systems Biology, GBF-German Research Center for Biotechnology, Mascheroder Weg 1, 38124 Braunschweig, Germany. fhe@gbf.de|Research Group Systems Biology, GBF-German Research Center for Biotechnology, Mascheroder Weg 1, 38124 Braunschweig, Germany. fhe@gbf.de', 'Germany|Germany', 17, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Protein Interaction Mapping|Time Factors', 'Evaluation Studies', '10.1186/1471-2105-7-69', '16478547', 'The increasing availability of time-series expression data opens up new possibilities to study functional linkages of genes. Present methods used to infer functional linkages between genes from expression data are mainly based on a point-to-point comparison. Change trends between consecutive time points in time-series data have been so far not well explored.'),
(90730, 2006, 'bmc', 'Hubs of knowledge: using the functional link structure in Biozon to mine for biologically significant entities', 'Shafer, Paul|Isganitis, Timothy|Yona, Golan', 'Department of Computer Science, Cornell University, Ithaca, NY, USA. pes25@cornell.edu|Department of Computer Science, Cornell University, Ithaca, NY, USA. pes25@cornell.edu|Department of Computer Science, Cornell University, Ithaca, NY, USA. pes25@cornell.edu', 'United States|United States|United States', 0, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Natural Language Processing|Online Systems|User-Computer Interface|Vocabulary, Controlled', 'Evaluation Studies', '10.1186/1471-2105-7-71', '16480496', 'Existing biological databases support a variety of queries such as keyword or definition search. However, they do not provide any measure of relevance for the instances reported, and result sets are usually sorted arbitrarily.'),
(90731, 2006, 'bmc', 'BIOZON: a system for unification, management and analysis of heterogeneous biological data', 'Birkland, Aaron|Yona, Golan', 'Department of Computer Science, Cornell University, Ithaca, NY, USA. birkland@cs.cornell.edu|Department of Computer Science, Cornell University, Ithaca, NY, USA. birkland@cs.cornell.edu', 'United States|United States', 63, 'Animals|Biology|Computational Biology|Computer Graphics|Database Management Systems|Databases, Factual|Databases, Genetic|Databases, Protein|Humans|Information Storage and Retrieval|Internet|Models, Statistical|Programming Languages|Research|Sequence Analysis, DNA|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-70', '16480510', 'Integration of heterogeneous data types is a challenging problem, especially in biology, where the number of databases and data types increase rapidly. Amongst the problems that one has to face are integrity, consistency, redundancy, connectivity, expressiveness and updatability.'),
(90732, 2006, 'bmc', 'GO-Diff: mining functional differentiation between EST-based transcriptomes', 'Chen, Zuozhou|Wang, Weilin|Ling, Xuefeng Bruce|Liu, Jane Jijun|Chen, Liangbiao', 'College of Life Science, Zhejiang University, Hangzhou 310029, China. zzchen@genetics.ac.cn|College of Life Science, Zhejiang University, Hangzhou 310029, China. zzchen@genetics.ac.cn|College of Life Science, Zhejiang University, Hangzhou 310029, China. zzchen@genetics.ac.cn|College of Life Science, Zhejiang University, Hangzhou 310029, China. zzchen@genetics.ac.cn|College of Life Science, Zhejiang University, Hangzhou 310029, China. zzchen@genetics.ac.cn', 'China|China|China|China|China', 0, 'Animals|Chromosome Mapping|Databases, Protein|Expressed Sequence Tags|Gene Expression Profiling|Genetics|Information Storage and Retrieval|Mice|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Proteome|Software|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-72', '16480524', 'Large-scale sequencing efforts produced millions of Expressed Sequence Tags (ESTs) collectively representing differentiated biochemical and functional states. Analysis of these EST libraries reveals differential gene expressions, and therefore EST data sets constitute valuable resources for comparative transcriptomics. To translate differentially expressed genes into a better understanding of the underlying biological phenomena, existing microarray analysis approaches usually involve the integration of gene expression with Gene Ontology (GO) databases to derive comparable functional profiles. However, methods are not available yet to process EST-derived transcription maps to enable GO-based global functional profiling for comparative transcriptomics in a high throughput manner.'),
