INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91017, 2006, 'bmc', 'BBP: Brucella genome annotation with literature mining and curation', 'Xiang, Zuoshuang|Zheng, Wenjie|He, Yongqun', 'Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA. zxiang@umich.edu|Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA. zxiang@umich.edu|Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109, USA. zxiang@umich.edu', 'United States|United States|United States', 35, 'Algorithms|Brucella|Computational Biology|Databases, Bibliographic|Databases, Genetic|Genes, Bacterial|Genome|Genome, Bacterial|Genomics|Mutation|Programming Languages|Software|Virulence', 'Journal Article', '10.1186/1471-2105-7-347', '16842628', 'Brucella species are Gram-negative, facultative intracellular bacteria that cause brucellosis in humans and animals. Sequences of four Brucella genomes have been published, and various Brucella gene and genome data and analysis resources exist. A web gateway to integrate these resources will greatly facilitate Brucella research. Brucella genome data in current databases is largely derived from computational analysis without experimental validation typically found in peer-reviewed publications. It is partially due to the lack of a literature mining and curation system able to efficiently incorporate the large amount of literature data into genome annotation. It is further hypothesized that literature-based Brucella gene annotation would increase understanding of complicated Brucella pathogenesis mechanisms.'),
(91018, 2006, 'bmc', 'Integrated functional visualization of eukaryotic genomes', 'Ghai, Rohit|Lindemann, Hannes|Chakraborty, Trinad', 'Institute of Medical Microbiology, Faculty of Medicine, Justus-Liebig University, Frankfurter Strasse 107, 35392 - Giessen, Germany. Rohit.Ghai@mikrobio.med.uni-giessen.de|Institute of Medical Microbiology, Faculty of Medicine, Justus-Liebig University, Frankfurter Strasse 107, 35392 - Giessen, Germany. Rohit.Ghai@mikrobio.med.uni-giessen.de|Institute of Medical Microbiology, Faculty of Medicine, Justus-Liebig University, Frankfurter Strasse 107, 35392 - Giessen, Germany. Rohit.Ghai@mikrobio.med.uni-giessen.de', 'Germany|Germany|Germany', 2, 'Algorithms|Animals|Chromosome Mapping|Database Management Systems|Databases, Genetic|Genome|Humans|Information Storage and Retrieval|Natural Language Processing|Software|Structure-Activity Relationship|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-348', '16848887', 'Increasing amounts of data from large scale whole genome analysis efforts demands convenient tools for manipulation, visualization and investigation. Whole genome plots offer an intuitive window to the analysis. We describe two applications that enable users to easily plot and explore whole genome data from their own or other researchers experiments.'),
(91019, 2006, 'bmc', 'Simulation of microarray data with realistic characteristics', 'Nykter, Matti|Aho, Tommi|Ahdesmäki, Miika|Ruusuvuori, Pekka|Lehmussola, Antti|Yli-Harja, Olli', 'Institute of Signal Processing, Tampere University of Technology, Tampere, Finland. matti.nykter@tut.fi|Institute of Signal Processing, Tampere University of Technology, Tampere, Finland. matti.nykter@tut.fi|Institute of Signal Processing, Tampere University of Technology, Tampere, Finland. matti.nykter@tut.fi|Institute of Signal Processing, Tampere University of Technology, Tampere, Finland. matti.nykter@tut.fi|Institute of Signal Processing, Tampere University of Technology, Tampere, Finland. matti.nykter@tut.fi|Institute of Signal Processing, Tampere University of Technology, Tampere, Finland. matti.nykter@tut.fi', 'Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Algorithms|Computational Biology|Computer Simulation|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-7-349', '16848902', 'Microarray technologies have become common tools in biological research. As a result, a need for effective computational methods for data analysis has emerged. Numerous different algorithms have been proposed for analyzing the data. However, an objective evaluation of the proposed algorithms is not possible due to the lack of biological ground truth information. To overcome this fundamental problem, the use of simulated microarray data for algorithm validation has been proposed.'),
(91020, 2006, 'bmc', 'Genome BLAST distance phylogenies inferred from whole plastid and whole mitochondrion genome sequences', 'Auch, Alexander F|Henz, Stefan R|Holland, Barbara R|Göker, Markus', 'Center for Bioinformatics ZBIT, Sand 14, Tübingen, University of Tübingen, Germany. auch@informatik.uni-tuebingen.de|Center for Bioinformatics ZBIT, Sand 14, Tübingen, University of Tübingen, Germany. auch@informatik.uni-tuebingen.de|Center for Bioinformatics ZBIT, Sand 14, Tübingen, University of Tübingen, Germany. auch@informatik.uni-tuebingen.de|Center for Bioinformatics ZBIT, Sand 14, Tübingen, University of Tübingen, Germany. auch@informatik.uni-tuebingen.de', 'Germany|Germany|Germany|Germany', 45, 'Algorithms|Animals|Computational Biology|DNA, Chloroplast|DNA, Mitochondrial|Databases, Genetic|Genome|Humans|Phylogeny|Plastids|Regression Analysis|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-7-350', '16854218', 'Phylogenetic methods which do not rely on multiple sequence alignments are important tools in inferring trees directly from completely sequenced genomes. Here, we extend the recently described Genome BLAST Distance Phylogeny (GBDP) strategy to compute phylogenetic trees from all completely sequenced plastid genomes currently available and from a selection of mitochondrial genomes representing the major eukaryotic lineages. BLASTN, TBLASTX, or combinations of both are used to locate high-scoring segment pairs (HSPs) between two sequences from which pairwise similarities and distances are computed in different ways resulting in a total of 96 GBDP variants. The suitability of these distance formulae for phylogeny reconstruction is directly estimated by computing a recently described measure of treelikeness, the so-called delta value, from the respective distance matrices. Additionally, we compare the trees inferred from these matrices using UPGMA, NJ, BIONJ, FastME, or STC, respectively, with the NCBI taxonomy tree of the taxa under study.'),
(91021, 2006, 'bmc', 'MANET: tracing evolution of protein architecture in metabolic networks', 'Kim, Hee Shin|Mittenthal, Jay E|Caetano-Anollés, Gustavo', 'Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. heekim1@uiuc.edu|Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. heekim1@uiuc.edu|Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. heekim1@uiuc.edu', 'United States|United States|United States', 41, 'Computer Graphics|Database Management Systems|Databases, Protein|Evolution, Molecular|Information Storage and Retrieval|Proteins|Signal Transduction|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-351', '16854231', 'Cellular metabolism can be characterized by networks of enzymatic reactions and transport processes capable of supporting cellular life. Our aim is to find evolutionary patterns and processes embedded in the architecture and function of modern metabolism, using information derived from structural genomics.'),
(91022, 2006, 'bmc', 'Discovery of cancer vaccination protocols with a genetic algorithm driving an agent based simulator', 'Lollini, Pier-Luigi|Motta, Santo|Pappalardo, Francesco', 'Sezione di Cancerologia, Dipartimento di Patologia Sperimentale, University of Bologna, Italy. pierluigi.lollini@unibo.it|Sezione di Cancerologia, Dipartimento di Patologia Sperimentale, University of Bologna, Italy. pierluigi.lollini@unibo.it|Sezione di Cancerologia, Dipartimento di Patologia Sperimentale, University of Bologna, Italy. pierluigi.lollini@unibo.it', 'Italy|Italy|Italy', 0, 'Algorithms|Animals|Apoptosis|Cancer Vaccines|Cell Survival|Computer Simulation|Drug Therapy, Computer-Assisted|Expert Systems|Immunization Schedule|Mammary Neoplasms, Experimental|Mice|Models, Genetic|Models, Immunological|T-Lymphocytes|Treatment Outcome', 'Evaluation Studies', '10.1186/1471-2105-7-352', '16857043', 'Immunological prevention of cancer has been obtained in HER-2/neu transgenic mice using a vaccine that combines 3 different immune stimuli (Triplex vaccine) that is repeatedly administered for the entire lifespan of the host (Chronic protocol). Biological experiments leave open the question of whether the Chronic protocol is indeed the minimal vaccination schedule affording 100% protection, or whether shorter protocols could be applied that would result in the same efficacy. A biological solution would require an enormous number of experiments, each lasting at least one year. Therefore we approached this problem by developing a simulator (SimTriplex) which describes the immune response activated by Triplex vaccine. This simulator, tested against in vivo experiments on HER-2/neu mice, reproduces all the vaccination protocols used in the in vivo experiments. The simulator should describe any vaccination protocol within the tested range. A possible solution to the former open question using a minimal search strategy based on a genetic algorithm is presented. This is the first step toward a more general approach of biological or clinical constraints for the search of an effective vaccination schedule.'),
(91023, 2006, 'bmc', 'A powerful method for detecting differentially expressed genes from GeneChip arrays that does not require replicates', 'Hein, Anne-Mette K|Richardson, Sylvia', 'Dept. of Epidemiology and Public Health, Imperial College London, Norfolk Place, London, UK. a.hein@imperial.ac.uk|Dept. of Epidemiology and Public Health, Imperial College London, Norfolk Place, London, UK. a.hein@imperial.ac.uk', 'United Kingdom|United Kingdom', 11, 'Algorithms|Animals|Bayes Theorem|Gene Expression Profiling|Gene Expression Regulation|Genetic Techniques|Humans|Mice|Models, Statistical|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|RNA|ROC Curve', 'Journal Article', '10.1186/1471-2105-7-353', '16857053', 'Studies of differential expression that use Affymetrix GeneChip arrays are often carried out with a limited number of replicates. Reasons for this include financial considerations and limits on the available amount of RNA for sample preparation. In addition, failed hybridizations are not uncommon leading to a further reduction in the number of replicates available for analysis. Most existing methods for studying differential expression rely on the availability of replicates and the demand for alternative methods that require few or no replicates is high.'),
(91024, 2006, 'bmc', 'A combined approach to data mining of textual and structured data to identify cancer-related targets', 'Pospisil, Pavel|Iyer, Lakshmanan K|Adelstein, S James|Kassis, Amin I', 'Harvard Medical School, Department of Radiology, 200 Longwood Avenue, Boston, Massachusetts, USA. pavel_pospisil@hms.harvard.edu|Harvard Medical School, Department of Radiology, 200 Longwood Avenue, Boston, Massachusetts, USA. pavel_pospisil@hms.harvard.edu|Harvard Medical School, Department of Radiology, 200 Longwood Avenue, Boston, Massachusetts, USA. pavel_pospisil@hms.harvard.edu|Harvard Medical School, Department of Radiology, 200 Longwood Avenue, Boston, Massachusetts, USA. pavel_pospisil@hms.harvard.edu', 'United States|United States|United States|United States', 59, 'Biomarkers, Tumor|Database Management Systems|Databases, Protein|Drug Delivery Systems|Gene Targeting|Humans|Information Storage and Retrieval|Natural Language Processing|Neoplasm Proteins|Neoplasms|PubMed|Systems Integration', 'Journal Article', '10.1186/1471-2105-7-354', '16857057', 'We present an effective, rapid, systematic data mining approach for identifying genes or proteins related to a particular interest. A selected combination of programs exploring PubMed abstracts, universal gene/protein databases (UniProt, InterPro, NCBI Entrez), and state-of-the-art pathway knowledge bases (LSGraph and Ingenuity Pathway Analysis) was assembled to distinguish enzymes with hydrolytic activities that are expressed in the extracellular space of cancer cells. Proteins were identified with respect to six types of cancer occurring in the prostate, breast, lung, colon, ovary, and pancreas.'),
(91025, 2006, 'bmc', 'Functional clustering of yeast proteins from the protein-protein interaction network', 'Sen, Taner Z|Kloczkowski, Andrzej|Jernigan, Robert L', 'L.H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University Ames, IA 50011, USA. taner@iastate.edu|L.H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University Ames, IA 50011, USA. taner@iastate.edu|L.H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University Ames, IA 50011, USA. taner@iastate.edu', 'United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Computer Simulation|Gene Expression|Models, Biological|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1186/1471-2105-7-355', '16863590', 'The abundant data available for protein interaction networks have not yet been fully understood. New types of analyses are needed to reveal organizational principles of these networks to investigate the details of functional and regulatory clusters of proteins.'),
(91026, 2006, 'bmc', 'New directions in biomedical text annotation: definitions, guidelines and corpus construction', 'Wilbur, W John|Rzhetsky, Andrey|Shatkay, Hagit', 'National Center for Biotechnology Information NLM, NIH, Bethesda, MD, USA. wilbur@ncbi.nlm.nih.gov|National Center for Biotechnology Information NLM, NIH, Bethesda, MD, USA. wilbur@ncbi.nlm.nih.gov|National Center for Biotechnology Information NLM, NIH, Bethesda, MD, USA. wilbur@ncbi.nlm.nih.gov', 'United States|United States|United States', 88, 'Computational Biology|Guidelines as Topic|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-7-356', '16867190', 'While biomedical text mining is emerging as an important research area, practical results have proven difficult to achieve. We believe that an important first step towards more accurate text-mining lies in the ability to identify and characterize text that satisfies various types of information needs. We report here the results of our inquiry into properties of scientific text that have sufficient generality to transcend the confines of a narrow subject area, while supporting practical mining of text for factual information. Our ultimate goal is to annotate a significant corpus of biomedical text and train machine learning methods to automatically categorize such text along certain dimensions that we have defined.'),
(91027, 2006, 'bmc', 'Improved alignment quality by combining evolutionary information, predicted secondary structure and self-organizing maps', 'Ohlson, Tomas|Aggarwal, Varun|Elofsson, Arne|MacCallum, Robert M', 'Stockholm Bioinformatics Center, Stockholm University, SE-106 91 Stockholm, Sweden. tomasoh@sbc.su.se|Stockholm Bioinformatics Center, Stockholm University, SE-106 91 Stockholm, Sweden. tomasoh@sbc.su.se|Stockholm Bioinformatics Center, Stockholm University, SE-106 91 Stockholm, Sweden. tomasoh@sbc.su.se|Stockholm Bioinformatics Center, Stockholm University, SE-106 91 Stockholm, Sweden. tomasoh@sbc.su.se', 'Sweden|Sweden|Sweden|Sweden', 10, 'Computational Biology|Databases, Protein|Evolution, Molecular|Forecasting|Neural Networks (Computer)|Protein Structure, Secondary|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-7-357', '16869963', 'Protein sequence alignment is one of the basic tools in bioinformatics. Correct alignments are required for a range of tasks including the derivation of phylogenetic trees and protein structure prediction. Numerous studies have shown that the incorporation of predicted secondary structure information into alignment algorithms improves their performance. Secondary structure predictors have to be trained on a set of somewhat arbitrarily defined states (e.g. helix, strand, coil), and it has been shown that the choice of these states has some effect on alignment quality. However, it is not unlikely that prediction of other structural features also could provide an improvement. In this study we use an unsupervised clustering method, the self-organizing map, to assign sequence profile windows to structural states and assess their use in sequence alignment.'),
(91028, 2006, 'bmc', 'Identification of biomarkers from mass spectrometry data using a common peak approach', 'Fushiki, Tadayoshi|Fujisawa, Hironori|Eguchi, Shinto', 'Department of Mathematical Analysis and Statistical Inference, Institute of Statistical Mathematics, Tokyo, Japan. fushiki@ism.ac.jp|Department of Mathematical Analysis and Statistical Inference, Institute of Statistical Mathematics, Tokyo, Japan. fushiki@ism.ac.jp|Department of Mathematical Analysis and Statistical Inference, Institute of Statistical Mathematics, Tokyo, Japan. fushiki@ism.ac.jp', 'Japan|Japan|Japan', 31, 'Algorithms|Biomarkers, Tumor|Computational Biology|Female|Gene Expression Regulation, Neoplastic|Humans|Mass Spectrometry|Models, Statistical|Neoplasm Proteins|Ovarian Neoplasms|Protein Array Analysis|Proteome|Proteomics|Software', 'Journal Article', '10.1186/1471-2105-7-358', '16869977', 'Proteomic data obtained from mass spectrometry have attracted great interest for the detection of early-stage cancer. However, as mass spectrometry data are high-dimensional, identification of biomarkers is a key problem.'),
(91029, 2006, 'bmc', 'Comparison and evaluation of methods for generating differentially expressed gene lists from microarray data', 'Jeffery, Ian B|Higgins, Desmond G|Culhane, Aedín C', 'Bioinformatics, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Ian.Jeffery@ucd.ie|Bioinformatics, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Ian.Jeffery@ucd.ie|Bioinformatics, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. Ian.Jeffery@ucd.ie', 'Ireland|Ireland|Ireland', 257, 'Algorithms|Cell Line, Tumor|Computational Biology|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|ROC Curve|Sample Size', 'Comparative Study', '10.1186/1471-2105-7-359', '16872483', 'Numerous feature selection methods have been applied to the identification of differentially expressed genes in microarray data. These include simple fold change, classical t-statistic and moderated t-statistics. Even though these methods return gene lists that are often dissimilar, few direct comparisons of these exist. We present an empirical study in which we compare some of the most commonly used feature selection methods. We apply these to 9 publicly available datasets, and compare, both the gene lists produced and how these perform in class prediction of test datasets.'),
(91030, 2006, 'bmc', 'A direct comparison of protein interaction confidence assignment schemes', 'Suthram, Silpa|Shlomi, Tomer|Ruppin, Eytan|Sharan, Roded|Ideker, Trey', 'Department of Bioengineering, University of California, San Diego, CA 92093, USA. ssuthram@ucsd.edu|Department of Bioengineering, University of California, San Diego, CA 92093, USA. ssuthram@ucsd.edu|Department of Bioengineering, University of California, San Diego, CA 92093, USA. ssuthram@ucsd.edu|Department of Bioengineering, University of California, San Diego, CA 92093, USA. ssuthram@ucsd.edu|Department of Bioengineering, University of California, San Diego, CA 92093, USA. ssuthram@ucsd.edu', 'United States|United States|United States|United States|United States', 91, 'Caenorhabditis elegans Proteins|Databases, Protein|Drosophila Proteins|Protein Binding|Protein Interaction Mapping|Proteomics|Reproducibility of Results|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1186/1471-2105-7-360', '16872496', 'Recent technological advances have enabled high-throughput measurements of protein-protein interactions in the cell, producing large protein interaction networks for various species at an ever-growing pace. However, common technologies like yeast two-hybrid may experience high rates of false positive detection. To combat false positive discoveries, a number of different methods have been recently developed that associate confidence scores with protein interactions. Here, we perform a rigorous comparative analysis and performance assessment among these different methods.'),
(91031, 2006, 'bmc', 'Cluster analysis for DNA methylation profiles having a detection threshold', 'Marjoram, Paul|Chang, Jing|Laird, Peter W|Siegmund, Kimberly D', 'Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. pmarjora@usc.edu|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. pmarjora@usc.edu|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. pmarjora@usc.edu|Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA. pmarjora@usc.edu', 'United States|United States|United States|United States', 6, 'Artificial Intelligence|Base Sequence|Cluster Analysis|DNA Methylation|Differential Threshold|Gene Expression Profiling|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-7-361', '16872497', 'DNA methylation, a molecular feature used to investigate tumor heterogeneity, can be measured on many genomic regions using the MethyLight technology. Due to the combination of the underlying biology of DNA methylation and the MethyLight technology, the measurements, while being generated on a continuous scale, have a large number of 0 values. This suggests that conventional clustering methodology may not perform well on this data.'),
(91032, 2006, 'bmc', 'A fast SCOP fold classification system using content-based E-Predict algorithm', 'Chi, Pin-Hao|Shyu, Chi-Ren|Xu, Dong', 'Medical and Biological Digital Library Research Lab, Department of Computer Science, University of Missouri, Columbia, MO 65211, USA. pinhao@diglib1.cecs.missouri.edu|Medical and Biological Digital Library Research Lab, Department of Computer Science, University of Missouri, Columbia, MO 65211, USA. pinhao@diglib1.cecs.missouri.edu|Medical and Biological Digital Library Research Lab, Department of Computer Science, University of Missouri, Columbia, MO 65211, USA. pinhao@diglib1.cecs.missouri.edu', 'United States|United States|United States', 12, 'Algorithms|Artificial Intelligence|Databases, Protein|Models, Molecular|Pattern Recognition, Automated|Protein Conformation|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structural Homology, Protein|Vocabulary, Controlled', 'Comparative Study', '10.1186/1471-2105-7-362', '16872501', 'Domain experts manually construct the Structural Classification of Protein (SCOP) database to categorize and compare protein structures. Even though using the SCOP database is believed to be more reliable than classification results from other methods, it is labor intensive. To mimic human classification processes, we develop an automatic SCOP fold classification system to assign possible known SCOP folds and recognize novel folds for newly-discovered proteins.'),
(91033, 2006, 'bmc', 'A literature-based similarity metric for biological processes', 'Chagoyen, Monica|Carmona-Saez, Pedro|Gil, Concha|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', 12, 'Databases, Bibliographic|Databases, Genetic|Genes, Fungal|Ion Transport|Natural Language Processing|Pattern Recognition, Automated|Physiological Phenomena|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Comparative Study', '10.1186/1471-2105-7-363', '16872502', 'Recent analyses in systems biology pursue the discovery of functional modules within the cell. Recognition of such modules requires the integrative analysis of genome-wide experimental data together with available functional schemes. In this line, methods to bridge the gap between the abstract definitions of cellular processes in current schemes and the interlinked nature of biological networks are required.'),
(91034, 2006, 'bmc', 'Improving the quality of protein structure models by selecting from alignment alternatives', 'Sommer, Ingolf|Toppo, Stefano|Sander, Oliver|Lengauer, Thomas|Tosatto, Silvio C E', 'Department of Computational Biology and Applied Algorithmics, Max-Planck-lnstitute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. sommer@mpi-sb.mpg.de|Department of Computational Biology and Applied Algorithmics, Max-Planck-lnstitute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. sommer@mpi-sb.mpg.de|Department of Computational Biology and Applied Algorithmics, Max-Planck-lnstitute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. sommer@mpi-sb.mpg.de|Department of Computational Biology and Applied Algorithmics, Max-Planck-lnstitute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. sommer@mpi-sb.mpg.de|Department of Computational Biology and Applied Algorithmics, Max-Planck-lnstitute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. sommer@mpi-sb.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 17, 'Computer Simulation|Databases, Protein|Models, Molecular|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-7-364', '16872519', 'In the area of protein structure prediction, recently a lot of effort has gone into the development of Model Quality Assessment Programs (MQAPs). MQAPs distinguish high quality protein structure models from inferior models. Here, we propose a new method to use an MQAP to improve the quality of models. With a given target sequence and template structure, we construct a number of different alignments and corresponding models for the sequence. The quality of these models is scored with an MQAP and used to choose the most promising model. An SVM-based selection scheme is suggested for combining MQAP partial potentials, in order to optimize for improved model selection.'),
(91035, 2006, 'bmc', 'PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs', 'Pitre, Sylvain|Dehne, Frank|Chan, Albert|Cheetham, Jim|Duong, Alex|Emili, Andrew|Gebbia, Marinella|Greenblatt, Jack|Jessulat, Mathew|Krogan, Nevan|Luo, Xuemei|Golshani, Ashkan', 'School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com|School of Computer Science, Carleton University, Ottawa, Canada. sylverbullit@hotmail.com', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 121, 'Algorithms|Base Sequence|Computational Biology|Molecular Sequence Data|Peptides|Protein Interaction Mapping|Proteins|Proteomics|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sensitivity and Specificity|Software|Two-Hybrid System Techniques', 'Journal Article', '10.1186/1471-2105-7-365', '16872538', 'Identification of protein interaction networks has received considerable attention in the post-genomic era. The currently available biochemical approaches used to detect protein-protein interactions are all time and labour intensive. Consequently there is a growing need for the development of computational tools that are capable of effectively identifying such interactions.'),
(91036, 2006, 'bmc', 'bioNMF: a versatile tool for non-negative matrix factorization in biology', 'Pascual-Montano, Alberto|Carmona-Saez, Pedro|Chagoyen, Monica|Tirado, Francisco|Carazo, Jose M|Pascual-Marqui, Roberto D', 'Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, 28040, Spain. pascual@fis.ucm.es|Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, 28040, Spain. pascual@fis.ucm.es|Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, 28040, Spain. pascual@fis.ucm.es|Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, 28040, Spain. pascual@fis.ucm.es|Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, 28040, Spain. pascual@fis.ucm.es|Computer Architecture Department, Facultad de Ciencias Físicas, Universidad Complutense de Madrid, 28040, Spain. pascual@fis.ucm.es', 'Spain|Spain|Spain|Spain|Spain|Spain', 64, 'Algorithms|Animals|Cluster Analysis|Computational Biology|Computer Graphics|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Genetic|Pattern Recognition, Automated|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-366', '16875499', 'In the Bioinformatics field, a great deal of interest has been given to Non-negative matrix factorization technique (NMF), due to its capability of providing new insights and relevant information about the complex latent relationships in experimental data sets. This method, and some of its variants, has been successfully applied to gene expression, sequence analysis, functional characterization of genes and text mining. Even if the interest on this technique by the bioinformatics community has been increased during the last few years, there are not many available simple standalone tools to specifically perform these types of data analysis in an integrated environment.'),
(91037, 2006, 'bmc', 'Prediction of a key role of motifs binding E2F and NR2F in down-regulation of numerous genes during the development of the mouse hippocampus', 'Dabrowski, Michal|Aerts, Stein|Kaminska, Bozena', 'Laboratory of Transcription Regulation, Department of Cell Biology, The Nencki Institute of Experimental Biology, Pasteura 3, 02-093 Warsaw, Poland. m.dabrowski@nencki.gov.pl|Laboratory of Transcription Regulation, Department of Cell Biology, The Nencki Institute of Experimental Biology, Pasteura 3, 02-093 Warsaw, Poland. m.dabrowski@nencki.gov.pl|Laboratory of Transcription Regulation, Department of Cell Biology, The Nencki Institute of Experimental Biology, Pasteura 3, 02-093 Warsaw, Poland. m.dabrowski@nencki.gov.pl', 'Poland|Poland|Poland', 5, 'Amino Acid Motifs|Amino Acid Sequence|Animals|Binding Sites|COUP Transcription Factors|Cell Differentiation|Computational Biology|Down-Regulation|E2F Transcription Factors|Gene Expression Profiling|Gene Expression Regulation, Developmental|Hippocampus|Humans|Mice|Myoblasts|Protein Binding|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-7-367', '16884529', 'We previously demonstrated that gene expression profiles during neuronal differentiation in vitro and hippocampal development in vivo were very similar, due to a conservation of the important second singular value decomposition (SVD) mode (Mode 2) of expression. The conservation of Mode 2 suggests that it reflects a regulatory mechanism conserved between the two systems. In either dataset, the expression vectors of all the genes form two large clusters that differ in the sign of the contribution of Mode 2, which for the majority of them reflects the difference between down- or up-regulation.'),
(91038, 2006, 'bmc', 'G-InforBIO: integrated system for microbial genomics', 'Tanaka, Naoto|Abe, Takashi|Miyazaki, Satoru|Sugawara, Hideaki', 'Center for Information Biology and DDBJ, National Institute of Genetics 1111 Yata, Mishima, Shizuoka 411-8540, Japan. natanaka@lab.nig.ac.jp|Center for Information Biology and DDBJ, National Institute of Genetics 1111 Yata, Mishima, Shizuoka 411-8540, Japan. natanaka@lab.nig.ac.jp|Center for Information Biology and DDBJ, National Institute of Genetics 1111 Yata, Mishima, Shizuoka 411-8540, Japan. natanaka@lab.nig.ac.jp|Center for Information Biology and DDBJ, National Institute of Genetics 1111 Yata, Mishima, Shizuoka 411-8540, Japan. natanaka@lab.nig.ac.jp', 'Japan|Japan|Japan|Japan', 7, 'Algorithms|Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Genetic|Genome, Bacterial|Genomics|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-368', '16887044', 'Genome databases contain diverse kinds of information, including gene annotations and nucleotide and amino acid sequences. It is not easy to integrate such information for genomic study. There are few tools for integrated analyses of genomic data, therefore, we developed software that enables users to handle, manipulate, and analyze genome data with a variety of sequence analysis programs.'),
(91039, 2006, 'bmc', 'Robust computational reconstitution - a new method for the comparative analysis of gene expression in tissues and isolated cell fractions', 'Hoffmann, Martin|Pohlers, Dirk|Koczan, Dirk|Thiesen, Hans-Jürgen|Wölfl, Stefan|Kinne, Raimund W', 'Leibniz Institute for Natural Products Research and Infection Biology - Hans Knöll Institute, Beutenbergstr, 11a, Jena, Germany. martin.hoffmann@hki-jena.de|Leibniz Institute for Natural Products Research and Infection Biology - Hans Knöll Institute, Beutenbergstr, 11a, Jena, Germany. martin.hoffmann@hki-jena.de|Leibniz Institute for Natural Products Research and Infection Biology - Hans Knöll Institute, Beutenbergstr, 11a, Jena, Germany. martin.hoffmann@hki-jena.de|Leibniz Institute for Natural Products Research and Infection Biology - Hans Knöll Institute, Beutenbergstr, 11a, Jena, Germany. martin.hoffmann@hki-jena.de|Leibniz Institute for Natural Products Research and Infection Biology - Hans Knöll Institute, Beutenbergstr, 11a, Jena, Germany. martin.hoffmann@hki-jena.de|Leibniz Institute for Natural Products Research and Infection Biology - Hans Knöll Institute, Beutenbergstr, 11a, Jena, Germany. martin.hoffmann@hki-jena.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 8, 'Arthritis, Rheumatoid|Fibroblasts|Gene Expression Profiling|Humans|Immunohistochemistry|Macrophages|Mathematical Computing|Models, Biological|Osteoarthritis|RNA, Messenger|Synovial Membrane', 'Comparative Study', '10.1186/1471-2105-7-369', '16889662', 'Biological tissues consist of various cell types that differentially contribute to physiological and pathophysiological processes. Determining and analyzing cell type-specific gene expression under diverse conditions is therefore a central aim of biomedical research. The present study compares gene expression profiles in whole tissues and isolated cell fractions purified from these tissues in patients with rheumatoid arthritis and osteoarthritis.'),
(91040, 2006, 'bmc', 'Automatic document classification of biological literature', 'Chen, David|Müller, Hans-Michael|Sternberg, Paul W', 'Division of Biology and Howard Hughes Medical Institute, California Institute of Technology, Pasadena, California, USA. davidc@caltech.edu|Division of Biology and Howard Hughes Medical Institute, California Institute of Technology, Pasadena, California, USA. davidc@caltech.edu|Division of Biology and Howard Hughes Medical Institute, California Institute of Technology, Pasadena, California, USA. davidc@caltech.edu', 'United States|United States|United States', 31, 'Abstracting and Indexing as Topic|Algorithms|Animals|Caenorhabditis elegans|Cluster Analysis|Databases, Bibliographic|Information Storage and Retrieval|Publications|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-370', '16893465', 'Document classification is a wide-spread problem with many applications, from organizing search engine snippets to spam filtering. We previously described Textpresso, a text-mining system for biological literature, which marks up full text according to a shallow ontology that includes terms of biological interest. This project investigates document classification in the context of biological literature, making use of the Textpresso markup of a corpus of Caenorhabditis elegans literature.'),
(91041, 2006, 'bmc', 'UniFrac--an online tool for comparing microbial community diversity in a phylogenetic context', 'Lozupone, Catherine|Hamady, Micah|Knight, Rob', 'Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, CO 80309, USA. lozupone@colorado.edu|Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, CO 80309, USA. lozupone@colorado.edu|Department of Molecular, Cellular, and Developmental Biology, University of Colorado, Boulder, CO 80309, USA. lozupone@colorado.edu', 'United States|United States|United States', 1041, 'Bacteria|Cluster Analysis|Computational Biology|Ecosystem|Environmental Microbiology|Genetic Variation|Internet|Phylogeny|RNA, Ribosomal, 16S', 'Comparative Study', '10.1186/1471-2105-7-371', '16893466', 'Moving beyond pairwise significance tests to compare many microbial communities simultaneously is critical for understanding large-scale trends in microbial ecology and community assembly. Techniques that allow microbial communities to be compared in a phylogenetic context are rapidly gaining acceptance, but the widespread application of these techniques has been hindered by the difficulty of performing the analyses.'),
(91042, 2006, 'bmc', 'Gene and protein nomenclature in public databases', 'Fundel, Katrin|Zimmer, Ralf', 'Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. katrin.fundel@bio.ifi.lmu.de|Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. katrin.fundel@bio.ifi.lmu.de', 'Germany|Germany', 36, 'Abstracting and Indexing as Topic|Animals|Databases, Genetic|Databases, Protein|Dictionaries as Topic|Genes|Humans|Information Storage and Retrieval|Mice|Proteins|Rats|Reproducibility of Results|Terminology as Topic|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-372', '16899134', 'Frequently, several alternative names are in use for biological objects such as genes and proteins. Applications like manual literature search, automated text-mining, named entity identification, gene/protein annotation, and linking of knowledge from different information sources require the knowledge of all used names referring to a given gene or protein. Various organism-specific or general public databases aim at organizing knowledge about genes and proteins. These databases can be used for deriving gene and protein name dictionaries. So far, little is known about the differences between databases in terms of size, ambiguities and overlap.'),