(90733, 2006, 'bmc', 'Detecting overlapping coding sequences in virus genomes', 'Firth, Andrew E|Brown, Chris M', 'Department of Biochemistry, University of Otago, PO Box 56, Dunedin, New Zealand. aef@sanger.otago.ac.nz|Department of Biochemistry, University of Otago, PO Box 56, Dunedin, New Zealand. aef@sanger.otago.ac.nz', 'New Zealand|New Zealand', 0, 'Algorithms|Binding Sites|Codon|Codon, Terminator|Computational Biology|Conserved Sequence|Databases as Topic|Frameshift Mutation|Genes, Overlapping|Genes, Viral|Genome|Genome, Viral|Likelihood Functions|Models, Statistical|Mutation|Open Reading Frames|Protein Biosynthesis|Sequence Alignment|Sequence Analysis, DNA|Software|Viruses', 'Journal Article', '10.1186/1471-2105-7-75', '16483358', 'Detecting new coding sequences (CDSs) in viral genomes can be difficult for several reasons. The typically compact genomes often contain a number of overlapping coding and non-coding functional elements, which can result in unusual patterns of codon usage, conservation between related sequences can be difficult to interpret--especially within overlapping genes, and viruses often employ non-canonical translational mechanisms--e.g. frameshifting, stop codon read-through, leaky-scanning and internal ribosome entry sites--which can conceal potentially coding open reading frames (ORFs).'),
(90734, 2006, 'bmc', 'Spectral embedding finds meaningful (relevant) structure in image and microarray data', 'Higgs, Brandon W|Weller, Jennifer|Solka, Jeffrey L', 'School of Computational Sciences, George Mason University, Manassas, VA 20110, USA. bhiggs@gmu.edu|School of Computational Sciences, George Mason University, Manassas, VA 20110, USA. bhiggs@gmu.edu|School of Computational Sciences, George Mason University, Manassas, VA 20110, USA. bhiggs@gmu.edu', 'United States|United States|United States', 15, 'Algorithms|Artificial Intelligence|Brain|Cluster Analysis|Computational Biology|Computer Graphics|Computing Methodologies|Data Interpretation, Statistical|Fibroblasts|Humans|Image Processing, Computer-Assisted|Information Storage and Retrieval|Models, Biological|Models, Statistical|Normal Distribution|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Principal Component Analysis|Regression Analysis|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-7-74', '16483359', 'Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing measurements across thousands of variables. Principal components analysis (PCA) is a linear dimensionality reduction (DR) method that is unsupervised in that it relies only on the data, projections are calculated in Euclidean or a similar linear space and do not use tuning parameters for optimizing the fit to the data. However, relationships within sets of nonlinear data types, such as biological networks or images, are frequently mis-rendered into a low dimensional space by linear methods. Nonlinear methods, in contrast, attempt to model important aspects of the underlying data structure, often requiring parameter(s) fitting to the data type of interest. In many cases, the optimal parameter values vary when different classification algorithms are applied on the same rendered subspace, making the results of such methods highly dependent upon the type of classifier implemented.'),
(90735, 2006, 'bmc', 'Instance-based concept learning from multiclass DNA microarray data', 'Berrar, Daniel|Bradbury, Ian|Dubitzky, Werner', 'School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. dp.berrar@ulster.ac.uk|School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. dp.berrar@ulster.ac.uk|School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. dp.berrar@ulster.ac.uk', 'Ireland|Ireland|Ireland', 0, 'Algorithms|Artificial Intelligence|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-7-73', '16483361', 'Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as nearest neighbor (NN) approaches perform remarkably well in comparison to more complex models, and are currently experiencing a renaissance in the analysis of data sets from biology and biotechnology. While binary classification of microarray data has been extensively investigated, studies involving multiclass data are rare. The question remains open whether there exists a significant difference in performance between NN approaches and more complex multiclass methods. Comparative studies in this field commonly assess different models based on their classification accuracy only, however, this approach lacks the rigor needed to draw reliable conclusions and is inadequate for testing the null hypothesis of equal performance. Comparing novel classification models to existing approaches requires focusing on the significance of differences in performance.'),