(91043, 2006, 'bmc', 'Text mining of full-text journal articles combined with gene expression analysis reveals a relationship between sphingosine-1-phosphate and invasiveness of a glioblastoma cell line', 'Natarajan, Jeyakumar|Berrar, Daniel|Dubitzky, Werner|Hack, Catherine|Zhang, Yonghong|DeSesa, Catherine|Van Brocklyn, James R|Bremer, Eric G', 'School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. j.natarajan@ulster.ac.uk|School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. j.natarajan@ulster.ac.uk|School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. j.natarajan@ulster.ac.uk|School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. j.natarajan@ulster.ac.uk|School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. j.natarajan@ulster.ac.uk|School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. j.natarajan@ulster.ac.uk|School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. j.natarajan@ulster.ac.uk|School of Biomedical Sciences, University of Ulster at Coleraine, Cromore Road, Northern Ireland, UK. j.natarajan@ulster.ac.uk', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 47, 'Cell Line, Tumor|Data Interpretation, Statistical|Databases, Bibliographic|Epidermal Growth Factor|Gene Expression Regulation, Neoplastic|Glioblastoma|Humans|Lysophospholipids|Matrix Metalloproteinase 9|Neoplasm Invasiveness|Neovascularization, Pathologic|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Sphingosine', 'Journal Article', '10.1186/1471-2105-7-373', '16901352', 'Sphingosine 1-phosphate (S1P), a lysophospholipid, is involved in various cellular processes such as migration, proliferation, and survival. To date, the impact of S1P on human glioblastoma is not fully understood. Particularly, the concerted role played by matrix metalloproteinases (MMP) and S1P in aggressive tumor behavior and angiogenesis remains to be elucidated.'),
(91044, 2006, 'bmc', 'Genome comparison using Gene Ontology (GO) with statistical testing', 'Cai, Zhaotao|Mao, Xizeng|Li, Songgang|Wei, Liping', 'Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, PR China. cait@mail.cbi.pku.edu.cn|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, PR China. cait@mail.cbi.pku.edu.cn|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, PR China. cait@mail.cbi.pku.edu.cn|Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, PR China. cait@mail.cbi.pku.edu.cn', 'China|China|China|China', 0, 'Anabaena|Animals|Computational Biology|Data Interpretation, Statistical|Databases, Protein|Genome|Humans|Mice|Models, Statistical|Saccharomyces cerevisiae|Schizosaccharomyces|Sequence Analysis, DNA|Software|Synechocystis', 'Journal Article', '10.1186/1471-2105-7-374', '16901353', 'Automated comparison of complete sets of genes encoded in two genomes can provide insight on the genetic basis of differences in biological traits between species. Gene ontology (GO) is used as a common vocabulary to annotate genes for comparison. Current approaches calculate the fold of unweighted or weighted differences between two species at the high-level GO functional categories. However, to ensure the reliability of the differences detected, it is important to evaluate their statistical significance. It is also useful to search for differences at all levels of GO.'),
(91045, 2006, 'bmc', 'PeanutMap: an online genome database for comparative molecular maps of peanut', 'Jesubatham, Arun M|Burow, Mark D', 'Department of Computer Science, Texas Tech University, Lubbock, TX 79409, USA. arunmoses99@yahoo.com|Department of Computer Science, Texas Tech University, Lubbock, TX 79409, USA. arunmoses99@yahoo.com', 'United States|United States', 0, 'Arachis|Chromosome Mapping|Chromosomes, Plant|Computational Biology|Databases, Genetic|Genetic Linkage|Genome, Plant|Internet|Microsatellite Repeats|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-7-375', '16904007', 'Molecular maps have been developed for many species, and are of particular importance for varietal development and comparative genomics. However, despite the existence of multiple sets of linkage maps, databases of these data are lacking for many species, including peanut.'),
(91046, 2006, 'bmc', 'Detecting the limits of regulatory element conservation and divergence estimation using pairwise and multiple alignments', 'Pollard, Daniel A|Moses, Alan M|Iyer, Venky N|Eisen, Michael B', 'Graduate Group in Biophysics, University of California, Berkeley, CA 94720, USA. dpollard@berkeley.edu|Graduate Group in Biophysics, University of California, Berkeley, CA 94720, USA. dpollard@berkeley.edu|Graduate Group in Biophysics, University of California, Berkeley, CA 94720, USA. dpollard@berkeley.edu|Graduate Group in Biophysics, University of California, Berkeley, CA 94720, USA. dpollard@berkeley.edu', 'United States|United States|United States|United States', 0, 'Binding Sites|Evolution, Molecular|Models, Genetic|Regulatory Elements, Transcriptional|Sequence Alignment|Sequence Analysis, DNA|Species Specificity', 'Comparative Study', '10.1186/1471-2105-7-376', '16904011', 'Molecular evolutionary studies of noncoding sequences rely on multiple alignments. Yet how multiple alignment accuracy varies across sequence types, tree topologies, divergences and tools, and further how this variation impacts specific inferences, remains unclear.'),
(91047, 2006, 'bmc', 'A novel data mining method to identify assay-specific signatures in functional genomic studies', 'Rollins, Derrick K|Zhai, Dongmei|Joe, Alrica L|Guidarelli, Jack W|Murarka, Abhishek|Gonzalez, Ramon', 'Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, USA. drollins@iastate.edu|Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, USA. drollins@iastate.edu|Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, USA. drollins@iastate.edu|Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, USA. drollins@iastate.edu|Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, USA. drollins@iastate.edu|Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, USA. drollins@iastate.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Biological Assay|Chromosome Mapping|Databases, Genetic|Gene Expression Profiling|Genomics|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Principal Component Analysis', 'Journal Article', '10.1186/1471-2105-7-377', '16907975', 'The highly dimensional data produced by functional genomic (FG) studies makes it difficult to visualize relationships between gene products and experimental conditions (i.e., assays). Although dimensionality reduction methods such as principal component analysis (PCA) have been very useful, their application to identify assay-specific signatures has been limited by the lack of appropriate methodologies. This article proposes a new and powerful PCA-based method for the identification of assay-specific gene signatures in FG studies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91048, 2006, 'bmc', 'Comprehensive quality control utilizing the prehybridization third-dye image leads to accurate gene expression measurements by cDNA microarrays', 'Wang, Xujing|Jia, Shuang|Meyer, Lisa|Xiang, Bixia|Chen, Li-Yen|Jiang, Nan|Moreno, Carol|Jacob, Howard J|Ghosh, Soumitra|Hessner, Martin J', 'The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu|The Max McGee National Research Center for Juvenile Diabetes, Department of Pediatrics, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA. xujing@mcw.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 8, 'Animals|Fluorescent Dyes|Gene Expression Profiling|Liver|Oligonucleotide Array Sequence Analysis|Quality Control|RNA|Rats|Reproducibility of Results|Reverse Transcriptase Polymerase Chain Reaction', 'Journal Article', '10.1186/1471-2105-7-378', '16907976', 'Gene expression profiling using microarrays has become an important genetic tool. Spotted arrays prepared in academic labs have the advantage of low cost and high design and content flexibility, but are often limited by their susceptibility to quality control (QC) issues. Previously, we have reported a novel 3-color microarray technology that enabled array fabrication QC. In this report we further investigated its advantage in spot-level data QC.'),
(91049, 2006, 'bmc', 'V-MitoSNP: visualization of human mitochondrial SNPs', 'Chuang, Li-Yeh|Yang, Cheng-Hong|Cheng, Yu-Huei|Gu, De-Leung|Chang, Phei-Lang|Tsui, Ke-Hung|Chang, Hsueh-Wei', 'Department of Chemical Engineering, I-Shou University, 840, Taiwan. chuang@isu.edu.tw|Department of Chemical Engineering, I-Shou University, 840, Taiwan. chuang@isu.edu.tw|Department of Chemical Engineering, I-Shou University, 840, Taiwan. chuang@isu.edu.tw|Department of Chemical Engineering, I-Shou University, 840, Taiwan. chuang@isu.edu.tw|Department of Chemical Engineering, I-Shou University, 840, Taiwan. chuang@isu.edu.tw|Department of Chemical Engineering, I-Shou University, 840, Taiwan. chuang@isu.edu.tw|Department of Chemical Engineering, I-Shou University, 840, Taiwan. chuang@isu.edu.tw', '-|-|-|-|-|-|-', 19, 'Base Sequence|Computational Biology|DNA, Mitochondrial|Databases, Genetic|Genotype|Humans|Information Storage and Retrieval|Molecular Sequence Data|Polymorphism, Restriction Fragment Length|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-379', '16907992', 'Mitochondrial single nucleotide polymorphisms (mtSNPs) constitute important data when trying to shed some light on human diseases and cancers. Unfortunately, providing relevant mtSNP genotyping information in mtDNA databases in a neatly organized and transparent visual manner still remains a challenge. Amongst the many methods reported for SNP genotyping, determining the restriction fragment length polymorphisms (RFLPs) is still one of the most convenient and cost-saving methods. In this study, we prepared the visualization of the mtDNA genome in a way, which integrates the RFLP genotyping information with mitochondria related cancers and diseases in a user-friendly, intuitive and interactive manner. The inherent problem associated with mtDNA sequences in BLAST of the NCBI database was also solved.'),
(91050, 2006, 'bmc', 'Validation and functional annotation of expression-based clusters based on gene ontology', 'Steuer, Ralf|Humburg, Peter|Selbig, Joachim', 'University Potsdam, Institute for Biochemistry and Biology, Karl-Liebknecht-Strasse 24-25, Haus 20, 14476 Potsdam, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Institute for Biochemistry and Biology, Karl-Liebknecht-Strasse 24-25, Haus 20, 14476 Potsdam, Germany. steuer@agnld.uni-potsdam.de|University Potsdam, Institute for Biochemistry and Biology, Karl-Liebknecht-Strasse 24-25, Haus 20, 14476 Potsdam, Germany. steuer@agnld.uni-potsdam.de', 'Germany|Germany|Germany', 0, 'Algorithms|Biotechnology|Cluster Analysis|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Models, Genetic|Pattern Recognition, Automated|Proteins|Reproducibility of Results', 'Comparative Study', '10.1186/1471-2105-7-380', '16911788', 'The biological interpretation of large-scale gene expression data is one of the paramount challenges in current bioinformatics. In particular, placing the results in the context of other available functional genomics data, such as existing bio-ontologies, has already provided substantial improvement for detecting and categorizing genes of interest. One common approach is to look for functional annotations that are significantly enriched within a group or cluster of genes, as compared to a reference group.'),
(91051, 2006, 'bmc', 'Modelling the network of cell cycle transcription factors in the yeast Saccharomyces cerevisiae', 'Cokus, Shawn|Rose, Sherri|Haynor, David|Grønbech-Jensen, Niels|Pellegrini, Matteo', 'Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, USA. cokus@mcdb.ucla.edu|Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, USA. cokus@mcdb.ucla.edu|Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, USA. cokus@mcdb.ucla.edu|Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, USA. cokus@mcdb.ucla.edu|Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, USA. cokus@mcdb.ucla.edu', 'United States|United States|United States|United States|United States', 0, 'Cell Cycle Proteins|Computer Simulation|Gene Expression Regulation, Fungal|Models, Biological|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-7-381', '16914048', 'Reverse-engineering regulatory networks is one of the central challenges for computational biology. Many techniques have been developed to accomplish this by utilizing transcription factor binding data in conjunction with expression data. Of these approaches, several have focused on the reconstruction of the cell cycle regulatory network of Saccharomyces cerevisiae. The emphasis of these studies has been to model the relationships between transcription factors and their target genes. In contrast, here we focus on reverse-engineering the network of relationships among transcription factors that regulate the cell cycle in S. cerevisiae.'),
(91052, 2006, 'bmc', 'MultiSeq: unifying sequence and structure data for evolutionary analysis', 'Roberts, Elijah|Eargle, John|Wright, Dan|Luthey-Schulten, Zaida', 'Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA. erobert3@scs.uiuc.edu|Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA. erobert3@scs.uiuc.edu|Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA. erobert3@scs.uiuc.edu|Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA. erobert3@scs.uiuc.edu', 'United States|United States|United States|United States', 253, 'Algorithms|Computational Biology|Computer Graphics|Computer Simulation|DNA|Databases, Genetic|Evolution, Molecular|Models, Molecular|Nucleic Acid Conformation|Phylogeny|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Nucleic Acid|Software|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-7-382', '16914055', 'Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data, information visualization to assist in recognizing correlations, mathematics to formulate statistical inferences, and biology to analyze chemical and physical properties in terms of sequence and structure changes.'),
(91053, 2006, 'bmc', 'Laboratory Information Management Software for genotyping workflows: applications in high throughput crop genotyping', 'Jayashree, B|Reddy, Praveen T|Leeladevi, Y|Crouch, Jonathan H|Mahalakshmi, V|Buhariwalla, Hutokshi K|Eshwar, K E|Mace, Emma|Folksterma, Rolf|Senthilvel, S|Varshney, Rajeev K|Seetha, K|Rajalakshmi, R|Prasanth, V P|Chandra, Subhash|Swarupa, L|Srikalyani, P|Hoisington, David A', 'Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org|Bioinformatics and Biometrics Unit, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India. b.jayashree@cgiar.org', 'India|India|India|India|India|India|India|India|India|India|India|India|India|India|India|India|Indi', 19, 'Algorithms|Base Sequence|Crops, Agricultural|DNA, Plant|Database Management Systems|Databases, Genetic|Genotype|Information Management|Information Storage and Retrieval|Laboratories|Molecular Sequence Data|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-383', '16914063', 'With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow.'),
(91054, 2006, 'bmc', 'Analysis of promoter regions of co-expressed genes identified by microarray analysis', 'Veerla, Srinivas|Höglund, Mattias', 'Department of Clinical Genetics, Lund University Hospital, SE-22185 Lund, Sweden. srinivas.veerla@med.lu.se|Department of Clinical Genetics, Lund University Hospital, SE-22185 Lund, Sweden. srinivas.veerla@med.lu.se', 'Sweden|Sweden', 0, 'Acute Disease|Animals|Cluster Analysis|Computational Biology|Databases, Genetic|Gene Expression|Humans|Leukemia, Myeloid|Mice|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-7-384', '16916454', 'The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biological processes. A logical and systematic approach to study co-expressed genes is to analyze their promoter sequences to identify transcription factors that may be involved in establishing specific profiles and that may be experimentally investigated.'),
(91055, 2006, 'bmc', 'Incorporating background frequency improves entropy-based residue conservation measures', 'Wang, Kai|Samudrala, Ram', 'Computational Genomics Group, Department of Microbiology, University of Washington, USA. dna@u.washington.edu|Computational Genomics Group, Department of Microbiology, University of Washington, USA. dna@u.washington.edu', 'United States|United States', 64, 'Amino Acid Sequence|Conserved Sequence|Databases, Protein|Entropy|Protein Structure, Secondary|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-7-385', '16916457', 'Several entropy-based methods have been developed for scoring sequence conservation in protein multiple sequence alignments. High scoring amino acid positions may correlate with structurally or functionally important residues. However, amino acid background frequencies are usually not taken into account in these entropy-based scoring schemes.'),
(91056, 2006, 'bmc', 'Hierarchical modularity of nested bow-ties in metabolic networks', 'Zhao, Jing|Yu, Hong|Luo, Jian-Hua|Cao, Zhi-Wei|Li, Yi-Xue', 'School of Life Sciences & Technology, Shanghai Jiao Tong University, Shanghai 200240, China. zjane_cn@sjtu.edu.cn|School of Life Sciences & Technology, Shanghai Jiao Tong University, Shanghai 200240, China. zjane_cn@sjtu.edu.cn|School of Life Sciences & Technology, Shanghai Jiao Tong University, Shanghai 200240, China. zjane_cn@sjtu.edu.cn|School of Life Sciences & Technology, Shanghai Jiao Tong University, Shanghai 200240, China. zjane_cn@sjtu.edu.cn|School of Life Sciences & Technology, Shanghai Jiao Tong University, Shanghai 200240, China. zjane_cn@sjtu.edu.cn', 'China|China|China|China|China', 81, 'Algorithms|Cell Physiological Phenomena|Computer Graphics|Computer Simulation|Gene Expression|Models, Biological|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-386', '16916470', 'The exploration of the structural topology and the organizing principles of genome-based large-scale metabolic networks is essential for studying possible relations between structure and functionality of metabolic networks. Topological analysis of graph models has often been applied to study the structural characteristics of complex metabolic networks.'),
(91057, 2006, 'bmc', 'On the statistical assessment of classifiers using DNA microarray data', 'Ancona, N|Maglietta, R|Piepoli, A|DAddabbo, A|Cotugno, R|Savino, M|Liuni, S|Carella, M|Pesole, G|Perri, F', 'lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it|lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it|lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it|lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it|lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it|lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it|lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it|lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it|lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it|lstituto di Studi sui Sistemi Intelligenti per IAutomazione-CNR, Via Amendola 122/D-l, 70126 Bari, Italy. ancona@ba.issia.cnr.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 59, 'Aged|Algorithms|Colonic Neoplasms|Data Interpretation, Statistical|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Male|Middle Aged|Models, Statistical|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Software|Statistics as Topic', 'Journal Article', '10.1186/1471-2105-7-387', '16919171', 'In this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia--Italy. The data set is made up of normal (22) and tumor (25) specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data.'),
(91058, 2006, 'bmc', 'Selecting normalization genes for small diagnostic microarrays', 'Jaeger, Jochen|Spang, Rainer', 'Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. jaeger@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. jaeger@molgen.mpg.de', 'Germany|Germany', 9, 'Algorithms|Gene Expression Profiling|Genome, Human|Humans|Multivariate Analysis|Oligonucleotide Array Sequence Analysis|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Sequence Analysis, DNA|Statistics as Topic', 'Comparative Study', '10.1186/1471-2105-7-388', '16925821', 'Normalization of gene expression microarrays carrying thousands of genes is based on assumptions that do not hold for diagnostic microarrays carrying only few genes. Thus, applying standard microarray normalization strategies to diagnostic microarrays causes new normalization problems.'),
(91059, 2006, 'bmc', 'Fast index based algorithms and software for matching position specific scoring matrices', 'Beckstette, Michael|Homann, Robert|Giegerich, Robert|Kurtz, Stefan', 'International NRW Graduate School in Bioinformatics and Genome Research, Center for Biotechnology (CeBITec), Bielefeld University, D-33594 Bielefeld, Germany. mbeckste@techfak.uni-bielefeld.de|International NRW Graduate School in Bioinformatics and Genome Research, Center for Biotechnology (CeBITec), Bielefeld University, D-33594 Bielefeld, Germany. mbeckste@techfak.uni-bielefeld.de|International NRW Graduate School in Bioinformatics and Genome Research, Center for Biotechnology (CeBITec), Bielefeld University, D-33594 Bielefeld, Germany. mbeckste@techfak.uni-bielefeld.de|International NRW Graduate School in Bioinformatics and Genome Research, Center for Biotechnology (CeBITec), Bielefeld University, D-33594 Bielefeld, Germany. mbeckste@techfak.uni-bielefeld.de', 'Germany|Germany|Germany|Germany', 92, 'Algorithms|Amino Acid Sequence|Databases, Factual|Matched-Pair Analysis|Research Design|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-7-389', '16930469', 'In biological sequence analysis, position specific scoring matrices (PSSMs) are widely used to represent sequence motifs in nucleotide as well as amino acid sequences. Searching with PSSMs in complete genomes or large sequence databases is a common, but computationally expensive task.'),
(91060, 2006, 'bmc', 'PET-Tool: a software suite for comprehensive processing and managing of Paired-End diTag (PET) sequence data', 'Chiu, Kuo Ping|Wong, Chee-Hong|Chen, Qiongyu|Ariyaratne, Pramila|Ooi, Hong Sain|Wei, Chia-Lin|Sung, Wing-Kin Ken|Ruan, Yijun', 'Information and Mathematical Sciences Group, Genome Institute of Singapore, 60 Biopolis Street, Genome #02-01, 138672, Singapore. chiukp@gis.a-star.edu.sg|Information and Mathematical Sciences Group, Genome Institute of Singapore, 60 Biopolis Street, Genome #02-01, 138672, Singapore. chiukp@gis.a-star.edu.sg|Information and Mathematical Sciences Group, Genome Institute of Singapore, 60 Biopolis Street, Genome #02-01, 138672, Singapore. chiukp@gis.a-star.edu.sg|Information and Mathematical Sciences Group, Genome Institute of Singapore, 60 Biopolis Street, Genome #02-01, 138672, Singapore. chiukp@gis.a-star.edu.sg|Information and Mathematical Sciences Group, Genome Institute of Singapore, 60 Biopolis Street, Genome #02-01, 138672, Singapore. chiukp@gis.a-star.edu.sg|Information and Mathematical Sciences Group, Genome Institute of Singapore, 60 Biopolis Street, Genome #02-01, 138672, Singapore. chiukp@gis.a-star.edu.sg|Information and Mathematical Sciences Group, Genome Institute of Singapore, 60 Biopolis Street, Genome #02-01, 138672, Singapore. chiukp@gis.a-star.edu.sg|Information and Mathematical Sciences Group, Genome Institute of Singapore, 60 Biopolis Street, Genome #02-01, 138672, Singapore. chiukp@gis.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 24, 'Animals|Base Sequence|Computational Biology|Databases, Nucleic Acid|Genome|Humans|Molecular Sequence Data|Sequence Analysis, DNA|Software|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-7-390', '16934139', 'We recently developed the Paired End diTag (PET) strategy for efficient characterization of mammalian transcriptomes and genomes. The paired end nature of short PET sequences derived from long DNA fragments raised a new set of bioinformatics challenges, including how to extract PETs from raw sequence reads, and correctly yet efficiently map PETs to reference genome sequences. To accommodate and streamline data analysis of the large volume PET sequences generated from each PET experiment, an automated PET data process pipeline is desirable.'),
(91061, 2006, 'bmc', 'Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression', 'Lemieux, Sébastien', 'Institute for Research in Immunology and Cancer, Université de Montréal, Montréal, Canada. s.lemieux@umontreal.ca', 'Canada', 9, 'Algorithms|Cluster Analysis|Data Interpretation, Statistical|Gene Expression Profiling|Linear Models|Models, Genetic|Normal Distribution|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|RNA, Messenger|ROC Curve|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-7-391', '16934150', 'The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level probe intensities, then deriving significance by comparing these expression levels between conditions. The proposed PL-LM (Probe-Level Linear Model) method implements a linear model applied on the probe-level data to directly estimate the treatment effect. A finite mixture of Gaussian components is then used to identify DEGs using the coefficients estimated by the linear model. This approach can readily be applied to experimental design with or without replication.'),
(91062, 2006, 'bmc', 'GeneLibrarian: an effective gene-information summarization and visualization system', 'Chiang, Jung-Hsien|Shin, Jyh-Wei|Liu, Heng-Hui|Chin, Chong-Liang', 'Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. jchiang@mail.ncku.edu.tw|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. jchiang@mail.ncku.edu.tw|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. jchiang@mail.ncku.edu.tw|Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan. jchiang@mail.ncku.edu.tw', '-|-|-|-', 13, 'Algorithms|Cluster Analysis|Databases, Genetic|Gene Expression|Information Storage and Retrieval|Internet|Reproducibility of Results|Semantics|Software', 'Journal Article', '10.1186/1471-2105-7-392', '16939640', 'Abundant information about gene products is stored in online searchable databases such as annotation or literature. To efficiently obtain and digest such information, there is a pressing need for automated information-summarization and functional-similarity clustering of genes.'),
(91063, 2006, 'bmc', 'A probabilistic classifier for olfactory receptor pseudogenes', 'Menashe, Idan|Aloni, Ronny|Lancet, Doron', 'Department of Molecular Genetics and the Crown Human Genome Center, The Weizmann Institute of Science, Rehovot 76100, Israel. idan.menashe@weizmann.ac.il|Department of Molecular Genetics and the Crown Human Genome Center, The Weizmann Institute of Science, Rehovot 76100, Israel. idan.menashe@weizmann.ac.il|Department of Molecular Genetics and the Crown Human Genome Center, The Weizmann Institute of Science, Rehovot 76100, Israel. idan.menashe@weizmann.ac.il', 'Israel|Israel|Israel', 33, 'Algorithms|Animals|Dogs|Evolution, Molecular|Humans|Mice|Models, Statistical|Pseudogenes|Receptors, Odorant', 'Comparative Study', '10.1186/1471-2105-7-393', '16939646', 'Olfactory receptors (ORs), the largest mammalian gene superfamily (900-1400 genes), has >50% pseudogenes in humans. While most of these inactive genes are identified via coding frame (nonsense) disruptions, seemingly intact genes may also be inactive due to other deleterious (missense) mutations. An ultimate assessment of the actual size of the functional human OR repertoire thus requires an accurate distinction between genes and pseudogenes.'),
(91064, 2006, 'bmc', 'Mining frequent patterns for AMP-activated protein kinase regulation on skeletal muscle', 'Chen, Qingfeng|Chen, Yi-Ping Phoebe', 'School of Engineering & Information Technology, Deakin University, Melbourne, Australia. qifengch@deakin.edu.au|School of Engineering & Information Technology, Deakin University, Melbourne, Australia. qifengch@deakin.edu.au', 'Australia|Australia', 34, 'AMP-Activated Protein Kinases|Algorithms|Diabetes Mellitus|Energy Metabolism|Exercise|Gene Expression Regulation, Enzymologic|Humans|Isoenzymes|Mathematical Computing|Multienzyme Complexes|Muscle, Skeletal|Protein Subunits|Protein-Serine-Threonine Kinases|Signal Transduction|Software', 'Journal Article', '10.1186/1471-2105-7-394', '16939655', 'AMP-activated protein kinase (AMPK) has emerged as a significant signaling intermediary that regulates metabolisms in response to energy demand and supply. An investigation into the degree of activation and deactivation of AMPK subunits under exercise can provide valuable data for understanding AMPK. In particular, the effect of AMPK on muscle cellular energy status makes this protein a promising pharmacological target for disease treatment. As more AMPK regulation data are accumulated, data mining techniques can play an important role in identifying frequent patterns in the data. Association rule mining, which is commonly used in market basket analysis, can be applied to AMPK regulation.'),
(91065, 2006, 'bmc', 'Probe set algorithms: is there a rational best bet?', 'Seo, Jinwook|Hoffman, Eric P', 'Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Ave NW, Washington DC 20010, USA. jseo@cnmcresearch.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Ave NW, Washington DC 20010, USA. jseo@cnmcresearch.org', 'United States|United States', 61, 'Algorithms|Computational Biology|False Positive Reactions|Gene Expression Profiling|Genetic Techniques|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|RNA, Messenger|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-7-395', '16942624', 'Affymetrix microarrays have become a standard experimental platform for studies of mRNA expression profiling. Their success is due, in part, to the multiple oligonucleotide features (probes) against each transcript (probe set). This multiple testing allows for more robust background assessments and gene expression measures, and has permitted the development of many computational methods to translate image data into a single normalized signal for mRNA transcript abundance. There are now many probe set algorithms that have been developed, with a gradual movement away from chip-by-chip methods (MAS5), to project-based model-fitting methods (dCHIP, RMA, others). Data interpretation is often profoundly changed by choice of algorithm, with disoriented biologists questioning what the accurate interpretation of their experiment is. Here, we summarize the debate concerning probe set algorithms. We provide examples of how changes in mismatch weight, normalizations, and construction of expression ratios each dramatically change data interpretation. All interpretations can be considered as computationally appropriate, but with varying biological credibility. We also illustrate the performance of two new hybrid algorithms (PLIER, GC-RMA) relative to more traditional algorithms (dCHIP, MAS5, Probe Profiler PCA, RMA) using an interactive power analysis tool. PLIER appears superior to other algorithms in avoiding false positives with poorly performing probe sets. Based on our interpretation of the literature, and examples presented here, we suggest that the variability in performance of probe set algorithms is more dependent upon assumptions regarding background, than on calculations of signal. We argue that background is an enormously complex variable that can only be vaguely quantified, and thus the best probe set algorithm will vary from project to project.'),
(91066, 2006, 'bmc', 'Predicting transcription factor binding sites using local over-representation and comparative genomics', 'Defrance, Matthieu|Touzet, Hélène', 'LIFL, UMR CNRS 8022, Université des Sciences et Technologies de Lille, Villeneuve dAscq, France. defrance@lifl.fr|LIFL, UMR CNRS 8022, Université des Sciences et Technologies de Lille, Villeneuve dAscq, France. defrance@lifl.fr', 'France|France', 47, 'Algorithms|Base Sequence|Binding Sites|Chromosome Mapping|Genomics|Molecular Sequence Data|Protein Binding|Regulatory Elements, Transcriptional|Sequence Alignment|Sequence Analysis, DNA|Software|Species Specificity|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-7-396', '16945132', 'Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs) in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms.'),
(91067, 2006, 'bmc', 'Methods for evaluating clustering algorithms for gene expression data using a reference set of functional classes', 'Datta, Susmita|Datta, Somnath', 'Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA. susmita.datta@louisville.edu|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40202, USA. susmita.datta@louisville.edu', 'United States|United States', 104, 'Algorithms|Artificial Intelligence|Benchmarking|Cluster Analysis|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reference Values', 'Evaluation Studies', '10.1186/1471-2105-7-397', '16945146', 'A cluster analysis is the most commonly performed procedure (often regarded as a first step) on a set of gene expression profiles. In most cases, a post hoc analysis is done to see if the genes in the same clusters can be functionally correlated. While past successes of such analyses have often been reported in a number of microarray studies (most of which used the standard hierarchical clustering, UPGMA, with one minus the Pearsons correlation coefficient as a measure of dissimilarity), often times such groupings could be misleading. More importantly, a systematic evaluation of the entire set of clusters produced by such unsupervised procedures is necessary since they also contain genes that are seemingly unrelated or may have more than one common function. Here we quantify the performance of a given unsupervised clustering algorithm applied to a given microarray study in terms of its ability to produce biologically meaningful clusters using a reference set of functional classes. Such a reference set may come from prior biological knowledge specific to a microarray study or may be formed using the growing databases of gene ontologies (GO) for the annotated genes of the relevant species.'),
(91068, 2006, 'bmc', 'PhyloPat: phylogenetic pattern analysis of eukaryotic genes', 'Hulsen, Tim|de Vlieg, Jacob|Groenen, Peter M A', 'Centre for Molecular and Biomolecular Informatics (CMBI), Nijmegen Centre for Molecular Life Sciences (NCMLS), Radboud University Nijmegen, Nijmegen, The Netherlands. T.Hulsen@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics (CMBI), Nijmegen Centre for Molecular Life Sciences (NCMLS), Radboud University Nijmegen, Nijmegen, The Netherlands. T.Hulsen@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics (CMBI), Nijmegen Centre for Molecular Life Sciences (NCMLS), Radboud University Nijmegen, Nijmegen, The Netherlands. T.Hulsen@cmbi.ru.nl', 'Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Conserved Sequence|Database Management Systems|Databases, Genetic|Eukaryotic Cells|Information Storage and Retrieval|Molecular Sequence Data|Pattern Recognition, Automated|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-7-398', '16948844', 'Phylogenetic patterns show the presence or absence of certain genes or proteins in a set of species. They can also be used to determine sets of genes or proteins that occur only in certain evolutionary branches. Phylogenetic patterns analysis has routinely been applied to protein databases such as COG and OrthoMCL, but not upon gene databases. Here we present a tool named PhyloPat which allows the complete Ensembl gene database to be queried using phylogenetic patterns.'),
(91069, 2006, 'bmc', 'Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive resonance theory (PART) filtering method', 'Takahashi, Hiro|Nemoto, Takeshi|Yoshida, Teruhiko|Honda, Hiroyuki|Hasegawa, Tadashi', 'Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. hirtakah@gan2.res.ncc.go.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. hirtakah@gan2.res.ncc.go.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. hirtakah@gan2.res.ncc.go.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. hirtakah@gan2.res.ncc.go.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. hirtakah@gan2.res.ncc.go.jp', 'Japan|Japan|Japan|Japan|Japan', 23, 'Algorithms|Biomarkers, Tumor|Cell Line, Tumor|Cluster Analysis|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sarcoma|Soft Tissue Neoplasms', 'Journal Article', '10.1186/1471-2105-7-399', '16948864', 'Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in improved diagnosis and selection of treatment. To accomplish this objective, it is important to establish a sophisticated algorithm that can deal with large quantities of data such as gene expression profiles obtained by DNA microarray analysis.'),
(91070, 2006, 'bmc', 'Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints', 'Dowell, Robin D|Eddy, Sean R', 'Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, 4444 Forest Park Blvd, Box 8510, St. Louis, MO 63108, USA. rdd@mit.edu|Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, 4444 Forest Park Blvd, Box 8510, St. Louis, MO 63108, USA. rdd@mit.edu', 'United States|United States', 0, 'Algorithms|Base Pairing|Computer Simulation|Models, Molecular|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Stochastic Processes', 'Comparative Study', '10.1186/1471-2105-7-400', '16952317', 'We are interested in the problem of predicting secondary structure for small sets of homologous RNAs, by incorporating limited comparative sequence information into an RNA folding model. The Sankoff algorithm for simultaneous RNA folding and alignment is a basis for approaches to this problem. There are two open problems in applying a Sankoff algorithm: development of a good unified scoring system for alignment and folding and development of practical heuristics for dealing with the computational complexity of the algorithm.'),
(91071, 2006, 'bmc', 'CRNPRED: highly accurate prediction of one-dimensional protein structures by large-scale critical random networks', 'Kinjo, Akira R|Nishikawa, Ken', 'Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima, 411-8540, Japan. akinjo@protein.osaka-u.ac.jp|Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima, 411-8540, Japan. akinjo@protein.osaka-u.ac.jp', 'Japan|Japan', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Data Interpretation, Statistical|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Protein Conformation|Proteins|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-7-401', '16952323', 'One-dimensional protein structures such as secondary structures or contact numbers are useful for three-dimensional structure prediction and helpful for intuitive understanding of the sequence-structure relationship. Accurate prediction methods will serve as a basis for these and other purposes.'),
(91072, 2006, 'bmc', 'Distill: a suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins', 'Baú, Davide|Martin, Alberto J M|Mooney, Catherine|Vullo, Alessandro|Walsh, Ian|Pollastri, Gianluca', 'School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland. davide.bau@ucd.ie|School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland. davide.bau@ucd.ie|School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland. davide.bau@ucd.ie|School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland. davide.bau@ucd.ie|School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland. davide.bau@ucd.ie|School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland. davide.bau@ucd.ie', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 0, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Databases, Protein|Internet|Protein Conformation|Protein Folding|Protein Interaction Mapping|Protein Structure, Secondary|Sequence Alignment|Solvents', 'Journal Article', '10.1186/1471-2105-7-402', '16953874', 'We describe Distill, a suite of servers for the prediction of protein structural features: secondary structure, relative solvent accessibility, contact density, backbone structural motifs, residue contact maps at 6, 8 and 12 Angstrom, coarse protein topology. The servers are based on large-scale ensembles of recursive neural networks and trained on large, up-to-date, non-redundant subsets of the Protein Data Bank. Together with structural feature predictions, Distill includes a server for prediction of Calpha traces for short proteins (up to 200 amino acids).'),
(91073, 2006, 'bmc', 'A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls', 'Titulaer, Mark K|Siccama, Ivar|Dekker, Lennard J|van Rijswijk, Angelique L C T|Heeren, Ron M A|Sillevis Smitt, Peter A|Luider, Theo M', 'Department of Neurology, Erasmus MC, Rotterdam, The Netherlands. m.titulaer@erasmusmc.nl|Department of Neurology, Erasmus MC, Rotterdam, The Netherlands. m.titulaer@erasmusmc.nl|Department of Neurology, Erasmus MC, Rotterdam, The Netherlands. m.titulaer@erasmusmc.nl|Department of Neurology, Erasmus MC, Rotterdam, The Netherlands. m.titulaer@erasmusmc.nl|Department of Neurology, Erasmus MC, Rotterdam, The Netherlands. m.titulaer@erasmusmc.nl|Department of Neurology, Erasmus MC, Rotterdam, The Netherlands. m.titulaer@erasmusmc.nl|Department of Neurology, Erasmus MC, Rotterdam, The Netherlands. m.titulaer@erasmusmc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Amino Acid Sequence|Biomarkers, Tumor|Database Management Systems|Databases, Protein|Diagnosis, Computer-Assisted|Humans|Information Storage and Retrieval|Molecular Sequence Data|Neoplasm Proteins|Neoplasms|Peptide Mapping|Reference Values|Sequence Analysis, Protein|Software|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Journal Article', '10.1186/1471-2105-7-403', '16953879', 'Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein ids can be added to peptide masses of interest.'),
(91074, 2006, 'bmc', 'RDMAS: a web server for RNA deleterious mutation analysis', 'Shu, Wenjie|Bo, Xiaochen|Liu, Rujia|Zhao, Dongsheng|Zheng, Zhiqiang|Wang, Shengqi', 'Beijing Institute of Radiation Medicine, Beijing 100850, China. shuwj@bmi.ac.cn|Beijing Institute of Radiation Medicine, Beijing 100850, China. shuwj@bmi.ac.cn|Beijing Institute of Radiation Medicine, Beijing 100850, China. shuwj@bmi.ac.cn|Beijing Institute of Radiation Medicine, Beijing 100850, China. shuwj@bmi.ac.cn|Beijing Institute of Radiation Medicine, Beijing 100850, China. shuwj@bmi.ac.cn|Beijing Institute of Radiation Medicine, Beijing 100850, China. shuwj@bmi.ac.cn', 'China|China|China|China|China|China', 0, 'Databases, Nucleic Acid|Humans|Internet|MicroRNAs|Nucleic Acid Conformation|Point Mutation|RNA, Untranslated', 'Journal Article', '10.1186/1471-2105-7-404', '16956394', 'The diverse functions of ncRNAs critically depend on their structures. Mutations in ncRNAs disrupting the structures of functional sites are expected to be deleterious. RNA deleterious mutations have attracted wide attentions because some of them in cells result in serious disease, and some others in microbes influence their fitness.'),
(91075, 2006, 'bmc', 'Predicting the effect of missense mutations on protein function: analysis with Bayesian networks', 'Needham, Chris J|Bradford, James R|Bulpitt, Andrew J|Care, Matthew A|Westhead, David R', 'School of Computing, University of Leeds, Leeds, LS2 9JT, UK. chrisn@comp.leeds.ac.uk|School of Computing, University of Leeds, Leeds, LS2 9JT, UK. chrisn@comp.leeds.ac.uk|School of Computing, University of Leeds, Leeds, LS2 9JT, UK. chrisn@comp.leeds.ac.uk|School of Computing, University of Leeds, Leeds, LS2 9JT, UK. chrisn@comp.leeds.ac.uk|School of Computing, University of Leeds, Leeds, LS2 9JT, UK. chrisn@comp.leeds.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acids|Bayes Theorem|Databases, Genetic|Markov Chains|Models, Biological|Models, Statistical|Monte Carlo Method|Muramidase|Mutation, Missense|Probability|Protein Conformation|Proteins|ROC Curve|Repressor Proteins|Structure-Activity Relationship', 'Comparative Study', '10.1186/1471-2105-7-405', '16956412', 'A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, many of these methods break down if either one of the two types of data are missing. Furthermore, there is a lack of rigorous assessment of how important the different factors are to prediction.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91076, 2006, 'bmc', 'Correction: genetic algorithm learning as a robust approach to RNA editing site site prediction', 'Thompson, James|Gopal, Shuba', 'Department of Biological Sciences, Rochester Institute of Technology, Rochester, NY 14623, USA. sxgsbi@rit.edu.|Department of Biological Sciences, Rochester Institute of Technology, Rochester, NY 14623, USA. sxgsbi@rit.edu.', 'United States|United States', 0, 'Algorithms|Arabidopsis|Brassica napus|Computational Biology|DNA, Mitochondrial|Genome, Plant|Oryza|RNA|RNA Editing|ROC Curve|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-7-406', '16956416', 'After the publication of [1], we were alerted to an error in our data. The error was an one-off miscalculation in the extraction of position information for our set of true negatives. Our data set should have used randomly selected non-edited cytosines (C) as true negatives, but the data generation phase resulted in a set of nucleotides that were each one nucleotide downstream of known, unedited cytosines. The consequences of this error are reflected in changes to our results, although the general conclusions presented in our original publication remain largely unchanged.'),
(91077, 2006, 'bmc', 'Identifying genes that contribute most to good classification in microarrays', 'Baker, Stuart G|Kramer, Barnett S', 'Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD 20892-7354, USA. sb16i@nih.gov|Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD 20892-7354, USA. sb16i@nih.gov', 'United States|United States', 46, 'Colonic Neoplasms|Cytoskeletal Proteins|Desmin|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Glycoproteins|Humans|Leukemia|Oligonucleotide Array Sequence Analysis|Proteoglycans|Software Validation|Zyxin', 'Journal Article', '10.1186/1471-2105-7-407', '16959042', 'The goal of most microarray studies is either the identification of genes that are most differentially expressed or the creation of a good classification rule. The disadvantage of the former is that it ignores the importance of gene interactions, the disadvantage of the latter is that it often does not provide a sufficient focus for further investigation because many genes may be included by chance. Our strategy is to search for classification rules that perform well with few genes and, if they are found, identify genes that occur relatively frequently under multiple random validation (random splits into training and test samples).'),
(91078, 2006, 'bmc', 'Scanning sequences after Gibbs sampling to find multiple occurrences of functional elements', 'Tharakaraman, Kannan|Mariño-Ramírez, Leonardo|Sheetlin, Sergey L|Landsman, David|Spouge, John L', 'Computational Biology Branch, National Center for Biotechnology Information National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 6075 Bethesda, MD 20894-6075, USA. tharakar@ncbi.nlm.nih.gov|Computational Biology Branch, National Center for Biotechnology Information National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 6075 Bethesda, MD 20894-6075, USA. tharakar@ncbi.nlm.nih.gov|Computational Biology Branch, National Center for Biotechnology Information National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 6075 Bethesda, MD 20894-6075, USA. tharakar@ncbi.nlm.nih.gov|Computational Biology Branch, National Center for Biotechnology Information National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 6075 Bethesda, MD 20894-6075, USA. tharakar@ncbi.nlm.nih.gov|Computational Biology Branch, National Center for Biotechnology Information National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 6075 Bethesda, MD 20894-6075, USA. tharakar@ncbi.nlm.nih.gov', 'United States|United States|United States|United States|United States', 0, 'Animals|Base Sequence|Drosophila|Markov Chains|Molecular Sequence Data|Monte Carlo Method|Regulatory Elements, Transcriptional|Saccharomyces|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1186/1471-2105-7-408', '16961919', 'Many DNA regulatory elements occur as multiple instances within a target promoter. Gibbs sampling programs for finding DNA regulatory elements de novo can be prohibitively slow in locating all instances of such an element in a sequence set.'),
(91079, 2006, 'bmc', 'Genome-wide DNA polymorphism analyses using VariScan', 'Hutter, Stephan|Vilella, Albert J|Rozas, Julio', 'Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain. hutter@zi.biologie.uni-muenchen.de|Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain. hutter@zi.biologie.uni-muenchen.de|Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain. hutter@zi.biologie.uni-muenchen.de', 'Spain|Spain|Spain', 75, 'Algorithms|Animals|Base Sequence|Computer Graphics|Genome|Humans|Mice|Polymorphism, Genetic|Polymorphism, Single Nucleotide|Selection, Genetic|Sequence Alignment|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-409', '16968531', 'DNA sequence polymorphisms analysis can provide valuable information on the evolutionary forces shaping nucleotide variation, and provides an insight into the functional significance of genomic regions. The recent ongoing genome projects will radically improve our capabilities to detect specific genomic regions shaped by natural selection. Current available methods and software, however, are unsatisfactory for such genome-wide analysis.'),
(91080, 2006, 'bmc', 'Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction', 'Scheeff, Eric D|Bourne, Philip E', 'San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093-0537, USA. scheeff@salk.edu|San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093-0537, USA. scheeff@salk.edu', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Markov Chains|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Evaluation Studies', '10.1186/1471-2105-7-410', '16970830', 'One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because profiles are built from sequence alignments, the sequences included in the alignment and the method used to align them will be important to the sensitivity of the resulting profile. The inclusion of highly diverse sequences will presumably produce a more powerful profile, but distantly related sequences can be difficult to align accurately using only sequence information. Therefore, it would be expected that the use of protein structure alignments to improve the selection and alignment of diverse sequence homologs might yield improved profiles. However, the actual utility of such an approach has remained unclear.'),
(91081, 2006, 'bmc', 'miTarget: microRNA target gene prediction using a support vector machine', 'Kim, Sung-Kyu|Nam, Jin-Wu|Rhee, Je-Keun|Lee, Wha-Jin|Zhang, Byoung-Tak', 'Graduate Program in Bioinformatics, Seoul National University, Seoul, Korea. skkim@bi.snu.ac.kr|Graduate Program in Bioinformatics, Seoul National University, Seoul, Korea. skkim@bi.snu.ac.kr|Graduate Program in Bioinformatics, Seoul National University, Seoul, Korea. skkim@bi.snu.ac.kr|Graduate Program in Bioinformatics, Seoul National University, Seoul, Korea. skkim@bi.snu.ac.kr|Graduate Program in Bioinformatics, Seoul National University, Seoul, Korea. skkim@bi.snu.ac.kr', '-|-|-|-|-', 0, 'Algorithms|Artificial Intelligence|Base Sequence|Gene Silencing|Gene Targeting|MicroRNAs|Molecular Sequence Data|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-7-411', '16978421', 'MicroRNAs (miRNAs) are small noncoding RNAs, which play significant roles as posttranscriptional regulators. The functions of animal miRNAs are generally based on complementarity for their 5 components. Although several computational miRNA target-gene prediction methods have been proposed, they still have limitations in revealing actual target genes.'),
(91082, 2006, 'bmc', 'Detecting recombination in evolving nucleotide sequences', 'Chan, Cheong Xin|Beiko, Robert G|Ragan, Mark A', 'ARC Centre in Bioinformatics and Institute for Molecular Bioscience, the University of Queensland, Brisbane, QLD 4072, Australia. c.chan@imb.uq.edu.au|ARC Centre in Bioinformatics and Institute for Molecular Bioscience, the University of Queensland, Brisbane, QLD 4072, Australia. c.chan@imb.uq.edu.au|ARC Centre in Bioinformatics and Institute for Molecular Bioscience, the University of Queensland, Brisbane, QLD 4072, Australia. c.chan@imb.uq.edu.au', 'Australia|Australia|Australia', 40, 'Algorithms|Base Sequence|Bayes Theorem|Computer Simulation|Evolution, Molecular|Linear Models|Models, Genetic|Phylogeny|Recombination, Genetic|Software', 'Comparative Study', '10.1186/1471-2105-7-412', '16978423', 'Genetic recombination can produce heterogeneous phylogenetic histories within a set of homologous genes. These recombination events can be obscured by subsequent residue substitutions, which consequently complicate their detection. While there are many algorithms for the identification of recombination events, little is known about the effects of subsequent substitutions on the accuracy of available recombination-detection approaches.'),
(91083, 2006, 'bmc', 'Correlated fragile site expression allows the identification of candidate fragile genes involved in immunity and associated with carcinogenesis', 'Re, Angela|Cora, Davide|Puliti, Alda Maria|Caselle, Michele|Sbrana, Isabella', 'Dipartimento di Fisica Teorica dellUniversità degli Studi di Torino e INFN, Via P, Giuria 1--I 10125 Torino, Italy. angelare@to.infn.it|Dipartimento di Fisica Teorica dellUniversità degli Studi di Torino e INFN, Via P, Giuria 1--I 10125 Torino, Italy. angelare@to.infn.it|Dipartimento di Fisica Teorica dellUniversità degli Studi di Torino e INFN, Via P, Giuria 1--I 10125 Torino, Italy. angelare@to.infn.it|Dipartimento di Fisica Teorica dellUniversità degli Studi di Torino e INFN, Via P, Giuria 1--I 10125 Torino, Italy. angelare@to.infn.it|Dipartimento di Fisica Teorica dellUniversità degli Studi di Torino e INFN, Via P, Giuria 1--I 10125 Torino, Italy. angelare@to.infn.it', 'Italy|Italy|Italy|Italy|Italy', 0, 'Cells, Cultured|Chromosome Fragile Sites|Chromosome Fragility|Databases, Genetic|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Humans|Immunity', 'Comparative Study', '10.1186/1471-2105-7-413', '16981993', 'Common fragile sites (cfs) are specific regions in the human genome that are particularly prone to genomic instability under conditions of replicative stress. Several investigations support the view that common fragile sites play a role in carcinogenesis. We discuss a genome-wide approach based on graph theory and Gene Ontology vocabulary for the functional characterization of common fragile sites and for the identification of genes that contribute to tumour cell biology.'),
(91084, 2006, 'bmc', 'Semi-supervised discovery of differential genes', 'Oba, Shigeyuki|Ishii, Shin', 'Graduate School of Information Science, Nara Institute of Science and Technology, Takayama, Ikoma, Nara, Japan. shige-o@is.naist.jp|Graduate School of Information Science, Nara Institute of Science and Technology, Takayama, Ikoma, Nara, Japan. shige-o@is.naist.jp', 'Japan|Japan', 3, 'Algorithms|Cluster Analysis|Colonic Neoplasms|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Likelihood Functions|Male|Models, Genetic|Prostatic Neoplasms|RNA, Messenger|Reproducibility of Results|Software|Stochastic Processes', 'Comparative Study', '10.1186/1471-2105-7-414', '16981994', 'Various statistical scores have been proposed for evaluating the significance of genes that may exhibit differential expression between two or more controlled conditions. However, in many clinical studies to detect clinical marker genes for example, the conditions have not necessarily been controlled well, thus condition labels are sometimes hard to obtain due to physical, financial, and time costs. In such a situation, we can consider an unsupervised case where labels are not available or a semi-supervised case where labels are available for a part of the whole sample set, rather than a well-studied supervised case where all samples have their labels.'),
(91085, 2006, 'bmc', 'Quantification of the variation in percentage identity for protein sequence alignments', 'Raghava, G P S|Barton, Geoffrey J', 'School of Life Sciences Research, University of Dundee, Dow Street, Dundee, DD1 5EH, Scotland, UK. raghava@imtech.res.in|School of Life Sciences Research, University of Dundee, Dow Street, Dundee, DD1 5EH, Scotland, UK. raghava@imtech.res.in', 'United Kingdom|United Kingdom', 39, 'Algorithms|Amino Acid Sequence|Computational Biology|Databases, Protein|Protein Conformation|Proteins|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-7-415', '16984632', 'Percentage Identity (PID) is frequently quoted in discussion of sequence alignments since it appears simple and easy to understand. However, although there are several different ways to calculate percentage identity and each may yield a different result for the same alignment, the method of calculation is rarely reported. Accordingly, quantification of the variation in PID caused by the different calculations would help in interpreting PID values in the literature. In this study, the variation in PID was quantified systematically on a reference set of 1028 alignments generated by comparison of the protein three-dimensional structures. Since the alignment algorithm may also affect the range of PID, this study also considered the effect of algorithm, and the combination of algorithm and PID method.'),
(91086, 2006, 'bmc', 'Genomes as geography: using GIS technology to build interactive genome feature maps', 'Dolan, Mary E|Holden, Constance C|Beard, M Kate|Bult, Carol J', 'National Center for Geographic Information and Analysis, University of Maine, Orono, ME 04469, USA. mdolan@informatics.jax.org|National Center for Geographic Information and Analysis, University of Maine, Orono, ME 04469, USA. mdolan@informatics.jax.org|National Center for Geographic Information and Analysis, University of Maine, Orono, ME 04469, USA. mdolan@informatics.jax.org|National Center for Geographic Information and Analysis, University of Maine, Orono, ME 04469, USA. mdolan@informatics.jax.org', 'United States|United States|United States|United States', 13, 'Animals|Chromosome Mapping|Databases, Genetic|Gene Expression Regulation|Genome|Geographic Information Systems|Mice', 'Journal Article', '10.1186/1471-2105-7-416', '16984652', 'Many commonly used genome browsers display sequence annotations and related attributes as horizontal data tracks that can be toggled on and off according to user preferences. Most genome browsers use only simple keyword searches and limit the display of detailed annotations to one chromosomal region of the genome at a time. We have employed concepts, methodologies, and tools that were developed for the display of geographic data to develop a Genome Spatial Information System (GenoSIS) for displaying genomes spatially, and interacting with genome annotations and related attribute data. In contrast to the paradigm of horizontally stacked data tracks used by most genome browsers, GenoSIS uses the concept of registered spatial layers composed of spatial objects for integrated display of diverse data. In addition to basic keyword searches, GenoSIS supports complex queries, including spatial queries, and dynamically generates genome maps. Our adaptation of the geographic information system (GIS) model in a genome context supports spatial representation of genome features at multiple scales with a versatile and expressive query capability beyond that supported by existing genome browsers.'),
(91087, 2006, 'bmc', 'Searching for interpretable rules for disease mutations: a simulated annealing bump hunting strategy', 'Jiang, Rui|Yang, Hua|Sun, Fengzhu|Chen, Ting', 'Molecular and Computational Biology, University of Southern California, MCB201, 1050 Childs way, Los Angeles, CA 90089-2910, USA. ruijiang@usc.edu|Molecular and Computational Biology, University of Southern California, MCB201, 1050 Childs way, Los Angeles, CA 90089-2910, USA. ruijiang@usc.edu|Molecular and Computational Biology, University of Southern California, MCB201, 1050 Childs way, Los Angeles, CA 90089-2910, USA. ruijiang@usc.edu|Molecular and Computational Biology, University of Southern California, MCB201, 1050 Childs way, Los Angeles, CA 90089-2910, USA. ruijiang@usc.edu', 'United States|United States|United States|United States', 23, 'Amino Acid Sequence|Amino Acid Substitution|Bacteriophage T4|Computational Biology|Computer Simulation|Escherichia coli Infections|Escherichia coli Proteins|Humans|Models, Genetic|Molecular Sequence Data|Mutation|Predictive Value of Tests', 'Comparative Study', '10.1186/1471-2105-7-417', '16984653', 'Understanding how amino acid substitutions affect protein functions is critical for the study of proteins and their implications in diseases. Although methods have been developed for predicting potential effects of amino acid substitutions using sequence, three-dimensional structural, and evolutionary properties of proteins, the applications are limited by the complication of the features and the availability of protein structural information. Another limitation is that the prediction results are hard to be interpreted with physicochemical principles and biological knowledge.'),
(91088, 2006, 'bmc', 'CROPPER: a metagene creator resource for cross-platform and cross-species compendium studies', 'Paananen, Jussi|Storvik, Markus|Wong, Garry', 'Department of Neurobiology, A. I. Virtanen Institute for Molecular Sciences, Kuopio, Finland. Jussi.Paananen@uku.fi|Department of Neurobiology, A. I. Virtanen Institute for Molecular Sciences, Kuopio, Finland. Jussi.Paananen@uku.fi|Department of Neurobiology, A. I. Virtanen Institute for Molecular Sciences, Kuopio, Finland. Jussi.Paananen@uku.fi', 'Finland|Finland|Finland', 2, 'Animals|Computational Biology|Databases, Genetic|Genomics|Humans|Internet|Programming Languages|Software|Species Specificity|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-418', '16995941', 'Current genomic research methods provide researchers with enormous amounts of data. Combining data from different high-throughput research technologies commonly available in biological databases can lead to novel findings and increase research efficiency. However, combining data from different heterogeneous sources is often a very arduous task. These sources can be different microarray technology platforms, genomic databases, or experiments performed on various species. Our aim was to develop a software program that could facilitate the combining of data from heterogeneous sources, and thus allow researchers to perform genomic cross-platform/cross-species studies and to use existing experimental data for compendium studies.'),
(91089, 2006, 'bmc', 'A machine learning strategy to identify candidate binding sites in human protein-coding sequence', 'Down, Thomas|Leong, Bernard|Hubbard, Tim J P', 'Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK. td2@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK. td2@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK. td2@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 11, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Base Sequence|Binding Sites|Computer Simulation|Humans|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Binding|Proteins|Sequence Analysis, DNA|Sequence Analysis, Protein|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-419', '17002805', 'The splicing of RNA transcripts is thought to be partly promoted and regulated by sequences embedded within exons. Known sequences include binding sites for SR proteins, which are thought to mediate interactions between splicing factors bound to the 5 and 3 splice sites. It would be useful to identify further candidate sequences, however identifying them computationally is hard since exon sequences are also constrained by their functional role in coding for proteins.'),
(91090, 2006, 'bmc', 'Comparative assessment of performance and genome dependence among phylogenetic profiling methods', 'Snitkin, Evan S|Gustafson, Adam M|Mellor, Joseph|Wu, Jie|DeLisi, Charles', 'Bioinformatics Graduate Program, Boston University, Boston, USA. esnitkin@bu.edu|Bioinformatics Graduate Program, Boston University, Boston, USA. esnitkin@bu.edu|Bioinformatics Graduate Program, Boston University, Boston, USA. esnitkin@bu.edu|Bioinformatics Graduate Program, Boston University, Boston, USA. esnitkin@bu.edu|Bioinformatics Graduate Program, Boston University, Boston, USA. esnitkin@bu.edu', 'United States|United States|United States|United States|United States', 41, 'Bacterial Proteins|Base Sequence|Computational Biology|Databases, Genetic|Entropy|Escherichia coli|Fungal Proteins|Genome, Bacterial|Genome, Fungal|Phylogeny|Saccharomyces cerevisiae|Sequence Homology', 'Comparative Study', '10.1186/1471-2105-7-420', '17005048', 'The rapidly increasing speed with which genome sequence data can be generated will be accompanied by an exponential increase in the number of sequenced eukaryotes. With the increasing number of sequenced eukaryotic genomes comes a need for bioinformatic techniques to aid in functional annotation. Ideally, genome context based techniques such as proximity, fusion, and phylogenetic profiling, which have been so successful in prokaryotes, could be utilized in eukaryotes. Here we explore the application of phylogenetic profiling, a method that exploits the evolutionary co-occurrence of genes in the assignment of functional linkages, to eukaryotic genomes.'),
(91091, 2006, 'bmc', 'Computational reconstruction of transcriptional regulatory modules of the yeast cell cycle', 'Wu, Wei-Sheng|Li, Wen-Hsiung|Chen, Bor-Sen', 'Lab of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan. wessonwu@gmail.com|Lab of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan. wessonwu@gmail.com|Lab of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan. wessonwu@gmail.com', '-|-|-', 51, 'Algorithms|Cell Cycle|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Fungal|Gene Regulatory Networks|Models, Genetic|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription Factors|Transcription, Genetic|Yeasts', 'Journal Article', '10.1186/1471-2105-7-421', '17010188', 'A transcriptional regulatory module (TRM) is a set of genes that is regulated by a common set of transcription factors (TFs). By organizing the genome into TRMs, a living cell can coordinate the activities of many genes and carry out complex functions. Therefore, identifying TRMs is helpful for understanding gene regulation.'),
(91092, 2006, 'bmc', 'Analysis with respect to instrumental variables for the exploration of microarray data structures', 'Baty, Florent|Facompré, Michaël|Wiegand, Jan|Schwager, Joseph|Brutsche, Martin H', 'Pulmonary Gene Research, Universitätsspital Basel, Petersgraben 4, 4031 Basel, Switzerland. florent.baty@unibas.ch|Pulmonary Gene Research, Universitätsspital Basel, Petersgraben 4, 4031 Basel, Switzerland. florent.baty@unibas.ch|Pulmonary Gene Research, Universitätsspital Basel, Petersgraben 4, 4031 Basel, Switzerland. florent.baty@unibas.ch|Pulmonary Gene Research, Universitätsspital Basel, Petersgraben 4, 4031 Basel, Switzerland. florent.baty@unibas.ch|Pulmonary Gene Research, Universitätsspital Basel, Petersgraben 4, 4031 Basel, Switzerland. florent.baty@unibas.ch', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 33, 'Algorithms|Artifacts|Data Interpretation, Statistical|Databases, Genetic|Equipment Design|Equipment Failure Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-7-422', '17010189', 'Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various factors structuring the data which should be taken into account. The objective of these experiments is the exploration of some given factors while controlling other factors.'),
(91093, 2006, 'bmc', 'Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs', 'Jacques, Pierre-Etienne|Rodrigue, Sébastien|Gaudreau, Luc|Goulet, Jean|Brzezinski, Ryszard', 'Département de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada. Pierre-Etienne.Jacques@USherbrooke.ca|Département de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada. Pierre-Etienne.Jacques@USherbrooke.ca|Département de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada. Pierre-Etienne.Jacques@USherbrooke.ca|Département de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada. Pierre-Etienne.Jacques@USherbrooke.ca|Département de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada. Pierre-Etienne.Jacques@USherbrooke.ca', 'Canada|Canada|Canada|Canada|Canada', 19, 'Algorithms|Base Sequence|Genome, Bacterial|Molecular Sequence Data|Prokaryotic Initiation Factors|Promoter Regions, Genetic|Sequence Analysis|Transcription, Genetic', 'Comparative Study', '10.1186/1471-2105-7-423', '17014715', 'In bacteria, sigma factors and other transcriptional regulatory proteins recognize DNA patterns upstream of their target genes and interact with RNA polymerase to control transcription. As a consequence of evolution, DNA sequences recognized by transcription factors are thought to be enriched in intergenic regions (IRs) and depleted from coding regions of prokaryotic genomes.'),
(91094, 2006, 'bmc', 'PubFocus: semantic MEDLINE/PubMed citations analytics through integration of controlled biomedical dictionaries and ranking algorithm', 'Plikus, Maksim V|Zhang, Zina|Chuong, Cheng-Ming', 'Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA. plikus@usc.edu|Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA. plikus@usc.edu|Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA. plikus@usc.edu', 'United States|United States|United States', 39, 'Algorithms|Dictionaries, Medical as Topic|MEDLINE|PubMed|Semantics|Software Design', 'Comparative Study', '10.1186/1471-2105-7-424', '17014720', 'Understanding research activity within any given biomedical field is important. Search outputs generated by MEDLINE/PubMed are not well classified and require lengthy manual citation analysis. Automation of citation analytics can be very useful and timesaving for both novices and experts.'),
(91095, 2006, 'bmc', 'Predicting residue-wise contact orders in proteins by support vector regression', 'Song, Jiangning|Burrage, Kevin', 'Advanced Computational Modelling Centre, The University of Queensland, Brisbane Qld 4072, Australia. sjn@maths.uq.edu.au|Advanced Computational Modelling Centre, The University of Queensland, Brisbane Qld 4072, Australia. sjn@maths.uq.edu.au', 'Australia|Australia', 53, 'Algorithms|Amino Acids|Artificial Intelligence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Pattern Recognition, Automated|Protein Binding|Protein Conformation|Regression Analysis|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-7-425', '17014735', 'The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships.'),
(91096, 2006, 'bmc', 'Grouping Gene Ontology terms to improve the assessment of gene set enrichment in microarray data', 'Lewin, Alex|Grieve, Ian C', 'Department of Epidemiology and Public Health, Imperial College, Norfolk Place, London W2 1PG, UK. a.m.lewin@imperial.ac.uk|Department of Epidemiology and Public Health, Imperial College, Norfolk Place, London W2 1PG, UK. a.m.lewin@imperial.ac.uk', 'United Kingdom|United Kingdom', 28, 'Algorithms|Database Management Systems|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Multigene Family|Oligonucleotide Array Sequence Analysis|Proteins', 'Journal Article', '10.1186/1471-2105-7-426', '17018143', 'Gene Ontology (GO) terms are often used to assess the results of microarray experiments. The most common way to do this is to perform Fishers exact tests to find GO terms which are over-represented amongst the genes declared to be differentially expressed in the analysis of the microarray experiment. However, due to the high degree of dependence between GO terms, statistical testing is conservative, and interpretation is difficult.'),
(91097, 2006, 'bmc', 'MICA: desktop software for comprehensive searching of DNA databases', 'Stokes, William A|Glick, Benjamin S', 'GSL Biotech, LLC, 5211 S. Kenwood Ave, Chicago, IL 60615, USA. wstokes@gmail.com|GSL Biotech, LLC, 5211 S. Kenwood Ave, Chicago, IL 60615, USA. wstokes@gmail.com', 'United States|United States', 3, 'Algorithms|Base Sequence|Chromosome Mapping|Database Management Systems|Databases, Nucleic Acid|Information Storage and Retrieval|Internet|Microcomputers|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-427', '17018144', 'Molecular biologists work with DNA databases that often include entire genomes. A common requirement is to search a DNA database to find exact matches for a nondegenerate or partially degenerate query. The software programs available for such purposes are normally designed to run on remote servers, but an appealing alternative is to work with DNA databases stored on local computers. We describe a desktop software program termed MICA (K-Mer Indexing with Compact Arrays) that allows large DNA databases to be searched efficiently using very little memory.'),