(90736, 2006, 'bmc', 'Gene annotation and network inference by phylogenetic profiling', 'Wu, Jie|Hu, Zhenjun|DeLisi, Charles', 'Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA. jiewu@bu.edu|Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA. jiewu@bu.edu|Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA. jiewu@bu.edu', 'United States|United States|United States', 26, 'Algorithms|Gene Expression Profiling|Gene Expression Regulation|Oligonucleotide Array Sequence Analysis|Phylogeny|Sequence Analysis, DNA|Signal Transduction', 'Journal Article', '10.1186/1471-2105-7-80', '16503966', 'Phylogenetic analysis is emerging as one of the most informative computational methods for the annotation of genes and identification of evolutionary modules of functionally related genes. The effectiveness with which phylogenetic profiles can be utilized to assign genes to pathways depends on an appropriate measure of correlation between gene profiles, and an effective decision rule to use the correlate. Current methods, though useful, perform at a level well below what is possible, largely because performance of the latter deteriorates rapidly as coverage increases.'),
(90737, 2006, 'bmc', 'Taxonomic colouring of phylogenetic trees of protein sequences', 'Palidwor, Gareth|Reynaud, Emmanuel G|Andrade-Navarro, Miguel A', 'Ontario Genomics Innovation Centre, Ottawa Health Research Institute, 501 Smyth, Ottawa, ON K1H 8L6, Canada. gpalidwor@ohri.ca|Ontario Genomics Innovation Centre, Ottawa Health Research Institute, 501 Smyth, Ottawa, ON K1H 8L6, Canada. gpalidwor@ohri.ca|Ontario Genomics Innovation Centre, Ottawa Health Research Institute, 501 Smyth, Ottawa, ON K1H 8L6, Canada. gpalidwor@ohri.ca', 'Canada|Canada|Canada', 6, 'Algorithms|Amino Acid Sequence|Color|Evolution, Molecular|Molecular Sequence Data|Phylogeny|Proteome|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-79', '16503967', 'Phylogenetic analyses of protein families are used to define the evolutionary relationships between homologous proteins. The interpretation of protein-sequence phylogenetic trees requires the examination of the taxonomic properties of the species associated to those sequences. However, there is no online tool to facilitate this interpretation, for example, by automatically attaching taxonomic information to the nodes of a tree, or by interactively colouring the branches of a tree according to any combination of taxonomic divisions. This is especially problematic if the tree contains on the order of hundreds of sequences, which, given the accelerated increase in the size of the protein sequence databases, is a situation that is becoming common.'),
(90738, 2006, 'bmc', 'Transcriptomic response to differentiation induction', 'Patton, G W|Stephens, R|Sidorov, I A|Xiao, X|Lempicki, R A|Dimitrov, D S|Shoemaker, R H|Tudor, G', 'Screening Technologies Branch, Developmental Therapeutics Program, NCI-Frederick, Frederick, MD 21702, USA. gpatton@ncifcrf.gov|Screening Technologies Branch, Developmental Therapeutics Program, NCI-Frederick, Frederick, MD 21702, USA. gpatton@ncifcrf.gov|Screening Technologies Branch, Developmental Therapeutics Program, NCI-Frederick, Frederick, MD 21702, USA. gpatton@ncifcrf.gov|Screening Technologies Branch, Developmental Therapeutics Program, NCI-Frederick, Frederick, MD 21702, USA. gpatton@ncifcrf.gov|Screening Technologies Branch, Developmental Therapeutics Program, NCI-Frederick, Frederick, MD 21702, USA. gpatton@ncifcrf.gov|Screening Technologies Branch, Developmental Therapeutics Program, NCI-Frederick, Frederick, MD 21702, USA. gpatton@ncifcrf.gov|Screening Technologies Branch, Developmental Therapeutics Program, NCI-Frederick, Frederick, MD 21702, USA. gpatton@ncifcrf.gov|Screening Technologies Branch, Developmental Therapeutics Program, NCI-Frederick, Frederick, MD 21702, USA. gpatton@ncifcrf.gov', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Cell Differentiation|Cell Line, Tumor|Cell Proliferation|Cluster Analysis|Data Interpretation, Statistical|Databases, Factual|Down-Regulation|Gene Expression Regulation, Neoplastic|Genes, Regulator|Granulocyte Precursor Cells|Humans|Internet|Leukemia|Oligonucleotide Array Sequence Analysis|Proteins|RNA, Messenger|Time Factors|Transcription Factors|Transcription, Genetic|Tretinoin|U937 Cells|Up-Regulation', 'Journal Article', '10.1186/1471-2105-7-81', '16503971', 'Microarrays used for gene expression studies yield large amounts of data. The processing of such data typically leads to lists of differentially-regulated genes. A common terminal data analysis step is to map pathways of potentially interrelated genes.'),