(91098, 2006, 'bmc', 'XRate: a fast prototyping, training and annotation tool for phylo-grammars', 'Klosterman, Peter S|Uzilov, Andrew V|Bendaña, Yuri R|Bradley, Robert K|Chao, Sharon|Kosiol, Carolin|Goldman, Nick|Holmes, Ian', 'Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com|Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com|Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com|Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com|Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com|Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com|Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com|Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com', 'United States|United States|United States|United States|United States|United States|United States|United States', 42, 'Algorithms|Artificial Intelligence|Chromosome Mapping|Conserved Sequence|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-7-428', '17018148', 'Recent years have seen the emergence of genome annotation methods based on the phylo-grammar, a probabilistic model combining continuous-time Markov chains and stochastic grammars. Previously, phylo-grammars have required considerable effort to implement, limiting their adoption by computational biologists.'),
(91099, 2006, 'bmc', 'Design of a combinatorial DNA microarray for protein-DNA interaction studies', 'Mintseris, Julian|Eisen, Michael B', 'Boston University, Bioinformatics Program, Boston, MA, USA. julianm@bu.edu|Boston University, Bioinformatics Program, Boston, MA, USA. julianm@bu.edu', 'United States|United States', 21, '3 Flanking Region|5 Flanking Region|Algorithms|Base Sequence|Binding Sites|Computational Biology|Computer Simulation|DNA|DNA Probes|DNA-Binding Proteins|Oligonucleotide Array Sequence Analysis|Oligonucleotides|Saccharomyces cerevisiae Proteins|Telomere-Binding Proteins|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-429', '17018151', 'Discovery of precise specificity of transcription factors is an important step on the way to understanding the complex mechanisms of gene regulation in eukaryotes. Recently, double-stranded protein-binding microarrays were developed as a potentially scalable approach to tackle transcription factor binding site identification.'),
(91100, 2006, 'bmc', 'Development of an open source laboratory information management system for 2-D gel electrophoresis-based proteomics workflow', 'Morisawa, Hiraku|Hirota, Mikako|Toda, Tosifusa', 'Proteomics Collaboration Center, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakaecho, Itabashi-ku, Tokyo, 173-0015, Japan. hmori@tmig.or.jp|Proteomics Collaboration Center, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakaecho, Itabashi-ku, Tokyo, 173-0015, Japan. hmori@tmig.or.jp|Proteomics Collaboration Center, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakaecho, Itabashi-ku, Tokyo, 173-0015, Japan. hmori@tmig.or.jp', 'Japan|Japan|Japan', 12, 'Computational Biology|Computer Graphics|Database Management Systems|Databases, Protein|Electrophoresis, Gel, Two-Dimensional|Information Dissemination|Information Storage and Retrieval|Internet|Laboratories|Peptide Mapping|Proteomics|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-430', '17018156', 'In the post-genome era, most research scientists working in the field of proteomics are confronted with difficulties in management of large volumes of data, which they are required to keep in formats suitable for subsequent data mining. Therefore, a well-developed open source laboratory information management system (LIMS) should be available for their proteomics research studies.'),
(91101, 2006, 'bmc', 'The BiSearch web server', 'Arányi, Tamás|Váradi, András|Simon, István|Tusnády, Gábor E', 'lnstitute of Enzymology, BRC, HAS, H-1113 Karolina út 29, Budapest, Hungary. aranyi@enzim.hu|lnstitute of Enzymology, BRC, HAS, H-1113 Karolina út 29, Budapest, Hungary. aranyi@enzim.hu|lnstitute of Enzymology, BRC, HAS, H-1113 Karolina út 29, Budapest, Hungary. aranyi@enzim.hu|lnstitute of Enzymology, BRC, HAS, H-1113 Karolina út 29, Budapest, Hungary. aranyi@enzim.hu', 'Hungary|Hungary|Hungary|Hungary', 63, 'DNA Primers|DNA, Complementary|Databases, Nucleic Acid|Internet|Polymerase Chain Reaction', 'Journal Article', '10.1186/1471-2105-7-431', '17022803', 'A large number of PCR primer-design softwares are available online. However, only very few of them can be used for the design of primers to amplify bisulfite-treated DNA templates, necessary to determine genomic DNA methylation profiles. Indeed, the number of studies on bisulfite-treated templates exponentially increases as determining DNA methylation becomes more important in the diagnosis of cancers. Bisulfite-treated DNA is difficult to amplify since undesired PCR products are often amplified due to the increased sequence redundancy after the chemical conversion. In order to increase the efficiency of PCR primer-design, we have developed BiSearch web server, an online primer-design tool for both bisulfite-treated and native DNA templates.'),
(91102, 2006, 'bmc', 'Feature selection using Haar wavelet power spectrum', 'Subramani, Prabakaran|Sahu, Rajendra|Verma, Shekhar', 'ABV-Indian Institute of Information Technology and Management, Gwalior, India. pra_spin2@yahoo.com|ABV-Indian Institute of Information Technology and Management, Gwalior, India. pra_spin2@yahoo.com|ABV-Indian Institute of Information Technology and Management, Gwalior, India. pra_spin2@yahoo.com', 'India|India|India', 26, 'Artificial Intelligence|Cluster Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-7-432', '17022808', 'Feature selection is an approach to overcome the curse of dimensionality in complex researches like disease classification using microarrays. Statistical methods are utilized more in this domain. Most of them do not fit for a wide range of datasets. The transform oriented signal processing domains are not probed much when other fields like image and video processing utilize them well. Wavelets, one of such techniques, have the potential to be utilized in feature selection method. The aim of this paper is to assess the capability of Haar wavelet power spectrum in the problem of clustering and gene selection based on expression data in the context of disease classification and to propose a method based on Haar wavelet power spectrum.'),
(91103, 2006, 'bmc', 'M-GCAT: interactively and efficiently constructing large-scale multiple genome comparison frameworks in closely related species', 'Treangen, Todd J|Messeguer, Xavier', 'Dept. of Computer Science, Technical University of Catalonia, Barcelona, Spain. treangen@lsi.upc.edu|Dept. of Computer Science, Technical University of Catalonia, Barcelona, Spain. treangen@lsi.upc.edu', 'Spain|Spain', 64, 'Algorithms|Bacteria|Base Sequence|Chromosome Mapping|Genome, Bacterial|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software|Species Specificity|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-433', '17022809', 'Due to recent advances in whole genome shotgun sequencing and assembly technologies, the financial cost of decoding an organisms DNA has been drastically reduced, resulting in a recent explosion of genomic sequencing projects. This increase in related genomic data will allow for in depth studies of evolution in closely related species through multiple whole genome comparisons.'),
(91104, 2006, 'bmc', 'Rank-statistics based enrichment-site prediction algorithm developed for chromatin immunoprecipitation on chip experiments', 'Ghosh, Srinka|Hirsch, Heather A|Sekinger, Edward|Struhl, Kevin|Gingeras, Thomas R', 'Affymetrix Inc., Santa Clara, CA 95051, USA. srinka_ghosh@affymetrix.com|Affymetrix Inc., Santa Clara, CA 95051, USA. srinka_ghosh@affymetrix.com|Affymetrix Inc., Santa Clara, CA 95051, USA. srinka_ghosh@affymetrix.com|Affymetrix Inc., Santa Clara, CA 95051, USA. srinka_ghosh@affymetrix.com|Affymetrix Inc., Santa Clara, CA 95051, USA. srinka_ghosh@affymetrix.com', 'United States|United States|United States|United States|United States', 8, 'Algorithms|Chromatin Immunoprecipitation|Microarray Analysis|Predictive Value of Tests|Statistics, Nonparametric', 'Comparative Study', '10.1186/1471-2105-7-434', '17022824', 'High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. Tiling arrays are increasingly used in chromatin immunoprecipitation (IP) experiments (ChIP on chip). ChIP on chip facilitates the generation of genome-wide maps of in-vivo interactions between DNA-associated proteins including transcription factors and DNA. Analysis of the hybridization of an immunoprecipitated sample to a tiling array facilitates the identification of ChIP-enriched segments of the genome. These enriched segments are putative targets of antibody assayable regulatory elements. The enrichment response is not ubiquitous across the genome. Typically 5 to 10% of tiled probes manifest some significant enrichment. Depending upon the factor being studied, this response can drop to less than 1%. The detection and assessment of significance for interactions that emanate from non-canonical and/or un-annotated regions of the genome is especially challenging. This is the motivation behind the proposed algorithm.'),
(91105, 2006, 'bmc', 'Coloring the Mu transpososome', 'Darcy, Isabel K|Chang, Jeff|Druivenga, Nathan|McKinney, Colin|Medikonduri, Ram K|Mills, Stacy|Navarra-Madsen, Junalyn|Ponnusamy, Arun|Sweet, Jesse|Thompson, Travis', 'Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu|Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu|Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu|Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu|Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu|Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu|Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu|Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu|Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu|Mathematics Department, University of Iowa, Iowa City, IA 52242, USA. idarcy@math.uiowa.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 14, 'Algorithms|Bacteriophage mu|Binding Sites|DNA Transposable Elements|DNA, Superhelical|DNA, Viral|DNA-Binding Proteins|Integrases|Models, Chemical|Models, Genetic|Nucleic Acid Conformation|Protein Binding|Protein Conformation|Software|Transposases', 'Journal Article', '10.1186/1471-2105-7-435', '17022825', 'Tangle analysis has been applied successfully to study proteins which bind two segments of DNA and can knot and link circular DNA. We show how tangle analysis can be extended to model any stable protein-DNA complex.'),
(91106, 2006, 'bmc', 'ORENZA: a web resource for studying ORphan ENZyme activities', 'Lespinet, Olivier|Labedan, Bernard', 'Institut de Génétique et Microbiologie, CNRS UMR 8621, Université Paris-Sud, Bâtiment 400, 91405 Orsay Cedex, France. olivier.lespinet@igmors.u-psud.fr|Institut de Génétique et Microbiologie, CNRS UMR 8621, Université Paris-Sud, Bâtiment 400, 91405 Orsay Cedex, France. olivier.lespinet@igmors.u-psud.fr', 'France|France', 24, 'Amino Acid Sequence|Databases, Genetic|Enzymes|Internet|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-7-436', '17026747', 'Despite the current availability of several hundreds of thousands of amino acid sequences, more than 36% of the enzyme activities (EC numbers) defined by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB) are not associated with any amino acid sequence in major public databases. This wide gap separating knowledge of biochemical function and sequence information is found for nearly all classes of enzymes. Thus, there is an urgent need to explore these sequence-less EC numbers, in order to progressively close this gap.'),
(91107, 2006, 'bmc', 'STAR: predicting recombination sites from amino acid sequence', 'Bauer, Denis C|Bodén, Mikael|Thier, Ricarda|Gillam, Elizabeth M', 'Institute for Molecular Bioscience, The University of Queensland, QLD 4072, Australia. d.bauer@imb.uq.edu.au|Institute for Molecular Bioscience, The University of Queensland, QLD 4072, Australia. d.bauer@imb.uq.edu.au|Institute for Molecular Bioscience, The University of Queensland, QLD 4072, Australia. d.bauer@imb.uq.edu.au|Institute for Molecular Bioscience, The University of Queensland, QLD 4072, Australia. d.bauer@imb.uq.edu.au', 'Australia|Australia|Australia|Australia', 7, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Binding Sites|Molecular Sequence Data|Protein Binding|Proteins|Recombinant Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-7-437', '17026775', 'Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probability that hybrid sequences have the desired properties is increased dramatically. The prohibitive requirements for applying current tools led us to investigate machine learning to assist in finding useful recombination sites from amino acid sequence alone.'),
(91108, 2006, 'bmc', 'QualitySNP: a pipeline for detecting single nucleotide polymorphisms and insertions/deletions in EST data from diploid and polyploid species', 'Tang, Jifeng|Vosman, Ben|Voorrips, Roeland E|van der Linden, C Gerard|Leunissen, Jack A M', 'Plant Research International, PO Box 16, 6700 AA Wageningen, The Netherlands. jifeng.tang@wur.nl|Plant Research International, PO Box 16, 6700 AA Wageningen, The Netherlands. jifeng.tang@wur.nl|Plant Research International, PO Box 16, 6700 AA Wageningen, The Netherlands. jifeng.tang@wur.nl|Plant Research International, PO Box 16, 6700 AA Wageningen, The Netherlands. jifeng.tang@wur.nl|Plant Research International, PO Box 16, 6700 AA Wageningen, The Netherlands. jifeng.tang@wur.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 102, 'Base Sequence|Chromosome Mapping|DNA Mutational Analysis|DNA Transposable Elements|Databases, Genetic|Diploidy|Expressed Sequence Tags|Gene Deletion|Molecular Sequence Data|Polymorphism, Single Nucleotide|Polyploidy|Software', 'Evaluation Studies', '10.1186/1471-2105-7-438', '17029635', 'Single nucleotide polymorphisms (SNPs) are important tools in studying complex genetic traits and genome evolution. Computational strategies for SNP discovery make use of the large number of sequences present in public databases (in most cases as expressed sequence tags (ESTs)) and are considered to be faster and more cost-effective than experimental procedures. A major challenge in computational SNP discovery is distinguishing allelic variation from sequence variation between paralogous sequences, in addition to recognizing sequencing errors. For the majority of the public EST sequences, trace or quality files are lacking which makes detection of reliable SNPs even more difficult because it has to rely on sequence comparisons only.'),
(91109, 2006, 'bmc', 'TreeDyn: towards dynamic graphics and annotations for analyses of trees', 'Chevenet, François|Brun, Christine|Bañuls, Anne-Laure|Jacq, Bernard|Christen, Richard', 'Laboratoire de Génétique et Evolution des Maladies Infectieuses, UMR CNRS/IRD 2724, IRD, 911 avenue Agropolis, BP 64501, 34394 Montpellier Cedex 5, France. chevenet@ird.fr|Laboratoire de Génétique et Evolution des Maladies Infectieuses, UMR CNRS/IRD 2724, IRD, 911 avenue Agropolis, BP 64501, 34394 Montpellier Cedex 5, France. chevenet@ird.fr|Laboratoire de Génétique et Evolution des Maladies Infectieuses, UMR CNRS/IRD 2724, IRD, 911 avenue Agropolis, BP 64501, 34394 Montpellier Cedex 5, France. chevenet@ird.fr|Laboratoire de Génétique et Evolution des Maladies Infectieuses, UMR CNRS/IRD 2724, IRD, 911 avenue Agropolis, BP 64501, 34394 Montpellier Cedex 5, France. chevenet@ird.fr|Laboratoire de Génétique et Evolution des Maladies Infectieuses, UMR CNRS/IRD 2724, IRD, 911 avenue Agropolis, BP 64501, 34394 Montpellier Cedex 5, France. chevenet@ird.fr', 'France|France|France|France|France', 0, 'Computer Graphics|Databases, Genetic|Decision Trees', 'Journal Article', '10.1186/1471-2105-7-439', '17032440', 'Analyses of biomolecules for biodiversity, phylogeny or structure/function studies often use graphical tree representations. Many powerful tree editors are now available, but existing tree visualization tools make little use of meta-information related to the entities under study such as taxonomic descriptions or gene functions that can hardly be encoded within the tree itself (if using popular tree formats). Consequently, a tedious manual analysis and post-processing of the tree graphics are required if one needs to use external information for displaying or investigating trees.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91110, 2006, 'bmc', 'A graph-search framework for associating gene identifiers with documents', 'Cohen, William W|Minkov, Einat', 'Department of Machine Learning, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA. wcohen@cs.cmu.edu|Department of Machine Learning, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA. wcohen@cs.cmu.edu', 'United States|United States', 18, 'Animals|Computational Biology|Computer Graphics|Databases, Genetic|Mice|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-7-440', '17032441', 'One step in the model organism database curation process is to find, for each article, the identifier of every gene discussed in the article. We consider a relaxation of this problem suitable for semi-automated systems, in which each article is associated with a ranked list of possible gene identifiers, and experimentally compare methods for solving this geneId ranking problem. In addition to baseline approaches based on combining named entity recognition (NER) systems with a soft dictionary of gene synonyms, we evaluate a graph-based method which combines the outputs of multiple NER systems, as well as other sources of information, and a learning method for reranking the output of the graph-based method.'),
(91111, 2006, 'bmc', 'Exhaustive assignment of compositional bias reveals universally prevalent biased regions: analysis of functional associations in human and Drosophila', 'Harrison, Paul M', 'Dept. of Biology, McGill University, Stewart Biology Building, 1205 Dr, Penfield Ave, Montreal, QC, H3A 1B1, Canada. paul.harrison@mcgill.ca', 'Canada', 0, 'Animals|Bias|Databases, Nucleic Acid|Drosophila melanogaster|Humans|Mice|Proteome|Rats|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-7-441', '17032452', 'Compositionally biased (CB) regions are stretches in protein sequences made from mainly a distinct subset of amino acid residues, such regions are frequently associated with a structural role in the cell, or with protein disorder.'),
(91112, 2006, 'bmc', 'A simple method to combine multiple molecular biomarkers for dichotomous diagnostic classification', 'Mamtani, Manju R|Thakre, Tushar P|Kalkonde, Mrunal Y|Amin, Manik A|Kalkonde, Yogeshwar V|Amin, Amit P|Kulkarni, Hemant', 'Lata Medical Research Foundation, Nagpur, India. mamtani@uthscsa.edu|Lata Medical Research Foundation, Nagpur, India. mamtani@uthscsa.edu|Lata Medical Research Foundation, Nagpur, India. mamtani@uthscsa.edu|Lata Medical Research Foundation, Nagpur, India. mamtani@uthscsa.edu|Lata Medical Research Foundation, Nagpur, India. mamtani@uthscsa.edu|Lata Medical Research Foundation, Nagpur, India. mamtani@uthscsa.edu|Lata Medical Research Foundation, Nagpur, India. mamtani@uthscsa.edu', 'India|India|India|India|India|India|India', 0, 'Algorithms|Biomarkers|Genetic Markers|Molecular Diagnostic Techniques', 'Journal Article', '10.1186/1471-2105-7-442', '17032455', 'In spite of the recognized diagnostic potential of biomarkers, the quest for squelching noise and wringing in information from a given set of biomarkers continues. Here, we suggest a statistical algorithm that--assuming each molecular biomarker to be a diagnostic test--enriches the diagnostic performance of an optimized set of independent biomarkers employing established statistical techniques. We validated the proposed algorithm using several simulation datasets in addition to four publicly available real datasets that compared i) subjects having cancer with those without, ii) subjects with two different cancers, iii) subjects with two different types of one cancer, and iv) subjects with same cancer resulting in differential time to metastasis.'),
(91113, 2006, 'bmc', 'GOLEM: an interactive graph-based gene-ontology navigation and analysis tool', 'Sealfon, Rachel S G|Hibbs, Matthew A|Huttenhower, Curtis|Myers, Chad L|Troyanskaya, Olga G', 'Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ, USA. sealfon@princeton.edu|Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ, USA. sealfon@princeton.edu|Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ, USA. sealfon@princeton.edu|Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ, USA. sealfon@princeton.edu|Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ, USA. sealfon@princeton.edu', 'United States|United States|United States|United States|United States', 0, 'Computer Graphics|Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Protein Interaction Mapping|Proteins|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-443', '17032457', 'The Gene Ontology has become an extremely useful tool for the analysis of genomic data and structuring of biological knowledge. Several excellent software tools for navigating the gene ontology have been developed. However, no existing system provides an interactively expandable graph-based view of the gene ontology hierarchy. Furthermore, most existing tools are web-based or require an Internet connection, will not load local annotations files, and provide either analysis or visualization functionality, but not both.'),
(91114, 2006, 'bmc', 'Testing statistical significance scores of sequence comparison methods with structure similarity', 'Hulsen, Tim|de Vlieg, Jacob|Leunissen, Jack A M|Groenen, Peter M A', 'Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. T.Hulsen@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. T.Hulsen@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. T.Hulsen@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. T.Hulsen@cmbi.ru.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 8, 'Base Sequence|Databases, Protein|Humans|Sequence Alignment|Sequence Analysis, Protein|Structural Homology, Protein', 'Comparative Study', '10.1186/1471-2105-7-444', '17038163', 'In the past years the Smith-Waterman sequence comparison algorithm has gained popularity due to improved implementations and rapidly increasing computing power. However, the quality and sensitivity of a database search is not only determined by the algorithm but also by the statistical significance testing for an alignment. The e-value is the most commonly used statistical validation method for sequence database searching. The CluSTr database and the Protein World database have been created using an alternative statistical significance test: a Z-score based on Monte-Carlo statistics. Several papers have described the superiority of the Z-score as compared to the e-value, using simulated data. We were interested if this could be validated when applied to existing, evolutionary related protein sequences.'),
(91115, 2006, 'bmc', 'Analysis of optimal phenotypic space using elementary modes as applied to Corynebacterium glutamicum', 'Gayen, Kalyan|Venkatesh, K V', 'Department of Chemical Engineering, Indian Institute of Technology, Bombay, Powai, Mumbai-400 076, India. gkalyan@iitb.ac.in|Department of Chemical Engineering, Indian Institute of Technology, Bombay, Powai, Mumbai-400 076, India. gkalyan@iitb.ac.in', 'India|India', 21, 'Corynebacterium glutamicum|Gene Regulatory Networks|Phenotype|Sequence Analysis', 'Journal Article', '10.1186/1471-2105-7-445', '17038164', 'Quantification of the metabolic network of an organism offers insights into possible ways of developing mutant strain for better productivity of an extracellular metabolite. The first step in this quantification is the enumeration of stoichiometries of all reactions occurring in a metabolic network. The structural details of the network in combination with experimentally observed accumulation rates of external metabolites can yield flux distribution at steady state. One such methodology for quantification is the use of elementary modes, which are minimal set of enzymes connecting external metabolites. Here, we have used a linear objective function subject to elementary modes as constraint to determine the fluxes in the metabolic network of Corynebacterium glutamicum. The feasible phenotypic space was evaluated at various combinations of oxygen and ammonia uptake rates.'),
(91116, 2006, 'bmc', 'CpGcluster: a distance-based algorithm for CpG-island detection', 'Hackenberg, Michael|Previti, Christopher|Luque-Escamilla, Pedro Luis|Carpena, Pedro|Martínez-Aroza, José|Oliver, José L', 'Dpto. de Genética, Facultad de Ciencias, Universidad de Granada, Spain. mlhack@gmail.com|Dpto. de Genética, Facultad de Ciencias, Universidad de Granada, Spain. mlhack@gmail.com|Dpto. de Genética, Facultad de Ciencias, Universidad de Granada, Spain. mlhack@gmail.com|Dpto. de Genética, Facultad de Ciencias, Universidad de Granada, Spain. mlhack@gmail.com|Dpto. de Genética, Facultad de Ciencias, Universidad de Granada, Spain. mlhack@gmail.com|Dpto. de Genética, Facultad de Ciencias, Universidad de Granada, Spain. mlhack@gmail.com', 'Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Animals|CpG Islands|Genome|Humans|Mice', 'Comparative Study', '10.1186/1471-2105-7-446', '17038168', 'Despite their involvement in the regulation of gene expression and their importance as genomic markers for promoter prediction, no objective standard exists for defining CpG islands (CGIs), since all current approaches rely on a large parameter space formed by the thresholds of length, CpG fraction and G+C content.'),
(91117, 2006, 'bmc', 'Statistical inference of chromosomal homology based on gene colinearity and applications to Arabidopsis and rice', 'Wang, Xiyin|Shi, Xiaoli|Li, Zhe|Zhu, Qihui|Kong, Lei|Tang, Wen|Ge, Song|Luo, Jingchu', 'College of Life Sciences, National Laboratory of Plant Genetic Engineering and Protein Engineering, Center of Bioinformatics, Peking University, Beijing 100871, China. wangxy@mail.cbi.pku.edu.cn|College of Life Sciences, National Laboratory of Plant Genetic Engineering and Protein Engineering, Center of Bioinformatics, Peking University, Beijing 100871, China. wangxy@mail.cbi.pku.edu.cn|College of Life Sciences, National Laboratory of Plant Genetic Engineering and Protein Engineering, Center of Bioinformatics, Peking University, Beijing 100871, China. wangxy@mail.cbi.pku.edu.cn|College of Life Sciences, National Laboratory of Plant Genetic Engineering and Protein Engineering, Center of Bioinformatics, Peking University, Beijing 100871, China. wangxy@mail.cbi.pku.edu.cn|College of Life Sciences, National Laboratory of Plant Genetic Engineering and Protein Engineering, Center of Bioinformatics, Peking University, Beijing 100871, China. wangxy@mail.cbi.pku.edu.cn|College of Life Sciences, National Laboratory of Plant Genetic Engineering and Protein Engineering, Center of Bioinformatics, Peking University, Beijing 100871, China. wangxy@mail.cbi.pku.edu.cn|College of Life Sciences, National Laboratory of Plant Genetic Engineering and Protein Engineering, Center of Bioinformatics, Peking University, Beijing 100871, China. wangxy@mail.cbi.pku.edu.cn|College of Life Sciences, National Laboratory of Plant Genetic Engineering and Protein Engineering, Center of Bioinformatics, Peking University, Beijing 100871, China. wangxy@mail.cbi.pku.edu.cn', 'China|China|China|China|China|China|China|China', 77, 'Algorithms|Arabidopsis|Base Sequence|Chromosome Mapping|Chromosomes, Plant|Computer Simulation|Data Interpretation, Statistical|Genome, Plant|Models, Genetic|Models, Statistical|Molecular Sequence Data|Multigene Family|Oryza|Sequence Homology, Nucleic Acid|Synteny', 'Evaluation Studies', '10.1186/1471-2105-7-447', '17038171', 'The identification of chromosomal homology will shed light on such mysteries of genome evolution as DNA duplication, rearrangement and loss. Several approaches have been developed to detect chromosomal homology based on gene synteny or colinearity. However, the previously reported implementations lack statistical inferences which are essential to reveal actual homologies.'),
(91118, 2006, 'bmc', 'Gene function classification using Bayesian models with hierarchy-based priors', 'Shahbaba, Babak|Neal, Radford M', 'Dept. of Public Health Sciences, Biostatistics, University of Toronto, Toronto, Ontario, Canada. babak@stat.utoronto.ca|Dept. of Public Health Sciences, Biostatistics, University of Toronto, Toronto, Ontario, Canada. babak@stat.utoronto.ca', 'Canada|Canada', 17, 'Bayes Theorem|Genes|Models, Genetic', 'Journal Article', '10.1186/1471-2105-7-448', '17038174', 'We investigate whether annotation of gene function can be improved using a classification scheme that is aware that functional classes are organized in a hierarchy. The classifiers look at phylogenic descriptors, sequence based attributes, and predicted secondary structure. We discuss three Bayesian models and compare their performance in terms of predictive accuracy. These models are the ordinary multinomial logit (MNL) model, a hierarchical model based on a set of nested MNL models, and an MNL model with a prior that introduces correlations between the parameters for classes that are nearby in the hierarchy. We also provide a new scheme for combining different sources of information. We use these models to predict the functional class of Open Reading Frames (ORFs) from the E. coli genome.'),
(91119, 2006, 'bmc', 'Integrative missing value estimation for microarray data', 'Hu, Jianjun|Li, Haifeng|Waterman, Michael S|Zhou, Xianghong Jasmine', 'Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 900089, USA. jianjunh@usc.edu|Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 900089, USA. jianjunh@usc.edu|Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 900089, USA. jianjunh@usc.edu|Molecular and Computational Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 900089, USA. jianjunh@usc.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Database Management Systems|Databases, Genetic|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Likelihood Functions|Markov Chains|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sample Size|Systems Integration', 'Journal Article', '10.1186/1471-2105-7-449', '17038176', 'Missing value estimation is an important preprocessing step in microarray analysis. Although several methods have been developed to solve this problem, their performance is unsatisfactory for datasets with high rates of missing data, high measurement noise, or limited numbers of samples. In fact, more than 80% of the time-series datasets in Stanford Microarray Database contain less than eight samples.'),
(91120, 2006, 'bmc', 'Genepi: a blackboard framework for genome annotation', 'Descorps-Declère, Stéphane|Ziébelin, Danielle|Rechenmann, François|Viari, Alain', 'GENOME express, Meylan, France. Stephane.Descorps-declere@inrialpes.fr|GENOME express, Meylan, France. Stephane.Descorps-declere@inrialpes.fr|GENOME express, Meylan, France. Stephane.Descorps-declere@inrialpes.fr|GENOME express, Meylan, France. Stephane.Descorps-declere@inrialpes.fr', 'France|France|France|France', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Databases, Genetic|Genome|Information Storage and Retrieval|Molecular Sequence Data|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-450', '17038181', 'Genome annotation can be viewed as an incremental, cooperative, data-driven, knowledge-based process that involves multiple methods to predict gene locations and structures. This process might have to be executed more than once and might be subjected to several revisions as the biological (new data) or methodological (new methods) knowledge evolves. In this context, although a lot of annotation platforms already exist, there is still a strong need for computer systems which take in charge, not only the primary annotation, but also the update and advance of the associated knowledge. In this paper, we propose to adopt a blackboard architecture for designing such a system'),
(91121, 2006, 'bmc', 'MIMOX: a web tool for phage display based epitope mapping', 'Huang, Jian|Gutteridge, Alex|Honda, Wataru|Kanehisa, Minoru', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan. hjian@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan. hjian@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan. hjian@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan. hjian@kuicr.kyoto-u.ac.jp', 'Japan|Japan|Japan|Japan', 70, 'Bacteriophages|Epitope Mapping|Internet|Peptide Library|Protein Structure, Secondary', 'Journal Article', '10.1186/1471-2105-7-451', '17038191', 'Phage display is widely used in basic research such as the exploration of protein-protein interaction sites and networks, and applied research such as the development of new drugs, vaccines, and diagnostics. It has also become a promising method for epitope mapping. Research on new algorithms that assist and automate phage display based epitope mapping has attracted many groups. Most of the existing tools have not been implemented as an online service until now however, making it less convenient for the community to access, utilize, and evaluate them.'),
(91122, 2006, 'bmc', 'A Fisheye Viewer for microarray-based gene expression data', 'Wu, Min|Thao, Cheng|Mu, Xiangming|Munson, Ethan V', 'University of Wisconsin Milwaukee, Department of Health Sciences, Milwaukee, Wisconsin 53211, USA. wu@uwm.edu|University of Wisconsin Milwaukee, Department of Health Sciences, Milwaukee, Wisconsin 53211, USA. wu@uwm.edu|University of Wisconsin Milwaukee, Department of Health Sciences, Milwaukee, Wisconsin 53211, USA. wu@uwm.edu|University of Wisconsin Milwaukee, Department of Health Sciences, Milwaukee, Wisconsin 53211, USA. wu@uwm.edu', 'United States|United States|United States|United States', 0, 'Gene Expression|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Programming Languages|Software|Statistics as Topic|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-452', '17038193', 'Microarray has been widely used to measure the relative amounts of every mRNA transcript from the genome in a single scan. Biologists have been accustomed to reading their experimental data directly from tables. However, microarray data are quite large and are stored in a series of files in a machine-readable format, so direct reading of the full data set is not feasible. The challenge is to design a user interface that allows biologists to usefully view large tables of raw microarray-based gene expression data. This paper presents one such interface--an electronic table (E-table) that uses fisheye distortion technology.'),
(91123, 2006, 'bmc', 'REEF: searching REgionally Enriched Features in genomes', 'Coppe, Alessandro|Danieli, Gian Antonio|Bortoluzzi, Stefania', 'Department of Biology, University of Padova, via G, Colombo 3, 35131, Padova, Italy. ale@telethon.bio.unipd.it|Department of Biology, University of Padova, via G, Colombo 3, 35131, Padova, Italy. ale@telethon.bio.unipd.it|Department of Biology, University of Padova, via G, Colombo 3, 35131, Padova, Italy. ale@telethon.bio.unipd.it', 'Italy|Italy|Italy', 30, 'Algorithms|Chromosome Mapping|Conserved Sequence|Genetic Linkage|Linkage Disequilibrium|Quantitative Trait Loci|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-7-453', '17042935', 'In Eukaryotic genomes, different features including genes are not uniformly distributed. The integration of annotation information and genomic position of functional DNA elements in the Eukaryotic genomes opened the way to test novel hypotheses of higher order genome organization and regulation of expression.'),
(91124, 2006, 'bmc', 'Whole genome association mapping by incompatibilities and local perfect phylogenies', 'Mailund, Thomas|Besenbacher, Søren|Schierup, Mikkel H', 'Department of Statistics, University of Oxford, UK. mailund@stats.ox.ac.uk|Department of Statistics, University of Oxford, UK. mailund@stats.ox.ac.uk|Department of Statistics, University of Oxford, UK. mailund@stats.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Chromosome Mapping|Cystic Fibrosis|Cytochrome P-450 CYP2D6|DNA Mutational Analysis|Genetic Predisposition to Disease|Humans|Linkage Disequilibrium|Phylogeny|Polymorphism, Single Nucleotide', 'Evaluation Studies', '10.1186/1471-2105-7-454', '17042942', 'With current technology, vast amounts of data can be cheaply and efficiently produced in association studies, and to prevent data analysis to become the bottleneck of studies, fast and efficient analysis methods that scale to such data set sizes must be developed.'),
(91125, 2006, 'bmc', 'Building multiclass classifiers for remote homology detection and fold recognition', 'Rangwala, Huzefa|Karypis, George', 'Department of Computer Science & Engineering, University of Minnesota, Minneapolis, Minnesota, USA. rangwala@cs.umn.edu|Department of Computer Science & Engineering, University of Minnesota, Minneapolis, Minnesota, USA. rangwala@cs.umn.edu', 'United States|United States', 18, 'Algorithms|Protein Folding|Protein Structure, Secondary|Proteins|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-7-455', '17042943', 'Protein remote homology detection and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines are currently one of the most effective methods for solving these problems. These methods are primarily used to solve binary classification problems and they have not been extensively used to solve the more general multiclass remote homology prediction and fold recognition problems.'),