(90739, 2006, 'bmc', 'Biclustering of gene expression data by Non-smooth Non-negative Matrix Factorization', 'Carmona-Saez, Pedro|Pascual-Marqui, Roberto D|Tirado, F|Carazo, Jose M|Pascual-Montano, Alberto', 'BioComputing Unit, National Center of Biotechnology, Campus Universidad Autónoma de Madrid, 28049. Spain. pcarmona@cnb.uam.es|BioComputing Unit, National Center of Biotechnology, Campus Universidad Autónoma de Madrid, 28049. Spain. pcarmona@cnb.uam.es|BioComputing Unit, National Center of Biotechnology, Campus Universidad Autónoma de Madrid, 28049. Spain. pcarmona@cnb.uam.es|BioComputing Unit, National Center of Biotechnology, Campus Universidad Autónoma de Madrid, 28049. Spain. pcarmona@cnb.uam.es|BioComputing Unit, National Center of Biotechnology, Campus Universidad Autónoma de Madrid, 28049. Spain. pcarmona@cnb.uam.es', 'Spain|Spain|Spain|Spain|Spain', 129, 'Algorithms|Artificial Intelligence|Cluster Analysis|Factor Analysis, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Evaluation Studies', '10.1186/1471-2105-7-78', '16503973', 'The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of genes across tens or hundreds of different experimental conditions. One of the major challenges in the analysis of such datasets is to discover local structures composed by sets of genes that show coherent expression patterns across subsets of experimental conditions. These patterns may provide clues about the main biological processes associated to different physiological states.'),
(90740, 2006, 'bmc', 'BIPAD: a web server for modeling bipartite sequence elements', 'Bi, Chengpeng|Rogan, Peter K', 'Laboratory of Human Molecular Genetics, Childrens Mercy Hospital & Clinics, Kansas City, MO 64108, USA. cbi@cmh.edu|Laboratory of Human Molecular Genetics, Childrens Mercy Hospital & Clinics, Kansas City, MO 64108, USA. cbi@cmh.edu', 'United States|United States', 13, 'Algorithms|Base Sequence|Binding Sites|Chromosome Mapping|Computer Simulation|DNA-Binding Proteins|Internet|Models, Genetic|Molecular Sequence Data|Online Systems|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-76', '16503993', 'Many dimeric protein complexes bind cooperatively to families of bipartite nucleic acid sequence elements, which consist of pairs of conserved half-site sequences separated by intervening distances that vary among individual sites.'),
(90741, 2006, 'bmc', 'Quantitative comparison of EST libraries requires compensation for systematic biases in cDNA generation', 'Liu, Donglin|Graber, Joel H', 'The Jackson Laboratory, Bar Harbor, ME 04609, USA. liudl@yahoo.com|The Jackson Laboratory, Bar Harbor, ME 04609, USA. liudl@yahoo.com', 'United States|United States', 25, 'Algorithms|Artifacts|Base Sequence|Bias|DNA, Complementary|Expressed Sequence Tags|Gene Library|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-77', '16503995', 'Publicly accessible EST libraries contain valuable information that can be utilized for studies of tissue-specific gene expression and processing of individual genes. This information is, however, confounded by multiple systematic effects arising from the procedures used to generate these libraries.'),
(90742, 2006, 'bmc', 'PhosphoregDB: the tissue and sub-cellular distribution of mammalian protein kinases and phosphatases', 'Forrest, Alistair R R|Taylor, Darrin F|Fink, J Lynn|Gongora, M Milena|Flegg, Cameron|Teasdale, Rohan D|Suzuki, Harukazu|Kanamori, Mutsumi|Kai, Chikatoshi|Hayashizaki, Yoshihide|Grimmond, Sean M', 'The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au|The Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia. a.forrest@imb.uq.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|', 12, 'Amino Acid Sequence|Animals|Cell Cycle|Cell Lineage|Cluster Analysis|Computational Biology|Cytoplasm|Databases, Protein|Expressed Sequence Tags|Gene Expression Regulation|HeLa Cells|Humans|Immune System|Immunoprecipitation|Internet|Mice|Molecular Sequence Data|Phosphoric Monoester Hydrolases|Phosphorylation|Polymerase Chain Reaction|Promoter Regions, Genetic|Protein Interaction Mapping|Protein Kinases|Signal Transduction|Substrate Specificity|Tissue Distribution|Transfection', 'Journal Article', '10.1186/1471-2105-7-82', '16504016', 'Protein kinases and protein phosphatases are the fundamental components of phosphorylation dependent protein regulatory systems. We have created a database for the protein kinase-like and phosphatase-like loci of mouse http://phosphoreg.imb.uq.edu.au that integrates protein sequence, interaction, classification and pathway information with the results of a systematic screen of their sub-cellular localization and tissue specific expression data mined from the GNF tissue atlas of mouse.'),
(90743, 2006, 'bmc', 'CARAT: a novel method for allelic detection of DNA copy number changes using high density oligonucleotide arrays', 'Huang, Jing|Wei, Wen|Chen, Joyce|Zhang, Jane|Liu, Guoying|Di, Xiaojun|Mei, Rui|Ishikawa, Shumpei|Aburatani, Hiroyuki|Jones, Keith W|Shapero, Michael H', 'Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com|Affymetrix, Inc, 3420 Central Expressway, Santa Clara, CA 95051, USA. jing_huang@affymetrix.com', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 53, 'Algorithms|Alleles|Chromosome Mapping|Chromosomes, Human, X|DNA Mutational Analysis|DNA, Neoplasm|Gene Dosage|Gene Frequency|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-7-83', '16504045', 'DNA copy number alterations are one of the main characteristics of the cancer cell karyotype and can contribute to the complex phenotype of these cells. These alterations can lead to gains in cellular oncogenes as well as losses in tumor suppressor genes and can span small intervals as well as involve entire chromosomes. The ability to accurately detect these changes is central to understanding how they impact the biology of the cell.'),
(90744, 2006, 'bmc', 'Statistical analysis of real-time PCR data', 'Yuan, Joshua S|Reed, Ann|Chen, Feng|Stewart, C Neal', 'Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. syuan@utk.edu|Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. syuan@utk.edu|Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. syuan@utk.edu|Department of Plant Sciences, University of Tennessee, Knoxville, TN 37996, USA. syuan@utk.edu', 'United States|United States|United States|United States', 1190, 'Analysis of Variance|Animals|Base Pair Mismatch|Cloning, Molecular|Computational Biology|DNA Probes|DNA, Complementary|Data Interpretation, Statistical|Gene Expression Profiling|Humans|Mice|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Polymerase Chain Reaction|Programming Languages|Quality Control|RNA|Regression Analysis|Reproducibility of Results|Reverse Transcriptase Polymerase Chain Reaction|Sensitivity and Specificity|Software|Statistics as Topic', 'Journal Article', '10.1186/1471-2105-7-85', '16504059', 'Even though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking, specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models for the analysis of real-time PCR data.'),
(90745, 2006, 'bmc', 'The PowerAtlas: a power and sample size atlas for microarray experimental design and research', 'Page, Grier P|Edwards, Jode W|Gadbury, Gary L|Yelisetti, Prashanth|Wang, Jelai|Trivedi, Prinal|Allison, David B', 'Department of Biostatistics, University of Alabama, Birmingham, AL, USA. gpage@uab.edu|Department of Biostatistics, University of Alabama, Birmingham, AL, USA. gpage@uab.edu|Department of Biostatistics, University of Alabama, Birmingham, AL, USA. gpage@uab.edu|Department of Biostatistics, University of Alabama, Birmingham, AL, USA. gpage@uab.edu|Department of Biostatistics, University of Alabama, Birmingham, AL, USA. gpage@uab.edu|Department of Biostatistics, University of Alabama, Birmingham, AL, USA. gpage@uab.edu|Department of Biostatistics, University of Alabama, Birmingham, AL, USA. gpage@uab.edu', 'United States|United States|United States|United States|United States|United States|United States', 53, 'Algorithms|Arabidopsis|Computational Biology|Computer Simulation|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Genes, Plant|Genetic Variation|Internet|Models, Statistical|Oligonucleotide Array Sequence Analysis|Plant Proteins|Probability|Programming Languages|RNA, Messenger|Reproducibility of Results|Research Design|Sample Size|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-7-84', '16504070', 'Microarrays permit biologists to simultaneously measure the mRNA abundance of thousands of genes. An important issue facing investigators planning microarray experiments is how to estimate the sample size required for good statistical power. What is the projected sample size or number of replicate chips needed to address the multiple hypotheses with acceptable accuracy? Statistical methods exist for calculating power based upon a single hypothesis, using estimates of the variability in data from pilot studies. There is, however, a need for methods to estimate power and/or required sample sizes in situations where multiple hypotheses are being tested, such as in microarray experiments. In addition, investigators frequently do not have pilot data to estimate the sample sizes required for microarray studies.'),