(91126, 2006, 'bmc', 'A framework for protein structure classification and identification of novel protein structures', 'Kim, You Jung|Patel, Jignesh M', 'Computer Science and Engineering, University of Michigan, Ann Arbor, USA. youjkim@eecs.umich.edu|Computer Science and Engineering, University of Michigan, Ann Arbor, USA. youjkim@eecs.umich.edu', 'United States|United States', 19, 'Artificial Intelligence|Computer Simulation|Models, Chemical|Models, Molecular|Pattern Recognition, Automated|Protein Conformation|Protein Folding|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-7-456', '17042958', 'Protein structure classification plays a central role in understanding the function of a protein molecule with respect to all known proteins in a structure database. With the rapid increase in the number of new protein structures, the need for automated and accurate methods for protein classification is increasingly important.'),
(91127, 2006, 'bmc', 'Comparison of protein interaction networks reveals species conservation and divergence', 'Liang, Zhi|Xu, Meng|Teng, Maikun|Niu, Liwen', 'Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science & Technology of China, 96 Jinzhai Road, Hefei, Anhui 230027, China. liangzhi968@ustc.edu|Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science & Technology of China, 96 Jinzhai Road, Hefei, Anhui 230027, China. liangzhi968@ustc.edu|Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science & Technology of China, 96 Jinzhai Road, Hefei, Anhui 230027, China. liangzhi968@ustc.edu|Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science & Technology of China, 96 Jinzhai Road, Hefei, Anhui 230027, China. liangzhi968@ustc.edu', 'China|China|China|China', 0, 'Animals|Computational Biology|Conserved Sequence|Gene Regulatory Networks|Humans|Protein Interaction Mapping|Proteins|Species Specificity|Yeasts', 'Comparative Study', '10.1186/1471-2105-7-457', '17044912', 'Recent progresses in high-throughput proteomics have provided us with a first chance to characterize protein interaction networks (PINs), but also raised new challenges in interpreting the accumulating data.'),
(91128, 2006, 'bmc', 'NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm', 'Xue, Yu|Chen, Hu|Jin, Changjiang|Sun, Zhirong|Yao, Xuebiao', 'Laboratory of Cellular Dynamics, Hefei National Laboratory for Physical Sciences, and the University of Science and Technology of China, Hefei, China. yxue@mail.ustc.edu.cn|Laboratory of Cellular Dynamics, Hefei National Laboratory for Physical Sciences, and the University of Science and Technology of China, Hefei, China. yxue@mail.ustc.edu.cn|Laboratory of Cellular Dynamics, Hefei National Laboratory for Physical Sciences, and the University of Science and Technology of China, Hefei, China. yxue@mail.ustc.edu.cn|Laboratory of Cellular Dynamics, Hefei National Laboratory for Physical Sciences, and the University of Science and Technology of China, Hefei, China. yxue@mail.ustc.edu.cn|Laboratory of Cellular Dynamics, Hefei National Laboratory for Physical Sciences, and the University of Science and Technology of China, Hefei, China. yxue@mail.ustc.edu.cn', 'China|China|China|China|China', 0, 'Acyltransferases|Algorithms|Bayes Theorem|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Palmitates|Protein Binding|Sequence Analysis, Protein|Software|Substrate Specificity', 'Journal Article', '10.1186/1471-2105-7-458', '17044919', 'Protein palmitoylation, an essential and reversible post-translational modification (PTM), has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design.'),
(91129, 2006, 'bmc', 'MannDB - a microbial database of automated protein sequence analyses and evidence integration for protein characterization', 'Zhou, Carol L Ecale|Lam, Marisa W|Smith, Jason R|Zemla, Adam T|Dyer, Matthew D|Kuczmarski, Thomas A|Vitalis, Elizabeth A|Slezak, Thomas R', 'Lawrence Livermore National Laboratory, Pathogen Bio-informatics, Livermore, CA, USA. zhou4@llnl.gov|Lawrence Livermore National Laboratory, Pathogen Bio-informatics, Livermore, CA, USA. zhou4@llnl.gov|Lawrence Livermore National Laboratory, Pathogen Bio-informatics, Livermore, CA, USA. zhou4@llnl.gov|Lawrence Livermore National Laboratory, Pathogen Bio-informatics, Livermore, CA, USA. zhou4@llnl.gov|Lawrence Livermore National Laboratory, Pathogen Bio-informatics, Livermore, CA, USA. zhou4@llnl.gov|Lawrence Livermore National Laboratory, Pathogen Bio-informatics, Livermore, CA, USA. zhou4@llnl.gov|Lawrence Livermore National Laboratory, Pathogen Bio-informatics, Livermore, CA, USA. zhou4@llnl.gov|Lawrence Livermore National Laboratory, Pathogen Bio-informatics, Livermore, CA, USA. zhou4@llnl.gov', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Bacterial Proteins|Binding Sites|Computer Graphics|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Molecular Sequence Data|Protein Binding|Proteome|Sequence Alignment|Sequence Analysis, Protein|Software|Systems Integration|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-459', '17044936', 'MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data.'),
(91130, 2006, 'bmc', 'Representing and comparing protein structures as paths in three-dimensional space', 'Zhi, Degui|Krishna, S Sri|Cao, Haibo|Pevzner, Pavel|Godzik, Adam', 'Department of Plant and Microbial Biology, University of California, Berkeley, California 94720-3102, USA. dzhi@compbio.berkeley.edu|Department of Plant and Microbial Biology, University of California, Berkeley, California 94720-3102, USA. dzhi@compbio.berkeley.edu|Department of Plant and Microbial Biology, University of California, Berkeley, California 94720-3102, USA. dzhi@compbio.berkeley.edu|Department of Plant and Microbial Biology, University of California, Berkeley, California 94720-3102, USA. dzhi@compbio.berkeley.edu|Department of Plant and Microbial Biology, University of California, Berkeley, California 94720-3102, USA. dzhi@compbio.berkeley.edu', 'United States|United States|United States|United States|United States', 12, 'Algorithms|Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1186/1471-2105-7-460', '17052359', 'Most existing formulations of protein structure comparison are based on detailed atomic level descriptions of protein structures and bypass potential insights that arise from a higher-level abstraction.'),
(91131, 2006, 'bmc', 'inGeno--an integrated genome and ortholog viewer for improved genome to genome comparisons', 'Liang, Chunguang|Dandekar, Thomas', 'Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, D-97074 Würzburg, Germany. liang@biozentrum.uni-wuerzburg.de|Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, D-97074 Würzburg, Germany. liang@biozentrum.uni-wuerzburg.de', 'Germany|Germany', 0, 'Base Sequence|Escherichia|Genome|Genome, Bacterial|Genomics|Listeria|Molecular Sequence Data|Sequence Alignment|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-7-461', '17054788', 'Systematic genome comparisons are an important tool to reveal gene functions, pathogenic features, metabolic pathways and genome evolution in the era of post-genomics. Furthermore, such comparisons provide important clues for vaccines and drug development. Existing genome comparison software often lacks accurate information on orthologs, the function of similar genes identified and genome-wide reports and lists on specific functions. All these features and further analyses are provided here in the context of a modular software tool inGeno written in Java with Biojava subroutines.'),
(91132, 2006, 'bmc', 'Java GUI for InterProScan (JIPS): a tool to help process multiple InterProScans and perform ortholog analysis', 'Syed, Aijazuddin|Upton, Chris', 'Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, V8W 3P6, Canada. asyed@uvic.ca|Department of Biochemistry and Microbiology, University of Victoria, Victoria, BC, V8W 3P6, Canada. asyed@uvic.ca', 'Canada|Canada', 0, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Programming Languages|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-462', '17054794', 'Recent, rapid growth in the quantity of available genomic data has generated many protein sequences that are not yet biochemically classified. Thus, the prediction of biochemical function based on structural motifs is an important task in post-genomic analysis. The InterPro databases are a major resource for protein function information. For optimal results, these databases should be searched at regular intervals, since they are frequently updated.'),
(91133, 2006, 'bmc', 'SVRMHC prediction server for MHC-binding peptides', 'Wan, Ji|Liu, Wen|Xu, Qiqi|Ren, Yongliang|Flower, Darren R|Li, Tongbin', 'Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wanji@biocompute.umn.edu|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wanji@biocompute.umn.edu|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wanji@biocompute.umn.edu|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wanji@biocompute.umn.edu|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wanji@biocompute.umn.edu|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wanji@biocompute.umn.edu', 'United States|United States|United States|United States|United States|United States', 87, 'Amino Acid Sequence|Binding Sites|Computer Simulation|Epitope Mapping|Epitopes|Internet|Major Histocompatibility Complex|Models, Chemical|Models, Immunological|Models, Molecular|Molecular Sequence Data|Protein Binding|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1186/1471-2105-7-463', '17059589', 'The binding between antigenic peptides (epitopes) and the MHC molecule is a key step in the cellular immune response. Accurate in silico prediction of epitope-MHC binding affinity can greatly expedite epitope screening by reducing costs and experimental effort.'),
(91134, 2006, 'bmc', 'A summarization approach for Affymetrix GeneChip data using a reference training set from a large, biologically diverse database', 'Katz, Simon|Irizarry, Rafael A|Lin, Xue|Tripputi, Mark|Porter, Mark W', 'Gene Logic Inc., 610 Professional Dr, Gaithersburg, MD, 20876, USA. skatz@genelogic.com|Gene Logic Inc., 610 Professional Dr, Gaithersburg, MD, 20876, USA. skatz@genelogic.com|Gene Logic Inc., 610 Professional Dr, Gaithersburg, MD, 20876, USA. skatz@genelogic.com|Gene Logic Inc., 610 Professional Dr, Gaithersburg, MD, 20876, USA. skatz@genelogic.com|Gene Logic Inc., 610 Professional Dr, Gaithersburg, MD, 20876, USA. skatz@genelogic.com', 'United States|United States|United States|United States|United States', 55, 'Algorithms|Artificial Intelligence|DNA Probes|Databases, Genetic|Genetic Variation|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reference Values|Sequence Analysis, DNA', 'Evaluation Studies', '10.1186/1471-2105-7-464', '17059591', 'Many of the most popular pre-processing methods for Affymetrix expression arrays, such as RMA, gcRMA, and PLIER, simultaneously analyze data across a set of predetermined arrays to improve precision of the final measures of expression. One problem associated with these algorithms is that expression measurements for a particular sample are highly dependent on the set of samples used for normalization and results obtained by normalization with a different set may not be comparable. A related problem is that an organization producing and/or storing large amounts of data in a sequential fashion will need to either re-run the pre-processing algorithm every time an array is added or store them in batches that are pre-processed together. Furthermore, pre-processing of large numbers of arrays requires loading all the feature-level data into memory which is a difficult task even with modern computers. We utilize a scheme that produces all the information necessary for pre-processing using a very large training set that can be used for summarization of samples outside of the training set. All subsequent pre-processing tasks can be done on an individual array basis. We demonstrate the utility of this approach by defining a new version of the Robust Multi-chip Averaging (RMA) algorithm which we refer to as refRMA.'),
(91135, 2006, 'bmc', 'Meta-All: a system for managing metabolic pathway information', 'Weise, Stephan|Grosse, Ivo|Klukas, Christian|Koschützki, Dirk|Scholz, Uwe|Schreiber, Falk|Junker, Björn H', 'Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstr, 3, 06466 Gatersleben, Germany. weise@ipk-gatersleben.de|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstr, 3, 06466 Gatersleben, Germany. weise@ipk-gatersleben.de|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstr, 3, 06466 Gatersleben, Germany. weise@ipk-gatersleben.de|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstr, 3, 06466 Gatersleben, Germany. weise@ipk-gatersleben.de|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstr, 3, 06466 Gatersleben, Germany. weise@ipk-gatersleben.de|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstr, 3, 06466 Gatersleben, Germany. weise@ipk-gatersleben.de|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstr, 3, 06466 Gatersleben, Germany. weise@ipk-gatersleben.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Database Management Systems|Databases, Factual|Metabolic Networks and Pathways', 'Journal Article', '10.1186/1471-2105-7-465', '17059592', 'Many attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed.'),
(91136, 2006, 'bmc', 'ProFAT: a web-based tool for the functional annotation of protein sequences', 'Bradshaw, Charles Richard|Surendranath, Vineeth|Habermann, Bianca', 'Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany. bradshaw@mpi-cbg.de <bradshaw@mpi-cbg.de>|Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany. bradshaw@mpi-cbg.de <bradshaw@mpi-cbg.de>|Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstrasse 108, 01307 Dresden, Germany. bradshaw@mpi-cbg.de <bradshaw@mpi-cbg.de>', 'Germany|Germany|Germany', 5, 'Algorithms|Amino Acid Sequence|Computational Biology|Databases, Protein|Internet|Markov Chains|Protein Structure, Tertiary|Proteins|Sequence Homology, Amino Acid|Software|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-7-466', '17059594', 'The functional annotation of proteins relies on published information concerning their close and remote homologues in sequence databases. Evidence for remote sequence similarity can be further strengthened by a similar biological background of the query sequence and identified database sequences. However, few tools exist so far, that provide a means to include functional information in sequence database searches.'),
(91137, 2006, 'bmc', 'Goulphar: rapid access and expertise for standard two-color microarray normalization methods', 'Lemoine, Sophie|Combes, Florence|Servant, Nicolas|Le Crom, Stéphane', 'IFR36, Plate-forme Transcriptome, Ecole Normale Supérieure, 46 rue dUlm, 75230 Paris cedex05, France. slemoine@biologie.ens.fr|IFR36, Plate-forme Transcriptome, Ecole Normale Supérieure, 46 rue dUlm, 75230 Paris cedex05, France. slemoine@biologie.ens.fr|IFR36, Plate-forme Transcriptome, Ecole Normale Supérieure, 46 rue dUlm, 75230 Paris cedex05, France. slemoine@biologie.ens.fr|IFR36, Plate-forme Transcriptome, Ecole Normale Supérieure, 46 rue dUlm, 75230 Paris cedex05, France. slemoine@biologie.ens.fr', 'France|France|France|France', 50, 'Algorithms|Calibration|Expert Systems|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence, Multiphoton|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-467', '17059595', 'Raw data normalization is a critical step in microarray data analysis because it directly affects data interpretation. Most of the normalization methods currently used are included in the R/BioConductor packages but it is often difficult to identify the most appropriate method. Furthermore, the use of R commands for functions and graphics can introduce mistakes that are difficult to trace. We present here a script written in R that provides a flexible means of access to and monitoring of data normalization for two-color microarrays. This script combines the power of BioConductor and R analysis functions and reduces the amount of R programming required.'),
(91138, 2006, 'bmc', 'SNP-PHAGE--High throughput SNP discovery pipeline', 'Matukumalli, Lakshmi K|Grefenstette, John J|Hyten, David L|Choi, Ik-Young|Cregan, Perry B|Van Tassell, Curtis P', 'US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA. lmatukum@gmu.edu|US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA. lmatukum@gmu.edu|US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA. lmatukum@gmu.edu|US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA. lmatukum@gmu.edu|US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA. lmatukum@gmu.edu|US Department of Agriculture, ARS, Beltsville Agricultural Research Center, Bovine Functional Genomics Laboratory, Beltsville, MD 20705, USA. lmatukum@gmu.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Molecular Sequence Data|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-468', '17059604', 'Single nucleotide polymorphisms (SNPs) as defined here are single base sequence changes or short insertion/deletions between or within individuals of a given species. As a result of their abundance and the availability of high throughput analysis technologies SNP markers have begun to replace other traditional markers such as restriction fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs) and simple sequence repeats (SSRs or microsatellite) markers for fine mapping and association studies in several species. For SNP discovery from chromatogram data, several bioinformatics programs have to be combined to generate an analysis pipeline. Results have to be stored in a relational database to facilitate interrogation through queries or to generate data for further analyses such as determination of linkage disequilibrium and identification of common haplotypes. Although these tasks are routinely performed by several groups, an integrated open source SNP discovery pipeline that can be easily adapted by new groups interested in SNP marker development is currently unavailable.'),
(91139, 2006, 'bmc', 'Evaluating different methods of microarray data normalization', 'Fujita, André|Sato, João Ricardo|Rodrigues, Leonardo de Oliveira|Ferreira, Carlos Eduardo|Sogayar, Mari Cleide', 'Institute of Mathematics and Statistics, University of São Paulo, Rua do Matão, 1010--São Paulo, 05508-090 SP, Brazil. fujita@ime.usp.br|Institute of Mathematics and Statistics, University of São Paulo, Rua do Matão, 1010--São Paulo, 05508-090 SP, Brazil. fujita@ime.usp.br|Institute of Mathematics and Statistics, University of São Paulo, Rua do Matão, 1010--São Paulo, 05508-090 SP, Brazil. fujita@ime.usp.br|Institute of Mathematics and Statistics, University of São Paulo, Rua do Matão, 1010--São Paulo, 05508-090 SP, Brazil. fujita@ime.usp.br|Institute of Mathematics and Statistics, University of São Paulo, Rua do Matão, 1010--São Paulo, 05508-090 SP, Brazil. fujita@ime.usp.br', 'Brazil|Brazil|Brazil|Brazil|Brazil', 0, 'Animals|Cells, Cultured|Data Interpretation, Statistical|Evaluation Studies as Topic|Gene Expression Profiling|Mice|Oligonucleotide Array Sequence Analysis|Reference Values|Regression Analysis', 'Comparative Study', '10.1186/1471-2105-7-469', '17059609', 'With the development of DNA hybridization microarray technologies, nowadays it is possible to simultaneously assess the expression levels of thousands to tens of thousands of genes. Quantitative comparison of microarrays uncovers distinct patterns of gene expression, which define different cellular phenotypes or cellular responses to drugs. Due to technical biases, normalization of the intensity levels is a pre-requisite to performing further statistical analyses. Therefore, choosing a suitable approach for normalization can be critical, deserving judicious consideration.'),
(91140, 2006, 'bmc', 'GeneTools--application for functional annotation and statistical hypothesis testing', 'Beisvag, Vidar|Jünge, Frode K R|Bergum, Hallgeir|Jølsum, Lars|Lydersen, Stian|Günther, Clara-Cecilie|Ramampiaro, Heri|Langaas, Mette|Sandvik, Arne K|Laegreid, Astrid', 'Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. vidar.beisvag@ntnu.no', 'Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Computer Simulation|Data Interpretation, Statistical|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Models, Genetic|Models, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-7-470', '17062145', 'Modern biology has shifted from one gene approaches to methods for genomic-scale analysis like microarray technology, which allow simultaneous measurement of thousands of genes. This has created a need for tools facilitating interpretation of biological data in batch mode. However, such tools often leave the investigator with large volumes of apparently unorganized information. To meet this interpretation challenge, gene-set, or cluster testing has become a popular analytical tool. Many gene-set testing methods and software packages are now available, most of which use a variety of statistical tests to assess the genes in a set for biological information. However, the field is still evolving, and there is a great need for integrated solutions.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91141, 2006, 'bmc', 'The accuracy of several multiple sequence alignment programs for proteins', 'Nuin, Paulo A S|Wang, Zhouzhi|Tillier, Elisabeth R M', 'Division of Cancer Genomics and Proteomics, Ontario Cancer Institute, University Health Network, 101 College St, M5G 1L7, Toronto, Ontario, Canada. pnuin@uhnres.utoronto.ca|Division of Cancer Genomics and Proteomics, Ontario Cancer Institute, University Health Network, 101 College St, M5G 1L7, Toronto, Ontario, Canada. pnuin@uhnres.utoronto.ca|Division of Cancer Genomics and Proteomics, Ontario Cancer Institute, University Health Network, 101 College St, M5G 1L7, Toronto, Ontario, Canada. pnuin@uhnres.utoronto.ca', 'Canada|Canada|Canada', 0, 'Amino Acid Sequence|Computational Biology|Computer Simulation|Databases, Protein|Gene Deletion|Mutation|Protein Conformation|Proteins|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-7-471', '17062146', 'There have been many algorithms and software programs implemented for the inference of multiple sequence alignments of protein and DNA sequences. The true alignment is usually unknown due to the incomplete knowledge of the evolutionary history of the sequences, making it difficult to gauge the relative accuracy of the programs.'),
(91142, 2006, 'bmc', 'CGAT: a comparative genome analysis tool for visualizing alignments in the analysis of complex evolutionary changes between closely related genomes', 'Uchiyama, Ikuo|Higuchi, Toshio|Kobayashi, Ichizo', 'National Institute for Basic Biology, National Institutes of Natural Sciences, Nishigonaka 38, Myodaiji, Okazaki, Aichi 444-8585, Japan. uchiyama@nibb.ac.jp|National Institute for Basic Biology, National Institutes of Natural Sciences, Nishigonaka 38, Myodaiji, Okazaki, Aichi 444-8585, Japan. uchiyama@nibb.ac.jp|National Institute for Basic Biology, National Institutes of Natural Sciences, Nishigonaka 38, Myodaiji, Okazaki, Aichi 444-8585, Japan. uchiyama@nibb.ac.jp', 'Japan|Japan|Japan', 17, 'Algorithms|Bacillus subtilis|Base Composition|Computer Graphics|Conserved Sequence|DNA, Bacterial|Databases, Nucleic Acid|Escherichia coli|Evolution, Molecular|Helicobacter pylori|Polymorphism, Genetic|Repetitive Sequences, Nucleic Acid|Reproducibility of Results|Salmonella enterica|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1186/1471-2105-7-472', '17062155', 'The recent accumulation of closely related genomic sequences provides a valuable resource for the elucidation of the evolutionary histories of various organisms. However, although numerous alignment calculation and visualization tools have been developed to date, the analysis of complex genomic changes, such as large insertions, deletions, inversions, translocations and duplications, still presents certain difficulties.'),
(91143, 2006, 'bmc', 'CAFTAN: a tool for fast mapping, and quality assessment of cDNAs', 'del Val, Coral|Kuryshev, Vladimir Yurjevich|Glatting, Karl-Heinz|Ernst, Peter|Hotz-Wagenblatt, Agnes|Poustka, Annemarie|Suhai, Sandor|Wiemann, Stefan', 'DKFZ, German Cancer Research Center, Division Molecular Biophysics, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de|DKFZ, German Cancer Research Center, Division Molecular Biophysics, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de|DKFZ, German Cancer Research Center, Division Molecular Biophysics, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de|DKFZ, German Cancer Research Center, Division Molecular Biophysics, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de|DKFZ, German Cancer Research Center, Division Molecular Biophysics, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de|DKFZ, German Cancer Research Center, Division Molecular Biophysics, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de|DKFZ, German Cancer Research Center, Division Molecular Biophysics, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de|DKFZ, German Cancer Research Center, Division Molecular Biophysics, Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Chromosome Mapping|Computational Biology|DNA, Complementary|Genome|Humans|RNA Splicing|RNA, Messenger|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1186/1471-2105-7-473', '17064411', 'The German cDNA Consortium has been cloning full length cDNAs and continued with their exploitation in protein localization experiments and cellular assays. However, the efficient use of large cDNA resources requires the development of strategies that are capable of a speedy selection of truly useful cDNAs from biological and experimental noise. To this end we have developed a new high-throughput analysis tool, CAFTAN, which simplifies these efforts and thus fills the gap between large-scale cDNA collections and their systematic annotation and application in functional genomics.'),
(91144, 2006, 'bmc', 'Annotation, submission and screening of repetitive elements in Repbase: RepbaseSubmitter and Censor', 'Kohany, Oleksiy|Gentles, Andrew J|Hankus, Lukasz|Jurka, Jerzy', 'Genetic Information Research Institute, 1925 Landings Drive, Mountain View, CA 94043, USA. kohany@girinst.org|Genetic Information Research Institute, 1925 Landings Drive, Mountain View, CA 94043, USA. kohany@girinst.org|Genetic Information Research Institute, 1925 Landings Drive, Mountain View, CA 94043, USA. kohany@girinst.org|Genetic Information Research Institute, 1925 Landings Drive, Mountain View, CA 94043, USA. kohany@girinst.org', 'United States|United States|United States|United States', 0, 'Animals|DNA Transposable Elements|Database Management Systems|Databases, Nucleic Acid|Humans|Open Reading Frames|Pattern Recognition, Automated|Programming Languages|Repetitive Sequences, Nucleic Acid|Retroelements|Retroviridae|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-7-474', '17064419', 'Repbase is a reference database of eukaryotic repetitive DNA, which includes prototypic sequences of repeats and basic information described in annotations. Updating and maintenance of the database requires specialized tools, which we have created and made available for use with Repbase, and which may be useful as a template for other curated databases.'),
(91145, 2006, 'bmc', 'Normalization and expression changes in predefined sets of proteins using 2D gel electrophoresis: a proteomic study of L-DOPA induced dyskinesia in an animal model of Parkinsons disease using DIGE', 'Kultima, Kim|Scholz, Birger|Alm, Henrik|Sköld, Karl|Svensson, Marcus|Crossman, Alan R|Bezard, Erwan|Andrén, Per E|Lönnstedt, Ingrid', 'Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se|Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se|Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se|Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se|Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se|Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se|Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se|Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se|Department of Pharmaceutical Biosciences, Division of Toxicology, Uppsala University, BMC, Box 594, SE-75124 Uppsala, Sweden. Kim.Kultima@farmbio.uu.se', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 37, 'Animals|Corpus Striatum|Disease Models, Animal|Electrophoresis, Gel, Two-Dimensional|Gene Expression Profiling|Levodopa|Macaca fascicularis|Movement Disorders|Nerve Tissue Proteins|Parkinson Disease, Secondary|Proteome', 'Journal Article', '10.1186/1471-2105-7-475', '17067368', 'Two-Dimensional Difference In Gel Electrophoresis (2D-DIGE) is a powerful tool for measuring differences in protein expression between samples or conditions. However, to remove systematic variability within and between gels the data has to be normalized. In this study we examined the ability of four existing and four novel normalization methods to remove systematic bias in data produced with 2D-DIGE. We also propose a modification of an existing method where the statistical framework determines whether a set of proteins shows an association with the predefined phenotypes of interest. This method was applied to our data generated from a monkey model (Macaca fascicularis) of Parkinsons disease.'),
(91146, 2006, 'bmc', 'Using the nucleotide substitution rate matrix to detect horizontal gene transfer', 'Hamady, Micah|Betterton, M D|Knight, Rob', 'Department of Chemistry and Biochemistry, University of Colorado, Boulder, CO 80309, USA. hamady@colorado.edu <hamady@colorado.edu>|Department of Chemistry and Biochemistry, University of Colorado, Boulder, CO 80309, USA. hamady@colorado.edu <hamady@colorado.edu>|Department of Chemistry and Biochemistry, University of Colorado, Boulder, CO 80309, USA. hamady@colorado.edu <hamady@colorado.edu>', 'United States|United States|United States', 0, 'Computational Biology|Computer Simulation|Gene Transfer, Horizontal|Genome, Human|Humans|Markov Chains|Models, Genetic|Models, Theoretical|Nucleotides|Phylogeny|Reproducibility of Results|Software', 'Journal Article', '10.1186/1471-2105-7-476', '17067382', 'Horizontal gene transfer (HGT) has allowed bacteria to evolve many new capabilities. Because transferred genes perform many medically important functions, such as conferring antibiotic resistance, improved detection of horizontally transferred genes from sequence data would be an important advance. Existing sequence-based methods for detecting HGT focus on changes in nucleotide composition or on differences between gene and genome phylogenies, these methods have high error rates.'),
(91147, 2006, 'bmc', 'Browsing repeats in genomes: Pygram and an application to non-coding region analysis', 'Durand, Patrick|Mahé, Frédéric|Valin, Anne-Sophie|Nicolas, Jacques', 'IRISA/INRIA, Campus de Beaulieu, 35042 Rennes Cedex, France. Patrick.Durand@irisa.fr|IRISA/INRIA, Campus de Beaulieu, 35042 Rennes Cedex, France. Patrick.Durand@irisa.fr|IRISA/INRIA, Campus de Beaulieu, 35042 Rennes Cedex, France. Patrick.Durand@irisa.fr|IRISA/INRIA, Campus de Beaulieu, 35042 Rennes Cedex, France. Patrick.Durand@irisa.fr', 'France|France|France|France', 12, 'Codon|Genome, Archaeal|Genome, Viral|Repetitive Sequences, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-7-477', '17067389', 'A large number of studies on genome sequences have revealed the major role played by repeated sequences in the structure, function, dynamics and evolution of genomes. In-depth repeat analysis requires specialized methods, including visualization techniques, to achieve optimum exploratory power.'),
(91148, 2006, 'bmc', 'Topological basis of signal integration in the transcriptional-regulatory network of the yeast, Saccharomyces cerevisiae', 'Farkas, Illés J|Wu, Chuang|Chennubhotla, Chakra|Bahar, Ivet|Oltvai, Zoltán N', 'Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA. illes.farkas@gmail.com <illes.farkas@gmail.com>|Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA. illes.farkas@gmail.com <illes.farkas@gmail.com>|Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA. illes.farkas@gmail.com <illes.farkas@gmail.com>|Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA. illes.farkas@gmail.com <illes.farkas@gmail.com>|Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15261, USA. illes.farkas@gmail.com <illes.farkas@gmail.com>', 'United States|United States|United States|United States|United States', 21, 'Algorithms|Computer Graphics|Computer Simulation|Databases, Genetic|Evolution, Molecular|Gene Expression Regulation, Fungal|Gene Regulatory Networks|Models, Genetic|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-7-478', '17069658', 'Signal recognition and information processing is a fundamental cellular function, which in part involves comprehensive transcriptional regulatory (TR) mechanisms carried out in response to complex environmental signals in the context of the cells own internal state. However, the network topological basis of developing such integrated responses remains poorly understood.'),
(91149, 2006, 'bmc', 'HybGFS: a hybrid method for genome-fingerprint scanning', 'Shinoda, Kosaku|Yachie, Nozomu|Masuda, Takeshi|Sugiyama, Naoyuki|Sugimoto, Masahiro|Soga, Tomoyoshi|Tomita, Masaru', 'Human Metabolome Technologies, Inc., Tsuruoka, Yamagata, 997-0052, Japan. kshinoda@humanmetabolome.com <kshinoda@humanmetabolome.com>|Human Metabolome Technologies, Inc., Tsuruoka, Yamagata, 997-0052, Japan. kshinoda@humanmetabolome.com <kshinoda@humanmetabolome.com>|Human Metabolome Technologies, Inc., Tsuruoka, Yamagata, 997-0052, Japan. kshinoda@humanmetabolome.com <kshinoda@humanmetabolome.com>|Human Metabolome Technologies, Inc., Tsuruoka, Yamagata, 997-0052, Japan. kshinoda@humanmetabolome.com <kshinoda@humanmetabolome.com>|Human Metabolome Technologies, Inc., Tsuruoka, Yamagata, 997-0052, Japan. kshinoda@humanmetabolome.com <kshinoda@humanmetabolome.com>|Human Metabolome Technologies, Inc., Tsuruoka, Yamagata, 997-0052, Japan. kshinoda@humanmetabolome.com <kshinoda@humanmetabolome.com>|Human Metabolome Technologies, Inc., Tsuruoka, Yamagata, 997-0052, Japan. kshinoda@humanmetabolome.com <kshinoda@humanmetabolome.com>', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 4, 'Algorithms|Chromatography, Liquid|Databases, Genetic|Escherichia coli Proteins|Genes, Bacterial|Peptide Mapping|Recombinant Proteins|Reproducibility of Results|Sequence Analysis, Protein|Software|Tandem Mass Spectrometry|Time Factors', 'Journal Article', '10.1186/1471-2105-7-479', '17069662', 'Protein identification based on mass spectrometry (MS) has previously been performed using peptide mass fingerprinting (PMF) or tandem MS (MS/MS) database searching. However, these methods cannot identify proteins that are not already listed in existing databases. Moreover, the alternative approach of de novo sequencing requires costly equipment and the interpretation of complex MS/MS spectra. Thus, there is a need for novel high-throughput protein-identification methods that are independent of existing predefined protein databases.'),
(91150, 2006, 'bmc', 'RiboSubstrates: a web application addressing the cleavage specificities of ribozymes in designated genomes', 'Lucier, Jean-François|Bergeron, Lucien Junior|Brière, Francis P|Ouellette, Rodney|Elela, Sherif Abou|Perreault, Jean-Pierre', 'RNA Group/Groupe ARN, Sherbrooke, Canada. jean-francois.lucier@usherbrooke.ca|RNA Group/Groupe ARN, Sherbrooke, Canada. jean-francois.lucier@usherbrooke.ca|RNA Group/Groupe ARN, Sherbrooke, Canada. jean-francois.lucier@usherbrooke.ca|RNA Group/Groupe ARN, Sherbrooke, Canada. jean-francois.lucier@usherbrooke.ca|RNA Group/Groupe ARN, Sherbrooke, Canada. jean-francois.lucier@usherbrooke.ca|RNA Group/Groupe ARN, Sherbrooke, Canada. jean-francois.lucier@usherbrooke.ca', 'Canada|Canada|Canada|Canada|Canada|Canada', 12, 'Animals|Databases, Nucleic Acid|Genomics|Hepatitis Delta Virus|Humans|Internet|RNA Interference|RNA, Catalytic|RNA, Messenger|RNA, Small Interfering|Sequence Analysis, DNA|Software|Substrate Specificity', 'Journal Article', '10.1186/1471-2105-7-480', '17076887', 'RNA-dependent gene silencing is becoming a routine tool used in laboratories worldwide. One of the important remaining hurdles in the selection of the target sequence, if not the most important one, is the designing of tools that have minimal off-target effects (i.e. cleaves only the desired sequence). Increasingly, in the current dawn of the post-genomic era, there is a heavy reliance on tools that are suitable for high-throughput functional genomics, consequently more and more bioinformatic software is becoming available. However, to date none have been designed to satisfy the ever-increasing need for the accurate selection of targets for a specific silencing reagent.'),
(91151, 2006, 'bmc', 'Mining expressed sequence tags identifies cancer markers of clinical interest', 'Campagne, Fabien|Skrabanek, Lucy', 'Institute for Computational Biomedicine and Dept. of Physiology and Biophysics, Weill Medical College of Cornell University, New York, NY 10021, USA. fac2003@med.cornell.edu|Institute for Computational Biomedicine and Dept. of Physiology and Biophysics, Weill Medical College of Cornell University, New York, NY 10021, USA. fac2003@med.cornell.edu', 'United States|United States', 20, 'Animals|Biomarkers, Tumor|Expressed Sequence Tags|Gene Expression Regulation, Neoplastic|Genomics|Humans|Mice|Neoplasms|RNA, Messenger|RNA-Binding Proteins|Signal Transduction|Transcription, Genetic', 'Comparative Study', '10.1186/1471-2105-7-481', '17078886', 'Gene expression data are a rich source of information about the transcriptional dis-regulation of genes in cancer. Genes that display differential regulation in cancer are a subtype of cancer biomarkers.'),
(91152, 2006, 'bmc', 'Application of Petri net based analysis techniques to signal transduction pathways', 'Sackmann, Andrea|Heiner, Monika|Koch, Ina', 'Technical University of Applied Sciences Berlin, Bioinformatics group, Seestr, 64, 13347 Berlin, Germany. andrea.sackmann@cs.put.poznan.pl <andrea.sackmann@cs.put.poznan.pl>|Technical University of Applied Sciences Berlin, Bioinformatics group, Seestr, 64, 13347 Berlin, Germany. andrea.sackmann@cs.put.poznan.pl <andrea.sackmann@cs.put.poznan.pl>|Technical University of Applied Sciences Berlin, Bioinformatics group, Seestr, 64, 13347 Berlin, Germany. andrea.sackmann@cs.put.poznan.pl <andrea.sackmann@cs.put.poznan.pl>', 'Germany|Germany|Germany', 141, 'Algorithms|Computational Biology|Computer Simulation|Kinetics|Models, Biological|Pheromones|Saccharomyces cerevisiae|Signal Transduction', 'Journal Article', '10.1186/1471-2105-7-482', '17081284', 'Signal transduction pathways are usually modelled using classical quantitative methods, which are based on ordinary differential equations (ODEs). However, some difficulties are inherent in this approach. On the one hand, the kinetic parameters involved are often unknown and have to be estimated. With increasing size and complexity of signal transduction pathways, the estimation of missing kinetic data is not possible. On the other hand, ODEs based models do not support any explicit insights into possible (signal-) flows within the network. Moreover, a huge amount of qualitative data is available due to high-throughput techniques. In order to get information on the systems behaviour, qualitative analysis techniques have been developed. Applications of the known qualitative analysis methods concern mainly metabolic networks. Petri net theory provides a variety of established analysis techniques, which are also applicable to signal transduction models. In this context special properties have to be considered and new dedicated techniques have to be designed.'),
(91153, 2006, 'bmc', 'Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems', 'Rodriguez-Fernandez, Maria|Egea, Jose A|Banga, Julio R', 'Process Engineering Group, Instituto de Investigaciones Marinas (C.S.I.C.), Spanish Council for Scientific Research, Vigo, Spain. mrodriguez@iim.csic.es <mrodriguez@iim.csic.es>|Process Engineering Group, Instituto de Investigaciones Marinas (C.S.I.C.), Spanish Council for Scientific Research, Vigo, Spain. mrodriguez@iim.csic.es <mrodriguez@iim.csic.es>|Process Engineering Group, Instituto de Investigaciones Marinas (C.S.I.C.), Spanish Council for Scientific Research, Vigo, Spain. mrodriguez@iim.csic.es <mrodriguez@iim.csic.es>', 'Spain|Spain|Spain', 188, 'Algorithms|Computational Biology|Computers|HIV Protease Inhibitors|Models, Chemical|Models, Statistical|Models, Theoretical|Monoterpenes|Nonlinear Dynamics|Numerical Analysis, Computer-Assisted|Software|Stochastic Processes|Systems Biology', 'Journal Article', '10.1186/1471-2105-7-483', '17081289', 'We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness.'),
(91154, 2006, 'bmc', 'A statistical score for assessing the quality of multiple sequence alignments', 'Ahola, Virpi|Aittokallio, Tero|Vihinen, Mauno|Uusipaikka, Esa', 'Biotechnology and Food Research, MTT Agrifood Research Finland, Jokioinen, Finland. virpi.ahola@mtt.fi|Biotechnology and Food Research, MTT Agrifood Research Finland, Jokioinen, Finland. virpi.ahola@mtt.fi|Biotechnology and Food Research, MTT Agrifood Research Finland, Jokioinen, Finland. virpi.ahola@mtt.fi|Biotechnology and Food Research, MTT Agrifood Research Finland, Jokioinen, Finland. virpi.ahola@mtt.fi', 'Finland|Finland|Finland|Finland', 32, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Computational Biology|Computer Simulation|Data Interpretation, Statistical|Models, Statistical|Phylogeny|Protein Structure, Tertiary|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-7-484', '17081313', 'Multiple sequence alignment is the foundation of many important applications in bioinformatics that aim at detecting functionally important regions, predicting protein structures, building phylogenetic trees etc. Although the automatic construction of a multiple sequence alignment for a set of remotely related sequences cause a very challenging and error-prone task, many downstream analyses still rely heavily on the accuracy of the alignments.'),
(91155, 2006, 'bmc', 'Machine learning techniques in disease forecasting: a case study on rice blast prediction', 'Kaundal, Rakesh|Kapoor, Amar S|Raghava, Gajendra P S', 'Bioinformatics Centre, Institute of Microbial Technology, Sector 39-A, Chandigarh 160036, India. rakesh@imtech.res.in <rakesh@imtech.res.in>|Bioinformatics Centre, Institute of Microbial Technology, Sector 39-A, Chandigarh 160036, India. rakesh@imtech.res.in <rakesh@imtech.res.in>|Bioinformatics Centre, Institute of Microbial Technology, Sector 39-A, Chandigarh 160036, India. rakesh@imtech.res.in <rakesh@imtech.res.in>', 'India|India|India', 69, 'Agriculture|Artificial Intelligence|Ascomycota|Forecasting|Pattern Recognition, Automated|Plant Diseases|Weather', 'Evaluation Studies', '10.1186/1471-2105-7-485', '17083731', 'Diverse modeling approaches viz. neural networks and multiple regression have been followed to date for disease prediction in plant populations. However, due to their inability to predict value of unknown data points and longer training times, there is need for exploiting new prediction softwares for better understanding of plant-pathogen-environment relationships. Further, there is no online tool available which can help the plant researchers or farmers in timely application of control measures. This paper introduces a new prediction approach based on support vector machines for developing weather-based prediction models of plant diseases.'),
(91156, 2006, 'bmc', 'GibbsST: a Gibbs sampling method for motif discovery with enhanced resistance to local optima', 'Shida, Kazuhito', 'TUBERO (Tohoku University Biomedical Engineering Research Organization) 980-8575, Sendai, Japan. shida@cir.tohoku.ac.jp', 'Japan', 19, 'Algorithms|Amino Acid Motifs|Binding Sites|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Software|Transcription Factors', 'Journal Article', '10.1186/1471-2105-7-486', '17083740', 'Computational discovery of transcription factor binding sites (TFBS) is a challenging but important problem of bioinformatics. In this study, improvement of a Gibbs sampling based technique for TFBS discovery is attempted through an approach that is widely known, but which has never been investigated before: reduction of the effect of local optima.'),
(91157, 2006, 'bmc', 'Accurate and unambiguous tag-to-gene mapping in serial analysis of gene expression', 'Malig, Rodrigo|Varela, Cristian|Agosin, Eduardo|Melo, Francisco', 'Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Alameda 340, Santiago, Chile. romalig2002@yahoo.com <romalig2002@yahoo.com>|Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Alameda 340, Santiago, Chile. romalig2002@yahoo.com <romalig2002@yahoo.com>|Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Alameda 340, Santiago, Chile. romalig2002@yahoo.com <romalig2002@yahoo.com>|Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Alameda 340, Santiago, Chile. romalig2002@yahoo.com <romalig2002@yahoo.com>', 'Chile|Chile|Chile|Chile', 8, 'Chromosome Mapping|Computational Biology|DNA, Complementary|Databases, Genetic|Expressed Sequence Tags|Gene Expression Regulation, Fungal|RNA, Fungal|RNA, Messenger|RNA, Untranslated|Reproducibility of Results|Restriction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Analysis, DNA|Sequence Analysis, RNA|Sequence Tagged Sites|Software|Transcription, Genetic', 'Comparative Study', '10.1186/1471-2105-7-487', '17083742', 'In this study, we present a robust and reliable computational method for tag-to-gene assignment in serial analysis of gene expression (SAGE). The method relies on current genome information and annotation, incorporation of several new features, and key improvements over alternative methods, all of which are important to determine gene expression levels more accurately. The method provides a complete annotation of potential virtual SAGE tags within a genome, along with an estimation of their confidence for experimental observation that ranks tags that present multiple matches in the genome.'),
(91158, 2006, 'bmc', 'Evaluation of clustering algorithms for protein-protein interaction networks', 'Brohée, Sylvain|van Helden, Jacques', 'Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Bruxelles, CP 263, Campus Plaine, Bd, du Triomphe, B-1050 Bruxelles, Belgium. sylvain@scmbb.ulb.ac.be|Service de Conformation des Macromolécules Biologiques et de Bioinformatique, Université Libre de Bruxelles, CP 263, Campus Plaine, Bd, du Triomphe, B-1050 Bruxelles, Belgium. sylvain@scmbb.ulb.ac.be', 'Belgium|Belgium', 587, 'Algorithms|Cluster Analysis|Computational Biology|Computer Graphics|Databases, Protein|Markov Chains|Mass Spectrometry|Protein Binding|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins|Software Validation|Two-Hybrid System Techniques', 'Comparative Study', '10.1186/1471-2105-7-488', '17087821', 'Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism). In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies). High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL), Restricted Neighborhood Search Clustering (RNSC), Super Paramagnetic Clustering (SPC), and Molecular Complex Detection (MCODE).'),
(91159, 2006, 'bmc', 'A simple spreadsheet-based, MIAME-supportive format for microarray data: MAGE-TAB', 'Rayner, Tim F|Rocca-Serra, Philippe|Spellman, Paul T|Causton, Helen C|Farne, Anna|Holloway, Ele|Irizarry, Rafael A|Liu, Junmin|Maier, Donald S|Miller, Michael|Petersen, Kjell|Quackenbush, John|Sherlock, Gavin|Stoeckert, Christian J|White, Joseph|Whetzel, Patricia L|Wymore, Farrell|Parkinson, Helen|Sarkans, Ugis|Ball, Catherine A|Brazma, Alvis', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. rayner@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|', 148, 'Computational Biology|Databases, Genetic|Humans|Oligonucleotide Array Sequence Analysis|Software', 'Editorial', '10.1186/1471-2105-7-489', '17087822', 'Sharing of microarray data within the research community has been greatly facilitated by the development of the disclosure and communication standards MIAME and MAGE-ML by the MGED Society. However, the complexity of the MAGE-ML format has made its use impractical for laboratories lacking dedicated bioinformatics support.'),
(91160, 2006, 'bmc', 'XML schemas for common bioinformatic data types and their application in workflow systems', 'Seibel, Philipp N|Krüger, Jan|Hartmeier, Sven|Schwarzer, Knut|Löwenthal, Kai|Mersch, Henning|Dandekar, Thomas|Giegerich, Robert', 'Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 26, 'Algorithms|Computational Biology|Computer Graphics|Database Management Systems|Information Storage and Retrieval|Programming Languages|Sequence Alignment|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-490', '17087823', 'Today, there is a growing need in bioinformatics to combine available software tools into chains, thus building complex applications from existing single-task tools. To create such workflows, the tools involved have to be able to work with each others data--therefore, a common set of well-defined data formats is needed. Unfortunately, current bioinformatic tools use a great variety of heterogeneous formats.'),
(91161, 2006, 'bmc', 'Assessing protein similarity with Gene Ontology and its use in subnuclear localization prediction', 'Lei, Zhengdeng|Dai, Yang', 'Department of Bioengineering (MC063), University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, USA. zlei2@uic.edu <zlei2@uic.edu>|Department of Bioengineering (MC063), University of Illinois at Chicago, 851 South Morgan Street, Chicago, IL 60607, USA. zlei2@uic.edu <zlei2@uic.edu>', 'United States|United States', 0, 'Algorithms|Cell Nucleus|Computational Biology|Computer Simulation|Databases, Protein|Models, Statistical|Pattern Recognition, Automated|Proteins|Proteomics|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-7-491', '17090318', 'The accomplishment of the various genome sequencing projects resulted in accumulation of massive amount of gene sequence information. This calls for a large-scale computational method for predicting protein localization from sequence. The protein localization can provide valuable information about its molecular function, as well as the biological pathway in which it participates. The prediction of localization of a protein at subnuclear level is a challenging task. In our previous work we proposed an SVM-based system using protein sequence information for this prediction task. In this work, we assess protein similarity with Gene Ontology (GO) and then improve the performance of the system by adding a module of nearest neighbor classifier using a similarity measure derived from the GO annotation terms for protein sequences.'),
(91162, 2006, 'bmc', 'Automated recognition of malignancy mentions in biomedical literature', 'Jin, Yang|McDonald, Ryan T|Lerman, Kevin|Mandel, Mark A|Carroll, Steven|Liberman, Mark Y|Pereira, Fernando C|Winters, Raymond S|White, Peter S', 'Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA. yajin@mail.med.upenn.edu <yajin@mail.med.upenn.edu>|Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA. yajin@mail.med.upenn.edu <yajin@mail.med.upenn.edu>|Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA. yajin@mail.med.upenn.edu <yajin@mail.med.upenn.edu>|Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA. yajin@mail.med.upenn.edu <yajin@mail.med.upenn.edu>|Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA. yajin@mail.med.upenn.edu <yajin@mail.med.upenn.edu>|Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA. yajin@mail.med.upenn.edu <yajin@mail.med.upenn.edu>|Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA. yajin@mail.med.upenn.edu <yajin@mail.med.upenn.edu>|Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA. yajin@mail.med.upenn.edu <yajin@mail.med.upenn.edu>|Department of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104, USA. yajin@mail.med.upenn.edu <yajin@mail.med.upenn.edu>', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 29, 'Algorithms|Automation|Computational Biology|Database Management Systems|Databases, Bibliographic|Humans|Neoplasms|Pattern Recognition, Automated|Phenotype|PubMed|Software|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-7-492', '17090325', 'The rapid proliferation of biomedical text makes it increasingly difficult for researchers to identify, synthesize, and utilize developed knowledge in their fields of interest. Automated information extraction procedures can assist in the acquisition and management of this knowledge. Previous efforts in biomedical text mining have focused primarily upon named entity recognition of well-defined molecular objects such as genes, but less work has been performed to identify disease-related objects and concepts. Furthermore, promise has been tempered by an inability to efficiently scale approaches in ways that minimize manual efforts and still perform with high accuracy. Here, we have applied a machine-learning approach previously successful for identifying molecular entities to a disease concept to determine if the underlying probabilistic model effectively generalizes to unrelated concepts with minimal manual intervention for model retraining.'),
(91163, 2006, 'bmc', 'A method for rapid similarity analysis of RNA secondary structures', 'Liu, Na|Wang, Tianming', 'Department of Applied Mathematics, Dalian University of Technology, Dalian 116024, China. liunasophia@163.com|Department of Applied Mathematics, Dalian University of Technology, Dalian 116024, China. liunasophia@163.com', 'China|China', 21, 'Algorithms|Base Pairing|Base Sequence|Cluster Analysis|Computational Biology|Computer Simulation|Databases, Nucleic Acid|Decision Trees|Evolution, Molecular|Molecular Sequence Data|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software Validation|Time Factors', 'Comparative Study', '10.1186/1471-2105-7-493', '17090331', 'Owing to the rapid expansion of RNA structure databases in recent years, efficient methods for structure comparison are in demand for function prediction and evolutionary analysis. Usually, the similarity of RNA secondary structures is evaluated based on tree models and dynamic programming algorithms. We present here a new method for the similarity analysis of RNA secondary structures.'),
(91164, 2006, 'bmc', 'Time scale and dimension analysis of a budding yeast cell cycle model', 'Lovrics, Anna|Csikász-Nagy, Attila|Zsély, István Gy|Zádor, Judit|Turányi, Tamás|Novák, Béla', 'Laboratory for Chemical Kinetics, Institute of Chemistry, Eötvös University (ELTE), Pázmány P, sétány 1/A, H-1117 Budapest, Hungary. lovricsa@yahoo.com <lovricsa@yahoo.com>|Laboratory for Chemical Kinetics, Institute of Chemistry, Eötvös University (ELTE), Pázmány P, sétány 1/A, H-1117 Budapest, Hungary. lovricsa@yahoo.com <lovricsa@yahoo.com>|Laboratory for Chemical Kinetics, Institute of Chemistry, Eötvös University (ELTE), Pázmány P, sétány 1/A, H-1117 Budapest, Hungary. lovricsa@yahoo.com <lovricsa@yahoo.com>|Laboratory for Chemical Kinetics, Institute of Chemistry, Eötvös University (ELTE), Pázmány P, sétány 1/A, H-1117 Budapest, Hungary. lovricsa@yahoo.com <lovricsa@yahoo.com>|Laboratory for Chemical Kinetics, Institute of Chemistry, Eötvös University (ELTE), Pázmány P, sétány 1/A, H-1117 Budapest, Hungary. lovricsa@yahoo.com <lovricsa@yahoo.com>|Laboratory for Chemical Kinetics, Institute of Chemistry, Eötvös University (ELTE), Pázmány P, sétány 1/A, H-1117 Budapest, Hungary. lovricsa@yahoo.com <lovricsa@yahoo.com>', 'Hungary|Hungary|Hungary|Hungary|Hungary|Hungary', 0, 'Cell Cycle|Cell Physiological Phenomena|Computational Biology|Computer Simulation|Cytoplasm|Kinetics|Models, Biological|Models, Theoretical|Saccharomyces cerevisiae Proteins|Saccharomycetales|Time', 'Journal Article', '10.1186/1471-2105-7-494', '17094799', 'The progress through the eukaryotic cell division cycle is driven by an underlying molecular regulatory network. Cell cycle progression can be considered as a series of irreversible transitions from one steady state to another in the correct order. Although this view has been put forward some time ago, it has not been quantitatively proven yet. Bifurcation analysis of a model for the budding yeast cell cycle has identified only two different steady states (one for G1 and one for mitosis) using cell mass as a bifurcation parameter. By analyzing the same model, using different methods of dynamical systems theory, we provide evidence for transitions among several different steady states during the budding yeast cell cycle.'),
(91165, 2006, 'bmc', 'DWARF--a data warehouse system for analyzing protein families', 'Fischer, Markus|Thai, Quan K|Grieb, Melanie|Pleiss, Jürgen', 'Institute of Technical Biochemistry, University of Stuttgart, Allmandring 31, D-70569, Germany. mf2355@columbia.edu <mf2355@columbia.edu>|Institute of Technical Biochemistry, University of Stuttgart, Allmandring 31, D-70569, Germany. mf2355@columbia.edu <mf2355@columbia.edu>|Institute of Technical Biochemistry, University of Stuttgart, Allmandring 31, D-70569, Germany. mf2355@columbia.edu <mf2355@columbia.edu>|Institute of Technical Biochemistry, University of Stuttgart, Allmandring 31, D-70569, Germany. mf2355@columbia.edu <mf2355@columbia.edu>', 'Germany|Germany|Germany|Germany', 0, 'Amino Acid Sequence|Computer Graphics|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-495', '17094801', 'The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allows to gain a novel understanding of complex biological systems. The data warehouse DWARF applies integrative bioinformatics approaches to the analysis of large protein families.'),
(91166, 2006, 'bmc', 'methBLAST and methPrimerDB: web-tools for PCR based methylation analysis', 'Pattyn, Filip|Hoebeeck, Jasmien|Robbrecht, Piet|Michels, Evi|De Paepe, Anne|Bottu, Guy|Coornaert, David|Herzog, Robert|Speleman, Frank|Vandesompele, Jo', 'Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>|Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>|Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>|Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>|Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>|Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>|Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>|Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>|Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>|Center for Medical Genetics, Ghent University Hospital, De Pintelaan 185, 9000 Ghent, Belgium. Filip.Pattyn@UGent.be <Filip.Pattyn@UGent.be>', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 30, 'Algorithms|Animals|Computational Biology|DNA Methylation|DNA Primers|Databases, Genetic|Databases, Protein|Epigenesis, Genetic|Humans|Internet|Mice|Polymerase Chain Reaction|Rats|Software|Sulfites', 'Journal Article', '10.1186/1471-2105-7-496', '17094804', 'DNA methylation plays an important role in development and tumorigenesis by epigenetic modification and silencing of critical genes. The development of PCR-based methylation assays on bisulphite modified DNA heralded a breakthrough in speed and sensitivity for gene methylation analysis. Despite this technological advancement, these approaches require a cumbersome gene by gene primer design and experimental validation. Bisulphite DNA modification results in sequence alterations (all unmethylated cytosines are converted into uracils) and a general sequence complexity reduction as cytosines become underrepresented. Consequently, standard BLAST sequence homology searches cannot be applied to search for specific methylation primers.'),
(91167, 2006, 'bmc', 'cPath: open source software for collecting, storing, and querying biological pathways', 'Cerami, Ethan G|Bader, Gary D|Gross, Benjamin E|Sander, Chris', 'Computational Biology Center, Memorial Sloan-Kettering Cancer Center 1275 York Avenue, Box 460, New York, NY 10021, USA. cpath-bmc@cbio.mskcc.org|Computational Biology Center, Memorial Sloan-Kettering Cancer Center 1275 York Avenue, Box 460, New York, NY 10021, USA. cpath-bmc@cbio.mskcc.org|Computational Biology Center, Memorial Sloan-Kettering Cancer Center 1275 York Avenue, Box 460, New York, NY 10021, USA. cpath-bmc@cbio.mskcc.org|Computational Biology Center, Memorial Sloan-Kettering Cancer Center 1275 York Avenue, Box 460, New York, NY 10021, USA. cpath-bmc@cbio.mskcc.org', 'United States|United States|United States|United States', 0, 'Computational Biology|Computer Graphics|Databases, Factual|Humans|Information Storage and Retrieval|Internet|Programming Languages|Signal Transduction|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-497', '17101041', 'Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91168, 2006, 'bmc', '4SALE--a tool for synchronous RNA sequence and secondary structure alignment and editing', 'Seibel, Philipp N|Müller, Tobias|Dandekar, Thomas|Schultz, Jörg|Wolf, Matthias', 'Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>|Department of Bioinformatics, Biocenter, University of Würzburg, Am Hubland, Würzburg, Germany. philipp.seibel@biozentrum.uni-wuerzburg.de <philipp.seibel@biozentrum.uni-wuerzburg.de>', 'Germany|Germany|Germany|Germany|Germany', 264, 'Algorithms|Base Pairing|Computational Biology|Databases, Genetic|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Software Validation|Time Factors|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-498', '17101042', 'In sequence analysis the multiple alignment builds the fundament of all proceeding analyses. Errors in an alignment could strongly influence all succeeding analyses and therefore could lead to wrong predictions. Hand-crafted and hand-improved alignments are necessary and meanwhile good common practice. For RNA sequences often the primary sequence as well as a secondary structure consensus is well known, e.g., the cloverleaf structure of the t-RNA. Recently, some alignment editors are proposed that are able to include and model both kinds of information. However, with the advent of a large amount of reliable RNA sequences together with their solved secondary structures (available from e.g. the ITS2 Database), we are faced with the problem to handle sequences and their associated secondary structures synchronously.'),
(91169, 2006, 'bmc', 'State of the art: refinement of multiple sequence alignments', 'Chakrabarti, Saikat|Lanczycki, Christopher J|Panchenko, Anna R|Przytycka, Teresa M|Thiessen, Paul A|Bryant, Stephen H', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. chakraba@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. chakraba@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. chakraba@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. chakraba@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. chakraba@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA. chakraba@ncbi.nlm.nih.gov', 'United States|United States|United States|United States|United States|United States', 9, 'Algorithms|Computational Biology|Databases, Protein|Markov Chains|Programming Languages|Protein Structure, Tertiary|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-7-499', '17105653', 'Accurate multiple sequence alignments of proteins are very important in computational biology today. Despite the numerous efforts made in this field, all alignment strategies have certain shortcomings resulting in alignments that are not always correct. Refinement of existing alignment can prove to be an intelligent choice considering the increasing importance of high quality alignments in large scale high-throughput analysis.'),
(91170, 2006, 'bmc', 'PathogenMIPer: a tool for the design of molecular inversion probes to detect multiple pathogens', 'Thiyagarajan, Sreedevi|Karhanek, Miloslav|Akhras, Michael|Davis, Ronald W|Pourmand, Nader', 'Stanford University, Palo Alto, CA, USA. sreedevi@stanford.edu <sreedevi@stanford.edu>|Stanford University, Palo Alto, CA, USA. sreedevi@stanford.edu <sreedevi@stanford.edu>|Stanford University, Palo Alto, CA, USA. sreedevi@stanford.edu <sreedevi@stanford.edu>|Stanford University, Palo Alto, CA, USA. sreedevi@stanford.edu <sreedevi@stanford.edu>|Stanford University, Palo Alto, CA, USA. sreedevi@stanford.edu <sreedevi@stanford.edu>', 'United States|United States|United States|United States|United States', 10, 'Computational Biology|DNA|DNA Primers|Female|Genes, Bacterial|Genetic Variation|Genome, Bacterial|Genotype|Humans|Oligonucleotide Probes|Oligonucleotides|Papillomaviridae|Skin Neoplasms|Software|Uterine Cervical Neoplasms', 'Journal Article', '10.1186/1471-2105-7-500', '17105657', 'Here we describe PathogenMIPer, a software program for designing molecular inversion probe (MIP) oligonucleotides for use in pathogen identification and detection. The software designs unique and specific oligonucleotide probes targeting microbial or other genomes. The tool tailors all probe sequence components (including target-specific sequences, barcode sequences, universal primers and restriction sites) and combines these components into ready-to-order probes for use in a MIP assay. The system can harness the genetic variability available in an entire genome in designing specific probes for the detection of multiple co-infections in a single tube using a MIP assay.'),
(91171, 2006, 'bmc', 'Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores', 'Salomon, Jesper|Flower, Darren R', 'The Jenner Institute, University of Oxford, Compton, Newbury, Berkshire, RG20 7NN, UK. bio@salomons.dk|The Jenner Institute, University of Oxford, Compton, Newbury, Berkshire, RG20 7NN, UK. bio@salomons.dk', 'United Kingdom|United Kingdom', 55, 'Binding Sites|Computational Biology|Databases, Genetic|Epitope Mapping|HLA-A Antigens|HLA-DR Antigens|HLA-DRB1 Chains|Histocompatibility Antigens Class II|Humans|Peptides|Protein Binding|Protein Conformation|ROC Curve|Reproducibility of Results|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1186/1471-2105-7-501', '17105666', 'Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epitopes. For Class II MHC alleles, the binding groove is open at both ends, causing ambiguity in the positional alignment between the groove and peptide, as well as creating uncertainty as to what parts of the peptide interact with the MHC. Moreover, the antigenic peptides have variable lengths, making naive modelling methods difficult to apply. This paper introduces a kernel method that can handle variable length peptides effectively by quantifying similarities between peptide sequences and integrating these into the kernel.'),
(91172, 2006, 'bmc', 'A correlated motif approach for finding short linear motifs from protein interaction networks', 'Tan, Soon-Heng|Hugo, Willy|Sung, Wing-Kin|Ng, See-Kiong', 'Knowledge Discovery Department, Institute for Infocomm Research, Singapore. chris.tan.sh@gmail.com|Knowledge Discovery Department, Institute for Infocomm Research, Singapore. chris.tan.sh@gmail.com|Knowledge Discovery Department, Institute for Infocomm Research, Singapore. chris.tan.sh@gmail.com|Knowledge Discovery Department, Institute for Infocomm Research, Singapore. chris.tan.sh@gmail.com', 'Singapore|Singapore|Singapore|Singapore', 36, 'Algorithms|Amino Acid Motifs|Computational Biology|Databases, Protein|Models, Biological|Models, Molecular|Models, Statistical|Programming Languages|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Sensitivity and Specificity|Sequence Analysis, Protein|Signal Transduction|Software', 'Journal Article', '10.1186/1471-2105-7-502', '17107624', 'An important class of interaction switches for biological circuits and disease pathways are short binding motifs. However, the biological experiments to find these binding motifs are often laborious and expensive. With the availability of protein interaction data, novel binding motifs can be discovered computationally: by applying standard motif extracting algorithms on protein sequence sets each interacting with either a common protein or a protein group with similar properties. The underlying assumption is that proteins with common interacting partners will share some common binding motifs. Although novel binding motifs have been discovered with such approach, it is not applicable if a protein interacts with very few other proteins or when prior knowledge of protein group is not available or erroneous. Experimental noise in input interaction data can further deteriorate the dismal performance of such approaches.'),
(91173, 2006, 'bmc', 'Predicting residue contacts using pragmatic correlated mutations method: reducing the false positives', 'Kundrotas, Petras J|Alexov, Emil G', 'Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA. pkundro@clemson.edu <pkundro@clemson.edu>|Computational Biophysics and Bioinformatics, Department of Physics, Clemson University, Clemson, SC 29634, USA. pkundro@clemson.edu <pkundro@clemson.edu>', 'United States|United States', 41, 'Algorithms|Biophysics|Computational Biology|Databases, Protein|False Positive Reactions|Genetic Variation|Imaging, Three-Dimensional|Internet|Models, Statistical|Mutation|Proteins|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-7-503', '17109752', 'Predicting residues contacts using primary amino acid sequence alone is an important task that can guide 3D structure modeling and can verify the quality of the predicted 3D structures. The correlated mutations (CM) method serves as the most promising approach and it has been used to predict amino acids pairs that are distant in the primary sequence but form contacts in the native 3D structure of homologous proteins.'),
(91174, 2006, 'bmc', 'A comparative analysis of the information content in long and short SAGE libraries', 'Li, Yi-Ju|Xu, Puting|Qin, Xuejun|Schmechel, Donald E|Hulette, Christine M|Haines, Jonathan L|Pericak-Vance, Margaret A|Gilbert, John R', 'Department of Medicine and Center for Human Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA. yiju.li@duke.edu|Department of Medicine and Center for Human Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA. yiju.li@duke.edu|Department of Medicine and Center for Human Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA. yiju.li@duke.edu|Department of Medicine and Center for Human Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA. yiju.li@duke.edu|Department of Medicine and Center for Human Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA. yiju.li@duke.edu|Department of Medicine and Center for Human Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA. yiju.li@duke.edu|Department of Medicine and Center for Human Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA. yiju.li@duke.edu|Department of Medicine and Center for Human Genetics, Duke University Medical Center, Durham, North Carolina 27710, USA. yiju.li@duke.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 10, 'Algorithms|Brain|Computational Biology|DNA, Complementary|Databases, Genetic|False Positive Reactions|Gene Expression|Gene Expression Profiling|Gene Library|Hippocampus|Humans|Models, Statistical|Multigene Family|RNA', 'Comparative Study', '10.1186/1471-2105-7-504', '17109755', 'Serial Analysis of Gene Expression (SAGE) is a powerful tool to determine gene expression profiles. Two types of SAGE libraries, ShortSAGE and LongSAGE, are classified based on the length of the SAGE tag (10 vs. 17 basepairs). LongSAGE libraries are thought to be more useful than ShortSAGE libraries, but their information content has not been widely compared. To dissect the differences between these two types of libraries, we utilized four libraries (two LongSAGE and two ShortSAGE libraries) generated from the hippocampus of Alzheimer and control samples. In addition, we generated two additional short SAGE libraries, the truncated long SAGE libraries (tSAGE), from LongSAGE libraries by deleting seven 5 basepairs from each LongSAGE tag.'),
(91175, 2006, 'bmc', 'Using local gene expression similarities to discover regulatory binding site modules', 'Wilczyxc5x84ski, Bartek|Hvidsten, Torgeir R|Kryshtafovych, Andriy|Tiuryn, Jerzy|Komorowski, Jan|Fidelis, Krzysztof', 'lnstitute of Mathematics, Polish Academy of Sciences, Warsaw, Poland. bartek@impan.gov.pl <bartek@impan.gov.pl>|lnstitute of Mathematics, Polish Academy of Sciences, Warsaw, Poland. bartek@impan.gov.pl <bartek@impan.gov.pl>|lnstitute of Mathematics, Polish Academy of Sciences, Warsaw, Poland. bartek@impan.gov.pl <bartek@impan.gov.pl>|lnstitute of Mathematics, Polish Academy of Sciences, Warsaw, Poland. bartek@impan.gov.pl <bartek@impan.gov.pl>|lnstitute of Mathematics, Polish Academy of Sciences, Warsaw, Poland. bartek@impan.gov.pl <bartek@impan.gov.pl>|lnstitute of Mathematics, Polish Academy of Sciences, Warsaw, Poland. bartek@impan.gov.pl <bartek@impan.gov.pl>', 'Poland|Poland|Poland|Poland|Poland|Poland', 10, 'Binding Sites|Cell Cycle|Chromatin Immunoprecipitation|Cluster Analysis|Computational Biology|Fungal Proteins|Gene Expression|Gene Expression Profiling|Gene Expression Regulation, Fungal|Multigene Family|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1186/1471-2105-7-505', '17109764', 'We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to relate the combinations of transcription factor binding sites (also referred to as binding site modules) identified in gene promoters to the expression of these genes. The novel aspects include local expression similarity clustering and an exact IF-THEN rule inference algorithm. We also provide a method of rule generalization to include genes with unknown expression profiles.'),