(90746, 2006, 'bmc', 'A graphical model approach to automated classification of protein subcellular location patterns in multi-cell images', 'Chen, Shann-Ching|Murphy, Robert F', 'Department of Biomedical Engineering and Center for Bioimage Informatics, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|Department of Biomedical Engineering and Center for Bioimage Informatics, Carnegie Mellon University, Pittsburgh, PA 15213, USA.', 'United States|United States', 22, 'Algorithms|Automation|Bayes Theorem|Cells|Cellular Structures|Computational Biology|HeLa Cells|Humans|Image Processing, Computer-Assisted|Microscopy, Fluorescence|Models, Biological|Pattern Recognition, Automated|Proteins|Reproducibility of Results', 'Evaluation Studies', '10.1186/1471-2105-7-90', '16504075', 'Knowledge of the subcellular location of a protein is critical to understanding how that protein works in a cell. This location is frequently determined by the interpretation of fluorescence microscope images. In recent years, automated systems have been developed for consistent and objective interpretation of such images so that the protein pattern in a single cell can be assigned to a known location category. While these systems perform with nearly perfect accuracy for single cell images of all major subcellular structures, their ability to distinguish subpatterns of an organelle (such as two Golgi proteins) is not perfect. Our goal in the work described here was to improve the ability of an automated system to decide which of two similar patterns is present in a field of cells by considering more than one cell at a time. Since cells displaying the same location pattern are often clustered together, considering multiple cells may be expected to improve discrimination between similar patterns.'),
(90747, 2006, 'bmc', 'Integrating protein structures and precomputed genealogies in the Magnum database: examples with cellular retinoid binding proteins', 'Bradley, Michael E|Benner, Steven A', 'Department of Chemistry, University of Florida, PO Box 117200, Gainesville, FL 32611, USA. mbradley@ffame.org|Department of Chemistry, University of Florida, PO Box 117200, Gainesville, FL 32611, USA. mbradley@ffame.org', 'United States|United States', 1, 'Amino Acid Sequence|Binding Sites|Computer Simulation|Database Management Systems|Databases, Protein|Evolution, Molecular|Information Storage and Retrieval|Models, Chemical|Molecular Sequence Data|Pedigree|Protein Binding|Protein Conformation|Retinol-Binding Proteins|Retinol-Binding Proteins, Cellular|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-7-89', '16504077', 'When accurate models for the divergent evolution of protein sequences are integrated with complementary biological information, such as folded protein structures, analyses of the combined data often lead to new hypotheses about molecular physiology. This represents an excellent example of how bioinformatics can be used to guide experimental research. However, progress in this direction has been slowed by the lack of a publicly available resource suitable for general use.'),
(90748, 2006, 'bmc', 'BayGO: Bayesian analysis of ontology term enrichment in microarray data', 'Vêncio, Ricardo Z N|Koide, Tie|Gomes, Suely L|Pereira, Carlos A de B', 'BIOINFO, Universidade de São Paulo, 05508-090 São Paulo, Brazil. rvencio@vision.ime.usp.br|BIOINFO, Universidade de São Paulo, 05508-090 São Paulo, Brazil. rvencio@vision.ime.usp.br|BIOINFO, Universidade de São Paulo, 05508-090 São Paulo, Brazil. rvencio@vision.ime.usp.br|BIOINFO, Universidade de São Paulo, 05508-090 São Paulo, Brazil. rvencio@vision.ime.usp.br', 'Brazil|Brazil|Brazil|Brazil', 41, 'Bacteria|Bayes Theorem|Computational Biology|Gene Expression Regulation, Bacterial|Heat-Shock Proteins|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software|Terminology as Topic', 'Comparative Study', '10.1186/1471-2105-7-86', '16504085', 'The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem.'),
(90749, 2006, 'bmc', 'Phase analysis of circadian-related genes in two tissues', 'Liu, Delong|Peddada, Shyamal D|Li, Leping|Weinberg, Clarice R', 'Biostatistics Branch, National Institute of Environmental Health Sciences, MD: A3-03, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA. dliu@ciit.org|Biostatistics Branch, National Institute of Environmental Health Sciences, MD: A3-03, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA. dliu@ciit.org|Biostatistics Branch, National Institute of Environmental Health Sciences, MD: A3-03, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA. dliu@ciit.org|Biostatistics Branch, National Institute of Environmental Health Sciences, MD: A3-03, 111 TW Alexander Dr, Research Triangle Park, NC 27709, USA. dliu@ciit.org', 'United States|United States|United States|United States', 15, 'Animals|Biological Clocks|Circadian Rhythm|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Heart|Liver|Mice|Models, Biological|Models, Statistical|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-87', '16504088', 'Recent circadian clock studies using gene expression microarray in two different tissues of mouse have revealed not all circadian-related genes are synchronized in phase or peak expression times across tissues in vivo. Instead, some circadian-related genes may be delayed by 4-8 hrs in peak expression in one tissue relative to the other. These interesting biological observations prompt a statistical question regarding how to distinguish the synchronized genes from genes that are systematically lagged in phase/peak expression time across two tissues.'),
(90750, 2006, 'bmc', 'Bias in error estimation when using cross-validation for model selection', 'Varma, Sudhir|Simon, Richard', 'Biometric Research Branch, National Cancer Institute, Bethesda, MD, USA. varmas@mail.nih.gov|Biometric Research Branch, National Cancer Institute, Bethesda, MD, USA. varmas@mail.nih.gov', 'United States|United States', 0, 'Algorithms|Artificial Intelligence|Bias|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-7-91', '16504092', 'Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error expected on independent data.'),
(90751, 2006, 'bmc', 'SIMMAP: stochastic character mapping of discrete traits on phylogenies', 'Bollback, Jonathan P', 'Bioinformatics Center, University of Copenhagen, Universitetsparken 15, Building 10, 2100 Copenhagen Ø, Denmark. bollback@binf.ku.dk', 'Denmark', 449, 'Animals|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|Humans|Models, Genetic|Models, Statistical|Phylogeny|Quantitative Trait Loci|Software|Stochastic Processes|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-88', '16504105', 'Character mapping on phylogenies has played an important, if not critical role, in our understanding of molecular, morphological, and behavioral evolution. Until very recently we have relied on parsimony to infer character changes. Parsimony has a number of serious limitations that are drawbacks to our understanding. Recent statistical methods have been developed that free us from these limitations enabling us to overcome the problems of parsimony by accommodating uncertainty in evolutionary time, ancestral states, and the phylogeny.'),
(90752, 2006, 'bmc', 'Various criteria in the evaluation of biomedical named entity recognition', 'Tsai, Richard Tzong-Han|Wu, Shih-Hung|Chou, Wen-Chi|Lin, Yu-Chun|He, Ding|Hsiang, Jieh|Sung, Ting-Yi|Hsu, Wen-Lian', 'Institute of Information Science, Academia Sinica, Nankang, Taipei 115, ROC, Taiwan. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, ROC, Taiwan. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, ROC, Taiwan. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, ROC, Taiwan. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, ROC, Taiwan. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, ROC, Taiwan. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, ROC, Taiwan. thtsai@iis.sinica.edu.tw|Institute of Information Science, Academia Sinica, Nankang, Taipei 115, ROC, Taiwan. thtsai@iis.sinica.edu.tw', '-|-|-|-|-|-|-|-', 0, 'Algorithms|Artificial Intelligence|Biology|Information Storage and Retrieval|Medicine|Natural Language Processing|Pattern Recognition, Automated|Terminology as Topic|Vocabulary, Controlled', 'Comparative Study', '10.1186/1471-2105-7-92', '16504116', 'Text mining in the biomedical domain is receiving increasing attention. A key component of this process is named entity recognition (NER). Generally speaking, two annotated corpora, GENIA and GENETAG, are most frequently used for training and testing biomedical named entity recognition (Bio-NER) systems. JNLPBA and BioCreAtIvE are two major Bio-NER tasks using these corpora. Both tasks take different approaches to corpus annotation and use different matching criteria to evaluate system performance. This paper details these differences and describes alternative criteria. We then examine the impact of different criteria and annotation schemes on system performance by retesting systems participated in the above two tasks.');