(91176, 2006, 'bmc', 'Visual setup of logical models of signaling and regulatory networks with ProMoT', 'Saez-Rodriguez, Julio|Mirschel, Sebastian|Hemenway, Rebecca|Klamt, Steffen|Gilles, Ernst Dieter|Ginkel, Martin', 'Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr, 1, 39106 Magdeburg, Germany. saezr@mpi-magdeburg.mpg.de <saezr@mpi-magdeburg.mpg.de>|Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr, 1, 39106 Magdeburg, Germany. saezr@mpi-magdeburg.mpg.de <saezr@mpi-magdeburg.mpg.de>|Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr, 1, 39106 Magdeburg, Germany. saezr@mpi-magdeburg.mpg.de <saezr@mpi-magdeburg.mpg.de>|Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr, 1, 39106 Magdeburg, Germany. saezr@mpi-magdeburg.mpg.de <saezr@mpi-magdeburg.mpg.de>|Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr, 1, 39106 Magdeburg, Germany. saezr@mpi-magdeburg.mpg.de <saezr@mpi-magdeburg.mpg.de>|Max-Planck-Institute for Dynamics of Complex Technical Systems, Sandtorstr, 1, 39106 Magdeburg, Germany. saezr@mpi-magdeburg.mpg.de <saezr@mpi-magdeburg.mpg.de>', 'Germany|Germany|Germany|Germany|Germany|Germany', 14, 'Animals|Biochemistry|Computational Biology|Computer Graphics|Humans|Internet|Lymphocyte Activation|Models, Biological|Models, Theoretical|Programming Languages|Signal Transduction|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-506', '17109765', 'The analysis of biochemical networks using a logical (Boolean) description is an important approach in Systems Biology. Recently, new methods have been proposed to analyze large signaling and regulatory networks using this formalism. Even though there is a large number of tools to set up models describing biological networks using a biochemical (kinetic) formalism, however, they do not support logical models.'),
(91177, 2006, 'bmc', 'Novel methods for secondary structure determination using low wavelength (VUV) circular dichroism spectroscopic data', 'Lees, Jonathan G|Miles, Andrew J|Janes, Robert W|Wallace, B A', 'School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK. j.lees@mail.cryst.bbk.ac.uk <j.lees@mail.cryst.bbk.ac.uk>|School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK. j.lees@mail.cryst.bbk.ac.uk <j.lees@mail.cryst.bbk.ac.uk>|School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK. j.lees@mail.cryst.bbk.ac.uk <j.lees@mail.cryst.bbk.ac.uk>|School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK. j.lees@mail.cryst.bbk.ac.uk <j.lees@mail.cryst.bbk.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 23, 'Algorithms|Circular Dichroism|Computational Biology|Data Interpretation, Statistical|Databases, Protein|Models, Statistical|Neural Networks (Computer)|Protein Conformation|Protein Folding|Protein Structure, Secondary|Reproducibility of Results|Spectrophotometry', 'Journal Article', '10.1186/1471-2105-7-507', '17112372', 'Circular Dichroism (CD) spectroscopy is a widely used method for studying protein structures in solution. Modern synchrotron radiation CD (SRCD) instruments have considerably higher photon fluxes than do conventional lab-based CD instruments, and hence have the ability to routinely measure CD data to much lower wavelengths. Recently a new reference dataset of SRCD spectra of proteins of known structure, designed to cover secondary structure and fold space, has been produced which includes low wavelength (vacuum ultraviolet - VUV) data. However, the existing algorithms used to calculate protein secondary structures from CD data have not been designed to take optimal advantage of the additional information in these low wavelength data.'),
(91178, 2006, 'bmc', 'IntNetDB v10: an integrated protein-protein interaction network database generated by a probabilistic model', 'Xia, Kai|Dong, Dong|Han, Jing-Dong J', 'Chinese Academy of Sciences Key Laboratory of Developmental Biology, Center for Molecular Systems Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China. kxia@genetics.ac.cn|Chinese Academy of Sciences Key Laboratory of Developmental Biology, Center for Molecular Systems Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China. kxia@genetics.ac.cn|Chinese Academy of Sciences Key Laboratory of Developmental Biology, Center for Molecular Systems Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China. kxia@genetics.ac.cn', 'China|China|China', 61, 'Algorithms|Animals|Bayes Theorem|Cluster Analysis|Computer Graphics|Databases, Genetic|Gene Expression Regulation|Humans|Internet|Models, Statistical|Phenotype|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Reproducibility of Results|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-508', '17112386', 'Although protein-protein interaction (PPI) networks have been explored by various experimental methods, the maps so built are still limited in coverage and accuracy. To further expand the PPI network and to extract more accurate information from existing maps, studies have been carried out to integrate various types of functional relationship data. A frequently updated database of computationally analyzed potential PPIs to provide biological researchers with rapid and easy access to analyze original data as a biological network is still lacking.'),
(91179, 2006, 'bmc', 'CoXpress: differential co-expression in gene expression data', 'Watson, Michael', 'Informatics Group, Institute for Animal Health, Compton, Newbury, Berks RG20 7NN, UK. michael.watson@bbsrc.ac.uk', 'United Kingdom', 97, 'Algorithms|Cluster Analysis|Computational Biology|Gene Expression Profiling|Gene Expression Regulation|Humans|Leukemia, Myeloid, Acute|Models, Statistical|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-7-509', '17116249', 'Traditional methods of analysing gene expression data often include a statistical test to find differentially expressed genes, or use of a clustering algorithm to find groups of genes that behave similarly across a dataset. However, these methods may miss groups of genes which form differential co-expression patterns under different subsets of experimental conditions. Here we describe coXpress, an R package that allows researchers to identify groups of genes that are differentially co-expressed.'),
(91180, 2006, 'bmc', 'Proceedings of the Third Annual Conference of the MidSouth Computational Biology and Bioinformatics Society Introduction', 'Wren, Jonathan D|Gusev, Yuriy|Ptitsyn, Andrey|Winters-Hilt, Stephen', 'Advanced Center for Genome Technology, Stephenson Research and Technology Center, Department of Botany and Microbiology, 101 David L, Boren Blvd, The University of Oklahoma, Norman, Oklahoma 73019, USA. Jonathan.Wren@OU.edu|Advanced Center for Genome Technology, Stephenson Research and Technology Center, Department of Botany and Microbiology, 101 David L, Boren Blvd, The University of Oklahoma, Norman, Oklahoma 73019, USA. Jonathan.Wren@OU.edu|Advanced Center for Genome Technology, Stephenson Research and Technology Center, Department of Botany and Microbiology, 101 David L, Boren Blvd, The University of Oklahoma, Norman, Oklahoma 73019, USA. Jonathan.Wren@OU.edu|Advanced Center for Genome Technology, Stephenson Research and Technology Center, Department of Botany and Microbiology, 101 David L, Boren Blvd, The University of Oklahoma, Norman, Oklahoma 73019, USA. Jonathan.Wren@OU.edu', 'United States|United States|United States|United States', 0, 'Computational Biology|Databases, Genetic|Microarray Analysis|United States', 'Introductory Journal Article', '10.1186/1471-2105-7-S2-S1', '17118130', '-'),
(91181, 2006, 'bmc', 'Permutation test for periodicity in short time series data', 'Ptitsyn, Andrey A|Zvonic, Sanjin|Gimble, Jeffrey M', 'Experimental Obesity Laboratory, Louisiana State University Pennington Biomedical Research Center, 6400 Perkins Rd,, Baton Rouge, LA 70808, USA. Andrey.Ptitsyn@pbrc.edu|Experimental Obesity Laboratory, Louisiana State University Pennington Biomedical Research Center, 6400 Perkins Rd,, Baton Rouge, LA 70808, USA. Andrey.Ptitsyn@pbrc.edu|Experimental Obesity Laboratory, Louisiana State University Pennington Biomedical Research Center, 6400 Perkins Rd,, Baton Rouge, LA 70808, USA. Andrey.Ptitsyn@pbrc.edu', 'United States|United States|United States', 31, 'Algorithms|Animals|Circadian Rhythm|Computational Biology|DNA|DNA Mutational Analysis|Liver|Mice|Mice, Inbred AKR|Oligonucleotide Array Sequence Analysis|Time Factors', 'Journal Article', '10.1186/1471-2105-7-S2-S10', '17118131', 'Periodic processes, such as the circadian rhythm, are important factors modulating and coordinating transcription of genes governing key metabolic pathways. Theoretically, even small fluctuations in the orchestration of circadian gene expression patterns among different tissues may result in functional asynchrony, at the organism level, and may contribute to a wide range of pathologic disorders. Identification of circadian expression pattern in time series data is important, but equally challenging. Microarray technology allows estimation of relative expression of thousands of genes at each time point. However, this estimation often lacks precision and microarray experiments are prohibitively expensive, limiting the number of data points in a time series expression profile. The data produced in these experiments carries a high degree of stochastic variation, obscuring the periodic pattern and a limited number of replicates, typically covering not more than two complete periods of oscillation.'),
(91182, 2006, 'bmc', 'A method for computing the overall statistical significance of a treatment effect among a group of genes', 'Delongchamp, Robert|Lee, Taewon|Velasco, Cruz', 'Division of Biometry and Risk Assessment, National Center for Toxicological Research, Jefferson, Arkansas 72079 USA.|Division of Biometry and Risk Assessment, National Center for Toxicological Research, Jefferson, Arkansas 72079 USA.|Division of Biometry and Risk Assessment, National Center for Toxicological Research, Jefferson, Arkansas 72079 USA.', 'United States|United States|United States', 30, 'Biometry|Computational Biology|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-7-S2-S11', '17118132', 'In studies that use DNA arrays to assess changes in gene expression, our goal is to evaluate the statistical significance of treatments on sets of genes. Genes can be grouped by a molecular function, a biological process, or a cellular component, e.g., gene ontology (GO) terms. The meaning of an affected GO group is often clearer than interpretations arising from a list of the statistically significant genes.'),
(91183, 2006, 'bmc', 'Improving the performance of SVM-RFE to select genes in microarray data', 'Ding, Yuanyuan|Wilkins, Dawn', 'Computer & Information Science Department, The University of Mississippi, University, MS, USA. yding@olemiss.edu|Computer & Information Science Department, The University of Mississippi, University, MS, USA. yding@olemiss.edu', 'United States|United States', 54, 'Algorithms|Computational Biology|Computer Simulation|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-7-S2-S12', '17118133', 'Recursive Feature Elimination is a common and well-studied method for reducing the number of attributes used for further analysis or development of prediction models. The effectiveness of the RFE algorithm is generally considered excellent, but the primary obstacle in using it is the amount of computational power required.'),
(91184, 2006, 'bmc', 'Beyond microarrays: find key transcription factors controlling signal transduction pathways', 'Kel, Alexdander|Voss, Nico|Jauregui, Ruy|Kel-Margoulis, Olga|Wingender, Edgar', 'BIOBASE GmbH, Halchtersche Str, 33, D-38304 Wolfenbüttel, Germany. alexander.kel@biobase-international.com|BIOBASE GmbH, Halchtersche Str, 33, D-38304 Wolfenbüttel, Germany. alexander.kel@biobase-international.com|BIOBASE GmbH, Halchtersche Str, 33, D-38304 Wolfenbüttel, Germany. alexander.kel@biobase-international.com|BIOBASE GmbH, Halchtersche Str, 33, D-38304 Wolfenbüttel, Germany. alexander.kel@biobase-international.com|BIOBASE GmbH, Halchtersche Str, 33, D-38304 Wolfenbüttel, Germany. alexander.kel@biobase-international.com', 'Germany|Germany|Germany|Germany|Germany', 65, 'Binding Sites|Computational Biology|Databases, Nucleic Acid|Endothelial Cells|Gene Regulatory Networks|Humans|Internet|Microarray Analysis|Signal Transduction|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-7-S2-S13', '17118134', 'Massive gene expression changes in different cellular states measured by microarrays, in fact, reflect just an echo of real molecular processes in the cells. Transcription factors constitute a class of the regulatory molecules that typically require posttranscriptional modifications or ligand binding in order to exert their function. Therefore, such important functional changes of transcription factors are not directly visible in the microarray experiments.'),
(91185, 2006, 'bmc', 'Hidden Markov model variants and their application', 'Winters-Hilt, Stephen', 'Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu', 'United States', 22, 'Alternative Splicing|Animals|Caenorhabditis elegans|Chlamydia trachomatis|Computational Biology|Computer Simulation|Markov Chains|Vibrio cholerae', 'Journal Article', '10.1186/1471-2105-7-S2-S14', '17118135', 'Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way. This approach is based on mutual information, probabilistic measures, hidden Markov models, and other purely statistical inputs. This approach also provides a uniquely common ground for comparative prokaryotic genomics. The approach is an on-going effort by its nature, as a multi-pass learning process, where each round is more informed than the last, and thereby allows a shift to the more powerful methods available for supervised learning at each iteration. It is envisaged that this bootstrap learning process will also be useful as a knowledge discovery tool. For such an ab initio prokaryotic gene-finder to work, however, it needs a mechanism to identify critical motif structure, such as those around the start of coding or start of transcription (and then, hopefully more).For eukaryotes, even with better start-of-coding identification, parsing of eukaryotic coding regions by the HMM is still limited by the HMMs single gene assumption, as evidenced by the poor performance in alternatively spliced regions. To address these complications an approach is described to expand the states in a eukaryotic gene-predictor HMM, to operate with two layers of DNA parsing. This extension from the single layer gene prediction parse is indicated after preliminary analysis of the C. elegans alt-splice statistics. State profiles have made use of a novel hash-interpolating MM (hIMM) method. A new implementation for an HMM-with-Duration is also described, with far-reaching application to gene-structure identification and analysis of channel current blockade data.'),
(91186, 2006, 'bmc', 'DNA molecule classification using feature primitives', 'Iqbal, Raja Tanveer|Landry, Matthew|Winters-Hilt, Stephen', 'Department of Electrical Engineering and Computer Science, Tulane University, New Orleans, LA 70118, USA. iqbal@eecs.tulane.edu|Department of Electrical Engineering and Computer Science, Tulane University, New Orleans, LA 70118, USA. iqbal@eecs.tulane.edu|Department of Electrical Engineering and Computer Science, Tulane University, New Orleans, LA 70118, USA. iqbal@eecs.tulane.edu', 'United States|United States|United States', 8, 'Computational Biology|DNA|Molecular Conformation|Nucleic Acid Conformation', 'Journal Article', '10.1186/1471-2105-7-S2-S15', '17118136', 'We present a novel strategy for classification of DNA molecules using measurements from an alpha-Hemolysin channel detector. The proposed approach provides excellent classification performance for five different DNA hairpins that differ in only one base-pair. For multi-class DNA classification problems, practitioners usually adopt approaches that use decision trees consisting of binary classifiers. Finding the best tree topology requires exploring all possible tree topologies and is computationally prohibitive. We propose a computational framework based on feature primitives that eliminates the need of a decision tree of binary classifiers. In the first phase, we generate a pool of weak features from nanopore blockade current measurements by using HMM analysis, principal component analysis and various wavelet filters. In the next phase, feature selection is performed using AdaBoost. AdaBoost provides an ensemble of weak learners of various types learned from feature primitives.'),
(91187, 2006, 'bmc', 'Analysis of gene expression changes in relation to toxicity and tumorigenesis in the livers of Big Blue transgenic rats fed comfrey (Symphytum officinale)', 'Mei, Nan|Guo, Lei|Zhang, Lu|Shi, Leming|Sun, Yongming Andrew|Fung, Chris|Moland, Carrie L|Dial, Stacey L|Fuscoe, James C|Chen, Tao', 'Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, FDA, Jefferson, AR 72079, USA. nan.mei@fda.hhs.gov', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 25, 'Animal Feed|Animals|Body Weight|Cell Transformation, Neoplastic|Comfrey|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Liver Neoplasms|Male|Mutation|Rats|Rats, Inbred F344|Rats, Transgenic', 'Journal Article', '10.1186/1471-2105-7-S2-S16', '17118137', 'Comfrey is consumed by humans as a vegetable and a tea, and has been used as an herbal medicine for more than 2000 years. Comfrey, however, is hepatotoxic in livestock and humans and carcinogenic in experimental animals. Our previous study suggested that comfrey induces liver tumors by a genotoxic mechanism and that the pyrrolizidine alkaloids in the plant are responsible for mutation induction and tumor initiation in rat liver.'),
(91188, 2006, 'bmc', 'Improvement in the reproducibility and accuracy of DNA microarray quantification by optimizing hybridization conditions', 'Han, Tao|Melvin, Cathy D|Shi, Leming|Branham, William S|Moland, Carrie L|Pine, P Scott|Thompson, Karol L|Fuscoe, James C', 'Center for Functional Genomics, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. Tao.Han@fda.hhs.gov|Center for Functional Genomics, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. Tao.Han@fda.hhs.gov|Center for Functional Genomics, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. Tao.Han@fda.hhs.gov|Center for Functional Genomics, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. Tao.Han@fda.hhs.gov|Center for Functional Genomics, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. Tao.Han@fda.hhs.gov|Center for Functional Genomics, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. Tao.Han@fda.hhs.gov|Center for Functional Genomics, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. Tao.Han@fda.hhs.gov|Center for Functional Genomics, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. Tao.Han@fda.hhs.gov', 'United States|United States|United States|United States|United States|United States|United States|United States', 31, 'Animals|Computational Biology|Mice|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Organ Specificity|Rats|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-7-S2-S17', '17118138', 'DNA microarrays, which have been increasingly used to monitor mRNA transcripts at a global level, can provide detailed insight into cellular processes involved in response to drugs and toxins. This is leading to new understandings of signaling networks that operate in the cell, and the molecular basis of diseases. Custom printed oligonucleotide arrays have proven to be an effective way to facilitate the applications of DNA microarray technology. A successful microarray experiment, however, involves many steps: well-designed oligonucleotide probes, printing, RNA extraction and labeling, hybridization, and imaging. Optimization is essential to generate reliable microarray data.'),
(91189, 2006, 'bmc', 'Differential gene expression in mouse primary hepatocytes exposed to the peroxisome proliferator-activated receptor alpha agonists', 'Guo, Lei|Fang, Hong|Collins, Jim|Fan, Xiao-hui|Dial, Stacey|Wong, Alex|Mehta, Kshama|Blann, Ernice|Shi, Leming|Tong, Weida|Dragan, Yvonne P', 'Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov|Division of Systems Toxicology, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR 72079, USA. lei.guo@fda.hhs.gov', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 45, 'Animals|Bezafibrate|Cells, Cultured|Fenofibrate|Gene Expression Profiling|Gene Expression Regulation|Hepatocytes|Male|Mice|Mice, Inbred C57BL|Oxidative Stress|PPAR alpha|Pyrimidines', 'Journal Article', '10.1186/1471-2105-7-S2-S18', '17118139', 'Fibrates are a unique hypolipidemic drugs that lower plasma triglyceride and cholesterol levels through their action as peroxisome proliferator-activated receptor alpha (PPARalpha) agonists. The activation of PPARalpha leads to a cascade of events that result in the pharmacological (hypolipidemic) and adverse (carcinogenic) effects in rodent liver.'),
(91190, 2006, 'bmc', 'An automated method for rapid identification of putative gene family members in plants', 'Frank, Ronald L|Mane, Ajay|Ercal, Fikret', 'Biological Sciences Department, University of Missouri-Rolla, Rolla, Missouri, USA. rfrank@umr.edu|Biological Sciences Department, University of Missouri-Rolla, Rolla, Missouri, USA. rfrank@umr.edu|Biological Sciences Department, University of Missouri-Rolla, Rolla, Missouri, USA. rfrank@umr.edu', 'United States|United States|United States', 0, 'Arabidopsis|Automation, Laboratory|Computational Biology|Software Design|Soybeans|Time Factors', 'Journal Article', '10.1186/1471-2105-7-S2-S19', '17118140', 'Gene duplication events have played a significant role in genome evolution, particularly in plants. Exhaustive searches for all members of a known gene family as well as the identification of new gene families has become increasingly important. Subfunctionalization via changes in regulatory sequences following duplication (adaptive selection) appears to be a common mechanism of evolution in plants and can be accompanied by purifying selection on the coding region. Such negative selection can be detected by a bias toward synonymous over nonsynonymous substitutions. However, the process of identifying this bias requires many steps usually employing several different software programs. We have simplified the process and significantly shortened the time required by condensing many steps into a few scripts or programs to rapidly identify putative gene family members beginning with a single query sequence.'),
(91191, 2006, 'bmc', 'A Fourier transformation based method to mine peptide space for antimicrobial activity', 'Nagarajan, Vijayaraj|Kaushik, Navodit|Murali, Beddhu|Zhang, Chaoyang|Lakhera, Sanyogita|Elasri, Mohamed O|Deng, Youping', 'Department of Biological Sciences, The University of Southern Mississippi, Hattiesburg, MS, 39406, USA.|Department of Biological Sciences, The University of Southern Mississippi, Hattiesburg, MS, 39406, USA.|Department of Biological Sciences, The University of Southern Mississippi, Hattiesburg, MS, 39406, USA.|Department of Biological Sciences, The University of Southern Mississippi, Hattiesburg, MS, 39406, USA.|Department of Biological Sciences, The University of Southern Mississippi, Hattiesburg, MS, 39406, USA.|Department of Biological Sciences, The University of Southern Mississippi, Hattiesburg, MS, 39406, USA.|Department of Biological Sciences, The University of Southern Mississippi, Hattiesburg, MS, 39406, USA.', 'United States|United States|United States|United States|United States|United States|United States', 15, 'Amino Acid Sequence|Anti-Infective Agents|Computational Biology|Databases, Protein|Drug Discovery|Fourier Analysis|Molecular Sequence Data|Peptides', 'Journal Article', '10.1186/1471-2105-7-S2-S2', '17118141', 'Naturally occurring antimicrobial peptides are currently being explored as potential candidate peptide drugs. Since antimicrobial peptides are part of the innate immune system of every living organism, it is possible to discover new candidate peptides using the available genomic and proteomic data. High throughput computational techniques could also be used to virtually scan the entire peptide space for discovering out new candidate antimicrobial peptides.'),
(91192, 2006, 'bmc', 'Gene expression profiles distinguish the carcinogenic effects of aristolochic acid in target (kidney) and non-target (liver) tissues in rats', 'Chen, Tao|Guo, Lei|Zhang, Lu|Shi, Leming|Fang, Hong|Sun, Yongming|Fuscoe, James C|Mei, Nan', 'Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. tao.chen@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. tao.chen@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. tao.chen@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. tao.chen@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. tao.chen@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. tao.chen@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. tao.chen@fda.hhs.gov|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR 72079, USA. tao.chen@fda.hhs.gov', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Aristolochic Acids|Biometry|Carcinogens|Cluster Analysis|Computational Biology|Gene Expression Profiling|Gene Expression Regulation|Kidney|Liver|Organ Specificity|Rats|Rats, Inbred F344', 'Journal Article', '10.1186/1471-2105-7-S2-S20', '17118142', 'Aristolochic acid (AA) is the active component of herbal drugs derived from Aristolochia species that have been used for medicinal purposes since antiquity. AA, however, induced nephropathy and urothelial cancer in people and malignant tumors in the kidney and urinary tract of rodents. Although AA is bioactivated in both kidney and liver, it only induces tumors in kidney. To evaluate whether microarray analysis can be used for distinguishing the tissue-specific carcinogenicity of AA, we examined gene expression profiles in kidney and liver of rats treated with carcinogenic doses of AA.'),
(91193, 2006, 'bmc', 'Nanopore Detector based analysis of single-molecule conformational kinetics and binding interactions', 'Winters-Hilt, Stephen', 'Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu', 'United States', 0, 'Base Sequence|Computational Biology|DNA|Kinetics|Models, Molecular|Molecular Sequence Data|Nanostructures|Nucleic Acid Conformation|Porosity|Proteins', 'Journal Article', '10.1186/1471-2105-7-S2-S21', '17118143', 'A Nanopore Detector provides a means to transduce single molecule events into observable channel current changes. Nanopore-based detection can report directly, or indirectly, on single molecule kinetics. The nanopore-based detector can directly measure molecular characteristics in terms of the blockade properties of individual molecules--this is possible due to the kinetic information that is embedded in the blockade measurements, where the adsorption-desorption history of the molecule to the surrounding channel, and the configurational changes in the molecule itself, imprint on the ionic flow through the channel. This rich source of information offers prospects for DNA sequencing and single nucleotide polymorphism (SNP) analysis. A nanopore-based detector can also measure molecular characteristics indirectly, by using a reporter molecule that binds to certain molecules, with subsequent distinctive blockade by the bound-molecule complex.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91194, 2006, 'bmc', 'Cheminformatics methods for novel nanopore analysis of HIV DNA termini', 'Winters-Hilt, Stephen|Landry, Matthew|Akeson, Mark|Tanase, Maria|Amin, Iftekhar|Coombs, Amy|Morales, Eric|Millet, John|Baribault, Carl|Sendamangalam, Srikanth', 'Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. winters@cs.uno.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 18, 'Base Sequence|Chemistry Techniques, Analytical|Computational Biology|DNA, Viral|HIV|Models, Molecular|Nanostructures|Nucleic Acid Conformation|Porosity', 'Journal Article', '10.1186/1471-2105-7-S2-S22', '17118144', 'Channel current feature extraction methods, using Hidden Markov Models (HMMs) have been designed for tracking individual-molecule conformational changes. This information is derived from observation of changes in ionic channel current blockade signal upon that molecules interaction with (and occlusion of) a single nanometer-scale channel in a nanopore detector. In effect, a nanopore detector transduces single molecule events into channel current blockades. HMM analysis tools described are used to help systematically explore DNA dinucleotide flexibility, with particular focus on HIVs highly conserved (and highly flexible/reactive) viral DNA termini. One of the most critical stages in HIVs attack is the binding between viral DNA and the retroviral integrase, which is influenced by the dynamic-coupling induced high flexibility of a CA/TG dinucleotide positioned precisely two base-pairs from the blunt terminus of the duplex viral DNA. This suggests the study of a family of such CA/TG dinucleotide molecules via nanopore measurement and cheminformatics analysis.'),
(91195, 2006, 'bmc', 'GOFFA: gene ontology for functional analysis--a FDA gene ontology tool for analysis of genomic and proteomic data', 'Sun, Hongmei|Fang, Hong|Chen, Tao|Perkins, Roger|Tong, Weida', 'National Center for Toxicological Research, Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA.|National Center for Toxicological Research, Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA.|National Center for Toxicological Research, Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA.|National Center for Toxicological Research, Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA.|National Center for Toxicological Research, Food and Drug Administration, 3900 NCTR Road, Jefferson, Arkansas 72079, USA.', 'United States|United States|United States|United States|United States', 0, 'Genomics|Internet|Proteomics|Software Design|United States|United States Food and Drug Administration', 'Journal Article', '10.1186/1471-2105-7-S2-S23', '17118145', 'Gene Ontology (GO) characterizes and categorizes the functions of genes and their products according to biological processes, molecular functions and cellular components, facilitating interpretation of data from high-throughput genomics and proteomics technologies. The most effective use of GO information is achieved when its rich and hierarchical complexity is retained and the information is distilled to the biological functions that are most germane to the phenomenon being investigated.'),
(91196, 2006, 'bmc', 'A scalable machine-learning approach to recognize chemical names within large text databases', 'Wren, Jonathan D', 'Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, Norman, Oklahoma 73019, USA. Jonathan.Wren@OU.edu', 'United States', 17, 'Computational Biology|MEDLINE|Markov Chains|PubMed', 'Journal Article', '10.1186/1471-2105-7-S2-S3', '17118146', 'The use or study of chemical compounds permeates almost every scientific field and in each of them, the amount of textual information is growing rapidly. There is a need to accurately identify chemical names within text for a number of informatics efforts such as database curation, report summarization, tagging of named entities and keywords, or the development/curation of reference databases.'),
(91197, 2006, 'bmc', 'Support vector machine implementations for classification & clustering', 'Winters-Hilt, Stephen|Yelundur, Anil|McChesney, Charlie|Landry, Matthew', 'Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. swinters@chnola-research.org|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. swinters@chnola-research.org|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. swinters@chnola-research.org|Department of Computer Science, University of New Orleans, New Orleans, LA 70148, USA. swinters@chnola-research.org', 'United States|United States|United States|United States', 31, 'Algorithms|Classification|Cluster Analysis|Computational Biology|DNA|Risk Factors', 'Journal Article', '10.1186/1471-2105-7-S2-S4', '17118147', 'We describe Support Vector Machine (SVM) applications to classification and clustering of channel current data. SVMs are variational-calculus based methods that are constrained to have structural risk minimization (SRM), i.e., they provide noise tolerant solutions for pattern recognition. The SVM approach encapsulates a significant amount of model-fitting information in the choice of its kernel. In work thus far, novel, information-theoretic, kernels have been successfully employed for notably better performance over standard kernels. Currently there are two approaches for implementing multiclass SVMs. One is called external multi-class that arranges several binary classifiers as a decision tree such that they perform a single-class decision making function, with each leaf corresponding to a unique class. The second approach, namely internal-multiclass, involves solving a single optimization problem corresponding to the entire data set (with multiple hyperplanes).'),
(91198, 2006, 'bmc', 'Metric for measuring the effectiveness of clustering of DNA microarray expression', 'Loganantharaj, Raja|Cheepala, Satish|Clifford, John', 'Bioinformatics Research Lab, University of Louisiana at Lafayette, PO Box 44330, Lafayette, LA 70504, USA. logan@cacs.louisiana.edu|Bioinformatics Research Lab, University of Louisiana at Lafayette, PO Box 44330, Lafayette, LA 70504, USA. logan@cacs.louisiana.edu|Bioinformatics Research Lab, University of Louisiana at Lafayette, PO Box 44330, Lafayette, LA 70504, USA. logan@cacs.louisiana.edu', 'United States|United States|United States', 0, 'Algorithms|Biometry|Cluster Analysis|Computational Biology|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-7-S2-S5', '17118148', 'The recent advancement of microarray technology with lower noise and better affordability makes it possible to determine expression of several thousand genes simultaneously. The differentially expressed genes are filtered first and then clustered based on the expression profiles of the genes. A large number of clustering algorithms and distance measuring matrices are proposed in the literature. The popular ones among them include hierarchal clustering and k-means clustering. These algorithms have often used the Euclidian distance or Pearson correlation distance. The biologists or the practitioners are often confused as to which algorithm to use since there is no clear winner among algorithms or among distance measuring metrics. Several validation indices have been proposed in the literature and these are based directly or indirectly on distances, hence a method that uses any of these indices does not relate to any biological features such as biological processes or molecular functions.'),
(91199, 2006, 'bmc', 'RiboaptDB: a comprehensive database of ribozymes and aptamers', 'Thodima, Venkata|Pirooznia, Mehdi|Deng, Youping', 'Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, Mississippi 39406, USA. youping.deng@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, Mississippi 39406, USA. youping.deng@usm.edu|Department of Biological Sciences, University of Southern Mississippi, Hattiesburg, Mississippi 39406, USA. youping.deng@usm.edu', 'United States|United States|United States', 15, 'Aptamers, Nucleotide|Computational Biology|Databases, Nucleic Acid|Internet|RNA, Catalytic|Sequence Analysis, DNA|Software Design', 'Journal Article', '10.1186/1471-2105-7-S2-S6', '17118149', 'Catalytic RNA molecules are called ribozymes. The aptamers are DNA or RNA molecules that have been selected from vast populations of random sequences, through a combinatorial approach known as SELEX. The selected oligo-nucleotide sequences (~200 bp in length) have the ability to recognize broad range of specific ligands by forming binding pockets. These novel aptamer sequences can bind to nucleic acids, proteins or small organic and inorganic chemical compounds and have many potential uses in medicine and technology.'),
(91200, 2006, 'bmc', 'EGenBio: a data management system for evolutionary genomics and biodiversity', 'Nahum, Laila A|Reynolds, Matthew T|Wang, Zhengyuan O|Faith, Jeremiah J|Jonna, Rahul|Jiang, Zhi J|Meyer, Thomas J|Pollock, David D', 'Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803, USA.|Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803, USA.|Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803, USA.|Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803, USA.|Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803, USA.|Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803, USA.|Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803, USA.|Department of Biological Sciences, Biological Computation and Visualization Center, Louisiana State University, Baton Rouge, LA 70803, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 5, 'Animals|Biodiversity|Computational Biology|Database Management Systems|Databases, Genetic|Evolution, Molecular|Genomics|Humans|Internet|Sequence Analysis, DNA|Software Design', 'Journal Article', '10.1186/1471-2105-7-S2-S7', '17118150', 'Evolutionary genomics requires management and filtering of large numbers of diverse genomic sequences for accurate analysis and inference on evolutionary processes of genomic and functional change. We developed Evolutionary Genomics and Biodiversity (EGenBio, http://egenbio.lsu.edu) to begin to address this.'),
(91201, 2006, 'bmc', 'Independent component analysis-motivated approach to classificatory decomposition of cortical evoked potentials', 'Smolinski, Tomasz G|Buchanan, Roger|Boratyn, Grzegorz M|Milanova, Mariofanna|Prinz, Astrid A', 'Department of Biology, Emory University, Atlanta, Georgia, USA. tomasz.smolinski@emory.edu|Department of Biology, Emory University, Atlanta, Georgia, USA. tomasz.smolinski@emory.edu|Department of Biology, Emory University, Atlanta, Georgia, USA. tomasz.smolinski@emory.edu|Department of Biology, Emory University, Atlanta, Georgia, USA. tomasz.smolinski@emory.edu|Department of Biology, Emory University, Atlanta, Georgia, USA. tomasz.smolinski@emory.edu', 'Georgia|Georgia|Georgia|Georgia|Georgia', 0, 'Algorithms|Animals|Brain|Computational Biology|Evoked Potentials|Rats', 'Journal Article', '10.1186/1471-2105-7-S2-S8', '17118151', 'Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied to measurements registered in a controlled setting and under exposure to an external stimulus, it can facilitate analysis of the impact of the stimulus on those sources. The link between the stimulus and a given source can be verified by a classifier that is able to predict the condition a given signal was registered under, solely based on the components. However, the ICAs assumption about statistical independence of sources is often unrealistic and turns out to be insufficient to build an accurate classifier. Therefore, we propose to utilize a novel method, based on hybridization of ICA, multi-objective evolutionary algorithms (MOEA), and rough sets (RS), that attempts to improve the effectiveness of signal decomposition techniques by providing them with classification-awareness.'),
(91202, 2006, 'bmc', 'Microarray analysis distinguishes differential gene expression patterns from large and small colony Thymidine kinase mutants of L5178Y mouse lymphoma cells', 'Han, Tao|Wang, Jianyong|Tong, Weida|Moore, Martha M|Fuscoe, James C|Chen, Tao', 'Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR, USA.|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR, USA.|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR, USA.|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR, USA.|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR, USA.|Division of Genetic and Reproductive Toxicology, National Center for Toxicological Research, US FDA, Jefferson, AR, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Animals|Chromosomes|Cluster Analysis|Gene Expression Regulation, Neoplastic|Leukemia L5178|Mice|Mutation|Oligonucleotide Array Sequence Analysis|Software|Thymidine Kinase|Tumor Cells, Cultured', 'Journal Article', '10.1186/1471-2105-7-S2-S9', '17118152', 'The Thymidine kinase (Tk) mutants generated from the widely used L5178Y mouse lymphoma assay fall into two categories, small colony and large colony. Cells from the large colonies grow at a normal rate while cells from the small colonies grow slower than normal. The relative proportion of large and small colonies after mutagen treatment is associated with a mutagens ability to induce point mutations and/or chromosomal mutations. The molecular distinction between large and small colony mutants, however, is not clear.'),
(91203, 2006, 'bmc', 'Connectivity independent protein-structure alignment: a hierarchical approach', 'Kolbeck, Bjoern|May, Patrick|Schmidt-Goenner, Tobias|Steinke, Thomas|Knapp, Ernst-Walter', 'Macromolecular Modeling Group, Institute of Chemistry and Biochemistry, FU Berlin, Takustrasse 6, 14195 Berlin, Germany. bjko@chemie.fu-berlin.de <bjko@chemie.fu-berlin.de>|Macromolecular Modeling Group, Institute of Chemistry and Biochemistry, FU Berlin, Takustrasse 6, 14195 Berlin, Germany. bjko@chemie.fu-berlin.de <bjko@chemie.fu-berlin.de>|Macromolecular Modeling Group, Institute of Chemistry and Biochemistry, FU Berlin, Takustrasse 6, 14195 Berlin, Germany. bjko@chemie.fu-berlin.de <bjko@chemie.fu-berlin.de>|Macromolecular Modeling Group, Institute of Chemistry and Biochemistry, FU Berlin, Takustrasse 6, 14195 Berlin, Germany. bjko@chemie.fu-berlin.de <bjko@chemie.fu-berlin.de>|Macromolecular Modeling Group, Institute of Chemistry and Biochemistry, FU Berlin, Takustrasse 6, 14195 Berlin, Germany. bjko@chemie.fu-berlin.de <bjko@chemie.fu-berlin.de>', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Amino Acid Motifs|Computational Biology|Computer Graphics|Databases, Genetic|Models, Molecular|Protein Conformation|Protein Folding|Protein Structure, Tertiary|Proteins|Reproducibility of Results|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-7-510', '17118190', 'Protein-structure alignment is a fundamental tool to study protein function, evolution and model building. In the last decade several methods for structure alignment were introduced, but most of them ignore that structurally similar proteins can share the same spatial arrangement of secondary structure elements (SSE) but differ in the underlying polypeptide chain connectivity (non-sequential SSE connectivity).'),
(91204, 2006, 'bmc', 'Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis', 'Holloway, Andrew J|Oshlack, Alicia|Diyagama, Dileepa S|Bowtell, David D L|Smyth, Gordon K', 'Ian Potter Foundation Centre for Cancer Genomics and Predictive Medicine, Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, Victoria 3002, Australia. andrew.holloway@petermac.org|Ian Potter Foundation Centre for Cancer Genomics and Predictive Medicine, Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, Victoria 3002, Australia. andrew.holloway@petermac.org|Ian Potter Foundation Centre for Cancer Genomics and Predictive Medicine, Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, Victoria 3002, Australia. andrew.holloway@petermac.org|Ian Potter Foundation Centre for Cancer Genomics and Predictive Medicine, Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, Victoria 3002, Australia. andrew.holloway@petermac.org|Ian Potter Foundation Centre for Cancer Genomics and Predictive Medicine, Peter MacCallum Cancer Centre, St Andrews Place, East Melbourne, Victoria 3002, Australia. andrew.holloway@petermac.org', 'Australia|Australia|Australia|Australia|Australia', 18, 'Algorithms|Bias|Data Interpretation, Statistical|Fluorescent Dyes|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Jurkat Cells|Models, Statistical|Nonlinear Dynamics|Oligonucleotide Array Sequence Analysis|RNA, Messenger|Regression Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-7-511', '17118209', 'Concerns are often raised about the accuracy of microarray technologies and the degree of cross-platform agreement, but there are yet no methods which can unambiguously evaluate precision and sensitivity for these technologies on a whole-array basis.'),
(91205, 2006, 'bmc', 'Systematic assignment of thermodynamic constraints in metabolic network models', 'Kümmel, Anne|Panke, Sven|Heinemann, Matthias', 'Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli-Str, 16, 8093 Zurich, Switzerland. kuemmel@imsb.biol.ethz.ch|Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli-Str, 16, 8093 Zurich, Switzerland. kuemmel@imsb.biol.ethz.ch|Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli-Str, 16, 8093 Zurich, Switzerland. kuemmel@imsb.biol.ethz.ch', 'Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Computational Biology|Computer Simulation|Energy Metabolism|Escherichia coli|Models, Biological|Thermodynamics', 'Comparative Study', '10.1186/1471-2105-7-512', '17123434', 'The availability of genome sequences for many organisms enabled the reconstruction of several genome-scale metabolic network models. Currently, significant efforts are put into the automated reconstruction of such models. For this, several computational tools have been developed that particularly assist in identifying and compiling the organism-specific lists of metabolic reactions. In contrast, the last step of the model reconstruction process, which is the definition of the thermodynamic constraints in terms of reaction directionalities, still needs to be done manually. No computational method exists that allows for an automated and systematic assignment of reaction directions in genome-scale models.'),
(91206, 2006, 'bmc', 'JUICE: a data management system that facilitates the analysis of large volumes of information in an EST project workflow', 'Latorre, Mariano|Silva, Herman|Saba, Juan|Guziolowski, Carito|Vizoso, Paula|Martinez, Veronica|Maldonado, Jonathan|Morales, Andrea|Caroca, Rodrigo|Cambiazo, Veronica|Campos-Vargas, Reinaldo|Gonzalez, Mauricio|Orellana, Ariel|Retamales, Julio|Meisel, Lee A', 'Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>|Millennium Nucleus in Plant Cell Biology and Plant Biotechnology Center, Andres Bello University, Santiago, Chile. marianolatorre@gmail.com <marianolatorre@gmail.com>', 'Chile|Chile|Chile|Chile|Chile|Chile|Chile|Chile|Chile|Chile|Chile|Chile|Chile|Chile|Chile', 0, 'Chromatography|Computational Biology|Database Management Systems|Databases, Genetic|Databases, Nucleic Acid|Expressed Sequence Tags|Genome|Genomics|Management Information Systems|Programming Languages|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-7-513', '17123449', 'Expressed sequence tag (EST) analyses provide a rapid and economical means to identify candidate genes that may be involved in a particular biological process. These ESTs are useful in many Functional Genomics studies. However, the large quantity and complexity of the data generated during an EST sequencing project can make the analysis of this information a daunting task.'),
(91207, 2006, 'bmc', 'A hierarchical Naïve Bayes Model for handling sample heterogeneity in classification problems: an application to tissue microarrays', 'Demichelis, Francesca|Magni, Paolo|Piergiorgi, Paolo|Rubin, Mark A|Bellazzi, Riccardo', 'Bionformatics, SRA, ITC-irst & Dept. of Information and Communication Technology, University of Trento, Trento, Italy. fdemichelis@partners.org <fdemichelis@partners.org>|Bionformatics, SRA, ITC-irst & Dept. of Information and Communication Technology, University of Trento, Trento, Italy. fdemichelis@partners.org <fdemichelis@partners.org>|Bionformatics, SRA, ITC-irst & Dept. of Information and Communication Technology, University of Trento, Trento, Italy. fdemichelis@partners.org <fdemichelis@partners.org>|Bionformatics, SRA, ITC-irst & Dept. of Information and Communication Technology, University of Trento, Trento, Italy. fdemichelis@partners.org <fdemichelis@partners.org>|Bionformatics, SRA, ITC-irst & Dept. of Information and Communication Technology, University of Trento, Trento, Italy. fdemichelis@partners.org <fdemichelis@partners.org>', 'Italy|Italy|Italy|Italy|Italy', 45, 'Algorithms|Animals|Artificial Intelligence|Bayes Theorem|Connective Tissue|Data Interpretation, Statistical|Gene Expression Profiling|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteome', 'Journal Article', '10.1186/1471-2105-7-514', '17125514', 'Uncertainty often affects molecular biology experiments and data for different reasons. Heterogeneity of gene or protein expression within the same tumor tissue is an example of biological uncertainty which should be taken into account when molecular markers are used in decision making. Tissue Microarray (TMA) experiments allow for large scale profiling of tissue biopsies, investigating protein patterns characterizing specific disease states. TMA studies deal with multiple sampling of the same patient, and therefore with multiple measurements of same protein target, to account for possible biological heterogeneity. The aim of this paper is to provide and validate a classification model taking into consideration the uncertainty associated with measuring replicate samples.'),
(91208, 2006, 'bmc', 'SigFlux: a novel network feature to evaluate the importance of proteins in signal transduction networks', 'Liu, Wei|Li, Dong|Zhang, Jiyang|Zhu, Yunping|He, Fuchu', 'College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, China. liuwei@hupo.org.cn <liuwei@hupo.org.cn>|College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, China. liuwei@hupo.org.cn <liuwei@hupo.org.cn>|College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, China. liuwei@hupo.org.cn <liuwei@hupo.org.cn>|College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, China. liuwei@hupo.org.cn <liuwei@hupo.org.cn>|College of Mechanical & Electronic Engineering and Automatization, National University of Defense Technology, Changsha, China. liuwei@hupo.org.cn <liuwei@hupo.org.cn>', 'China|China|China|China|China', 0, 'Adaptor Proteins, Signal Transducing|Animals|Cluster Analysis|Evolution, Molecular|Feedback, Physiological|Gene Expression Regulation|Gene Regulatory Networks|Hippocampus|Metabolic Networks and Pathways|Mice|Neurons|Phenotype|Proteins|Receptors, Cell Surface|Receptors, Cytoplasmic and Nuclear|Signal Transduction|Software|Transcription Factors', 'Comparative Study', '10.1186/1471-2105-7-515', '17129367', 'Measuring each proteins importance in signaling networks helps to identify the crucial proteins in a cellular process, find the fragile portion of the biology system and further assist for disease therapy. However, there are relatively few methods to evaluate the importance of proteins in signaling networks.'),
(91209, 2006, 'bmc', 'Integrated siRNA design based on surveying of features associated with high RNAi effectiveness', 'Gong, Wuming|Ren, Yongliang|Xu, Qiqi|Wang, Yejun|Lin, Dong|Zhou, Haiyan|Li, Tongbin', 'Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wuming@biocompute.umn.edu <wuming@biocompute.umn.edu>|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wuming@biocompute.umn.edu <wuming@biocompute.umn.edu>|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wuming@biocompute.umn.edu <wuming@biocompute.umn.edu>|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wuming@biocompute.umn.edu <wuming@biocompute.umn.edu>|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wuming@biocompute.umn.edu <wuming@biocompute.umn.edu>|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wuming@biocompute.umn.edu <wuming@biocompute.umn.edu>|Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, USA. wuming@biocompute.umn.edu <wuming@biocompute.umn.edu>', 'United States|United States|United States|United States|United States|United States|United States', 44, 'Algorithms|Base Sequence|Databases, Nucleic Acid|Drug Design|Molecular Sequence Data|RNA Interference|RNA, Small Interfering|Sequence Analysis, RNA|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-7-516', '17129386', 'Short interfering RNAs have allowed the development of clean and easily regulated methods for disruption of gene expression. However, while these methods continue to grow in popularity, designing effective siRNA experiments can be challenging. The various existing siRNA design guidelines suffer from two problems: they differ considerably from each other, and they produce high levels of false-positive predictions when tested on data of independent origins.'),
(91210, 2006, 'bmc', 'Correcting ligands, metabolites, and pathways', 'Ott, Martin A|Vriend, Gert', 'Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands. m.ott@ncmls.ru.nl <m.ott@ncmls.ru.nl>|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen, Nijmegen, The Netherlands. m.ott@ncmls.ru.nl <m.ott@ncmls.ru.nl>', 'Netherlands|Netherlands', 0, 'Computational Biology|Databases, Factual|Enzymes|Internet|Ligands|Molecular Structure|Signal Transduction|Software', 'Journal Article', '10.1186/1471-2105-7-517', '17132165', 'A wide range of research areas in bioinformatics, molecular biology and medicinal chemistry require precise chemical structure information about molecules and reactions, e.g. drug design, ligand docking, metabolic network reconstruction, and systems biology. Most available databases, however, treat chemical structures more as illustrations than as a datafield in its own right. Lack of chemical accuracy impedes progress in the areas mentioned above. We present a database of metabolites called BioMeta that augments the existing pathway databases by explicitly assessing the validity, correctness, and completeness of chemical structure and reaction information.'),
(91211, 2006, 'bmc', 'Lexical adaptation of link grammar to the biomedical sublanguage: a comparative evaluation of three approaches', 'Pyysalo, Sampo|Salakoski, Tapio|Aubin, Sophie|Nazarenko, Adeline', 'Turku Centre for Computer Science (TUCS) and University of Turku, Lemminkäisenkatu 14 A, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi|Turku Centre for Computer Science (TUCS) and University of Turku, Lemminkäisenkatu 14 A, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi|Turku Centre for Computer Science (TUCS) and University of Turku, Lemminkäisenkatu 14 A, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi|Turku Centre for Computer Science (TUCS) and University of Turku, Lemminkäisenkatu 14 A, 20520 Turku, Finland. sampo.pyysalo@it.utu.fi', 'Finland|Finland|Finland|Finland', 0, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Databases, Factual|Information Storage and Retrieval|Natural Language Processing|Semantics|Software|Terminology as Topic|Vocabulary, Controlled', 'Comparative Study', '10.1186/1471-2105-7-S3-S2', '17134475', 'We study the adaptation of Link Grammar Parser to the biomedical sublanguage with a focus on domain terms not found in a general parser lexicon. Using two biomedical corpora, we implement and evaluate three approaches to addressing unknown words: automatic lexicon expansion, the use of morphological clues, and disambiguation using a part-of-speech tagger. We evaluate each approach separately for its effect on parsing performance and consider combinations of these approaches.'),
(91212, 2006, 'bmc', 'An environment for relation mining over richly annotated corpora: the case of GENIA', 'Rinaldi, Fabio|Schneider, Gerold|Kaljurand, Kaarel|Hess, Michael|Romacker, Martin', 'Institute of Computational Linguistics, IFI, University of Zurich, Switzerland. rinaldi@ifi.unizh.ch|Institute of Computational Linguistics, IFI, University of Zurich, Switzerland. rinaldi@ifi.unizh.ch|Institute of Computational Linguistics, IFI, University of Zurich, Switzerland. rinaldi@ifi.unizh.ch|Institute of Computational Linguistics, IFI, University of Zurich, Switzerland. rinaldi@ifi.unizh.ch|Institute of Computational Linguistics, IFI, University of Zurich, Switzerland. rinaldi@ifi.unizh.ch', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 4, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Databases, Factual|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Semantics|Software|Terminology as Topic|Vocabulary, Controlled', 'Evaluation Studies', '10.1186/1471-2105-7-S3-S3', '17134476', 'The biomedical domain is witnessing a rapid growth of the amount of published scientific results, which makes it increasingly difficult to filter the core information. There is a real need for support tools that digest the published results and extract the most important information.'),
(91213, 2006, 'bmc', 'Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts', 'Chun, Hong-Woo|Tsuruoka, Yoshimasa|Kim, Jin-Dong|Shiba, Rie|Nagata, Naoki|Hishiki, Teruyoshi|Tsujii, Junichi', 'Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. chun@is.s.u-tokyo.ac.jp|Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. chun@is.s.u-tokyo.ac.jp|Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. chun@is.s.u-tokyo.ac.jp|Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. chun@is.s.u-tokyo.ac.jp|Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. chun@is.s.u-tokyo.ac.jp|Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. chun@is.s.u-tokyo.ac.jp|Department of Computer Science, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. chun@is.s.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Databases, Factual|Genes|Humans|Information Storage and Retrieval|MEDLINE|Male|Natural Language Processing|Neoplasm Proteins|Periodicals as Topic|Prostatic Neoplasms|Semantics|Software|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-7-S3-S4', '17134477', 'Automatic recognition of relations between a specific disease term and its relevant genes or protein terms is an important practice of bioinformatics. Considering the utility of the results of this approach, we identified prostate cancer and gene terms with the ID tags of public biomedical databases. Moreover, considering that genetics experts will use our results, we classified them based on six topics that can be used to analyze the type of prostate cancers, genes, and their relations.'),
(91214, 2006, 'bmc', 'A critical review of PASBios argument structures for biomedical verbs', 'Cohen, K Bretonnel|Hunter, Lawrence', 'Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO, USA. kevin.cohen@gmail.com|Center for Computational Pharmacology, University of Colorado School of Medicine, Aurora, CO, USA. kevin.cohen@gmail.com', 'United States|United States', 0, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Databases, Factual|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Semantics|Software|Terminology as Topic|Vocabulary, Controlled', 'Evaluation Studies', '10.1186/1471-2105-7-S3-S5', '17134478', 'Propositional representations of biomedical knowledge are a critical component of most aspects of semantic mining in biomedicine. However, the proper set of propositions has yet to be determined. Recently, the PASBio project proposed a set of propositions and argument structures for biomedical verbs. This initial set of representations presents an opportunity for evaluating the suitability of predicate-argument structures as a scheme for representing verbal semantics in the biomedical domain. Here, we quantitatively evaluate several dimensions of the initial PASBio propositional structure repository.'),
(91215, 2006, 'bmc', 'Mapping data elements to terminological resources for integrating biomedical data sources', 'Mougin, Fleur|Burgun, Anita|Bodenreider, Olivier', 'EA 3888, IFR 140, Faculté de Médecine, Université de Rennes I, France. fleur.mougin@univ-rennes1.fr|EA 3888, IFR 140, Faculté de Médecine, Université de Rennes I, France. fleur.mougin@univ-rennes1.fr|EA 3888, IFR 140, Faculté de Médecine, Université de Rennes I, France. fleur.mougin@univ-rennes1.fr', 'France|France|France', 0, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Databases, Factual|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Semantics|Software|Terminology as Topic|Vocabulary, Controlled', 'Evaluation Studies', '10.1186/1471-2105-7-S3-S6', '17134479', 'Data integration is a crucial task in the biomedical domain and integrating data sources is one approach to integrating data. Data elements (DEs) in particular play an important role in data integration. We combine schema- and instance-based approaches to mapping DEs to terminological resources in order to facilitate data sources integration.'),
(91216, 2006, 'bmc', 'Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence', 'Du, Pufeng|Li, Yanda', 'Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing, 100084, China. dpf05@mails.tsinghua.edu.cn <dpf05@mails.tsinghua.edu.cn>|Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing, 100084, China. dpf05@mails.tsinghua.edu.cn <dpf05@mails.tsinghua.edu.cn>', 'China|China', 161, 'Amino Acid Sequence|Arabidopsis|Chemical Phenomena|Chemistry, Physical|Computational Biology|Mitochondrial Membranes|Molecular Sequence Data|Peptide Fragments|Predictive Value of Tests|Proteins|Sequence Analysis, Protein|Submitochondrial Particles', 'Journal Article', '10.1186/1471-2105-7-518', '17134515', 'Knowing the submitochondria localization of a mitochondria protein is an important step to understand its function. We develop a method which is based on an extended version of pseudo-amino acid composition to predict the protein localization within mitochondria. This work goes one step further than predicting protein subcellular location. We also try to predict the membrane protein type for mitochondrial inner membrane proteins.'),
(91217, 2006, 'bmc', 'Inferring topology from clustering coefficients in protein-protein interaction networks', 'Friedel, Caroline C|Zimmer, Ralf', 'LFE Bioinformatik, Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. caroline.friedel@bio.ifi.lmu.de|LFE Bioinformatik, Institut für Informatik, Ludwig-Maximilians-Universität München, Amalienstrasse 17, 80333 München, Germany. caroline.friedel@bio.ifi.lmu.de', 'Germany|Germany', 0, 'Cluster Analysis|Computer Simulation|Fungal Proteins|Protein Interaction Mapping', 'Comparative Study', '10.1186/1471-2105-7-519', '17137490', 'Although protein-protein interaction networks determined with high-throughput methods are incomplete, they are commonly used to infer the topology of the complete interactome. These partial networks often show a scale-free behavior with only a few proteins having many and the majority having only a few connections. Recently, the possibility was suggested that this scale-free nature may not actually reflect the topology of the complete interactome but could also be due to the error proneness and incompleteness of large-scale experiments.'),
(91218, 2006, 'bmc', 'An accurate and interpretable model for siRNA efficacy prediction', 'Vert, Jean-Philippe|Foveau, Nicolas|Lajaunie, Christian|Vandenbrouck, Yves', 'Centre for Computational Biology, Ecole des Mines de Paris, 35 rue Saint-Honoré, 77300 Fontainebleau, France. Jean-Philippe.Vert@ensmp.fr|Centre for Computational Biology, Ecole des Mines de Paris, 35 rue Saint-Honoré, 77300 Fontainebleau, France. Jean-Philippe.Vert@ensmp.fr|Centre for Computational Biology, Ecole des Mines de Paris, 35 rue Saint-Honoré, 77300 Fontainebleau, France. Jean-Philippe.Vert@ensmp.fr|Centre for Computational Biology, Ecole des Mines de Paris, 35 rue Saint-Honoré, 77300 Fontainebleau, France. Jean-Philippe.Vert@ensmp.fr', 'France|France|France|France', 179, 'Algorithms|Base Sequence|Computer Simulation|Drug Design|Models, Genetic|Molecular Sequence Data|RNA Interference|RNA, Small Interfering|Sequence Analysis, RNA|Structure-Activity Relationship', 'Evaluation Studies', '10.1186/1471-2105-7-520', '17137497', 'The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional study and new drug target identification. Although considerable progress has been made recently in understanding how the RNAi pathway mediates gene silencing, the design of potent siRNAs remains challenging.'),
(91219, 2006, 'bmc', 'Dynamic variable selection in SNP genotype autocalling from APEX microarray data', 'Podder, Mohua|Welch, William J|Zamar, Ruben H|Tebbutt, Scott J', 'Department of Statistics, University of British Columbia, Vancouver, BC, Canada. mpodder@mrl.ubc.ca <mpodder@mrl.ubc.ca>|Department of Statistics, University of British Columbia, Vancouver, BC, Canada. mpodder@mrl.ubc.ca <mpodder@mrl.ubc.ca>|Department of Statistics, University of British Columbia, Vancouver, BC, Canada. mpodder@mrl.ubc.ca <mpodder@mrl.ubc.ca>|Department of Statistics, University of British Columbia, Vancouver, BC, Canada. mpodder@mrl.ubc.ca <mpodder@mrl.ubc.ca>', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|DNA Mutational Analysis|DNA Probes|Databases, Genetic|Discriminant Analysis|Gene Expression Profiling|Genetic Variation|Genotype|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Evaluation Studies', '10.1186/1471-2105-7-521', '17137502', 'Single nucleotide polymorphisms (SNPs) are DNA sequence variations, occurring when a single nucleotide--adenine (A), thymine (T), cytosine (C) or guanine (G)--is altered. Arguably, SNPs account for more than 90% of human genetic variation. Our laboratory has developed a highly redundant SNP genotyping assay consisting of multiple probes with signals from multiple channels for a single SNP, based on arrayed primer extension (APEX). This mini-sequencing method is a powerful combination of a highly parallel microarray with distinctive Sanger-based dideoxy terminator sequencing chemistry. Using this microarray platform, our current genotype calling system (known as SNP Chart) is capable of calling single SNP genotypes by manual inspection of the APEX data, which is time-consuming and exposed to user subjectivity bias.'),
(91220, 2006, 'bmc', 'Cis-motifs upstream of the transcription and translation initiation sites are effectively revealed by their positional disequilibrium in eukaryote genomes using frequency distribution curves', 'Berendzen, Kenneth W|Stüber, Kurt|Harter, Klaus|Wanke, Dierk', 'Max-Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, D-50829 Köln, Germany. kenneth.berendzen@zmbp.uni-tuebingen.de <kenneth.berendzen@zmbp.uni-tuebingen.de>|Max-Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, D-50829 Köln, Germany. kenneth.berendzen@zmbp.uni-tuebingen.de <kenneth.berendzen@zmbp.uni-tuebingen.de>|Max-Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, D-50829 Köln, Germany. kenneth.berendzen@zmbp.uni-tuebingen.de <kenneth.berendzen@zmbp.uni-tuebingen.de>|Max-Planck Institute for Plant Breeding Research, Carl-von-Linné-Weg 10, D-50829 Köln, Germany. kenneth.berendzen@zmbp.uni-tuebingen.de <kenneth.berendzen@zmbp.uni-tuebingen.de>', 'Germany|Germany|Germany|Germany', 44, 'Algorithms|Animals|Computational Biology|Conserved Sequence|DNA|Eukaryotic Cells|Genome|Promoter Regions, Genetic|Protein Biosynthesis|Regulatory Elements, Transcriptional|Software', 'Journal Article', '10.1186/1471-2105-7-522', '17137509', 'The discovery of cis-regulatory motifs still remains a challenging task even though the number of sequenced genomes is constantly growing. Computational analyses using pattern search algorithms have been valuable in phylogenetic footprinting approaches as have expression profile experiments to predict co-occurring motifs. Surprisingly little is known about the nature of cis-regulatory element (CRE) distribution in promoters.'),
(91221, 2006, 'bmc', 'BioMoby extensions to the Taverna workflow management and enactment software', 'Kawas, Edward|Senger, Martin|Wilkinson, Mark D', 'James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St, Pauls Hospital, Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6Z 1Y6, Canada. ekawas@mrl.ubc.ca <ekawas@mrl.ubc.ca>|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St, Pauls Hospital, Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6Z 1Y6, Canada. ekawas@mrl.ubc.ca <ekawas@mrl.ubc.ca>|James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St, Pauls Hospital, Department of Medical Genetics, University of British Columbia, Vancouver, BC, V6Z 1Y6, Canada. ekawas@mrl.ubc.ca <ekawas@mrl.ubc.ca>', 'Canada|Canada|Canada', 0, 'Biology|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Internet|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-523', '17137515', 'As biology becomes an increasingly computational science, it is critical that we develop software tools that support not only bioinformaticians, but also bench biologists in their exploration of the vast and complex data-sets that continue to build from international genomic, proteomic, and systems-biology projects. The BioMoby interoperability system was created with the goal of facilitating the movement of data from one Web-based resource to another to fulfill the requirements of non-expert bioinformaticians. In parallel with the development of BioMoby, the European myGrid project was designing Taverna, a bioinformatics workflow design and enactment tool. Here we describe the marriage of these two projects in the form of a Taverna plug-in that provides access to many of BioMobys features through the Taverna interface.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(91222, 2006, 'bmc', 'Improvement in accuracy of multiple sequence alignment using novel group-to-group sequence alignment algorithm with piecewise linear gap cost', 'Yamada, Shinsuke|Gotoh, Osamu|Yamana, Hayato', 'Department of Computer Science, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. shinsuke@yama.info.waseda.ac.jp|Department of Computer Science, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. shinsuke@yama.info.waseda.ac.jp|Department of Computer Science, Graduate School of Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan. shinsuke@yama.info.waseda.ac.jp', 'Japan|Japan|Japan', 23, 'Algorithms|Conserved Sequence|Linear Models|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis|Sequence Homology', 'Evaluation Studies', '10.1186/1471-2105-7-524', '17137519', 'Multiple sequence alignment (MSA) is a useful tool in bioinformatics. Although many MSA algorithms have been developed, there is still room for improvement in accuracy and speed. In the alignment of a family of protein sequences, global MSA algorithms perform better than local ones in many cases, while local ones perform better than global ones when some sequences have long insertions or deletions (indels) relative to others. Many recent leading MSA algorithms have incorporated pairwise alignment information obtained from a mixture of sources into their scoring system to improve accuracy of alignment containing long indels.'),
(91223, 2006, 'bmc', 'iHAP--integrated haplotype analysis pipeline for characterizing the haplotype structure of genes', 'Song, Chun Meng|Yeo, Boon Huat|Tantoso, Erwin|Yang, Yuchen|Lim, Yun Ping|Li, Kuo-Bin|Rajagopal, Gunaretnam', 'Bioinformatics Institute, 30 Biopolis Street, #07-01, 138671, Singapore. alfreds@bii.a-star.edu.sg <alfreds@bii.a-star.edu.sg>|Bioinformatics Institute, 30 Biopolis Street, #07-01, 138671, Singapore. alfreds@bii.a-star.edu.sg <alfreds@bii.a-star.edu.sg>|Bioinformatics Institute, 30 Biopolis Street, #07-01, 138671, Singapore. alfreds@bii.a-star.edu.sg <alfreds@bii.a-star.edu.sg>|Bioinformatics Institute, 30 Biopolis Street, #07-01, 138671, Singapore. alfreds@bii.a-star.edu.sg <alfreds@bii.a-star.edu.sg>|Bioinformatics Institute, 30 Biopolis Street, #07-01, 138671, Singapore. alfreds@bii.a-star.edu.sg <alfreds@bii.a-star.edu.sg>|Bioinformatics Institute, 30 Biopolis Street, #07-01, 138671, Singapore. alfreds@bii.a-star.edu.sg <alfreds@bii.a-star.edu.sg>|Bioinformatics Institute, 30 Biopolis Street, #07-01, 138671, Singapore. alfreds@bii.a-star.edu.sg <alfreds@bii.a-star.edu.sg>', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 12, 'Algorithms|Base Sequence|Chromosome Mapping|Databases, Genetic|Genetic Variation|Haplotypes|Information Storage and Retrieval|Molecular Sequence Data|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-7-525', '17137522', 'The advent of genotype data from large-scale efforts that catalog the genetic variants of different populations have given rise to new avenues for multifactorial disease association studies. Recent work shows that genotype data from the International HapMap Project have a high degree of transferability to the wider population. This implies that the design of genotyping studies on local populations may be facilitated through inferences drawn from information contained in HapMap populations.'),
(91224, 2006, 'bmc', 'Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas', 'Turkheimer, Federico E|Roncaroli, Federico|Hennuy, Benoit|Herens, Christian|Nguyen, Minh|Martin, Didier|Evrard, Annick|Bours, Vincent|Boniver, Jacques|Deprez, Manuel', 'Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk|Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk|Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk|Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk|Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk|Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk|Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk|Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk|Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk|Department of Clinical Neuroscience, Division of Neuroscience, Imperial College London, UK. federico.turkheimer@imperial.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Biomarkers, Tumor|Brain Neoplasms|Chromosome Mapping|Chromosomes, Human|Diagnosis, Computer-Assisted|Glioma|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Software', 'Evaluation Studies', '10.1186/1471-2105-7-526', '17140431', 'Expression microarrays represent a powerful technique for the simultaneous investigation of thousands of genes. The evidence that genes are not randomly distributed in the genome and that their coordinated expression depends on their position on chromosomes has highlighted the need for mathematical approaches to exploit this dependency for the analysis of expression data-sets.'),
(91225, 2006, 'bmc', 'Logarithmic gap costs decrease alignment accuracy', 'Cartwright, Reed A', 'Department of Genetics, University of Georgia, Athens, GA 30602-7223, USA. racartwr@ncsu.edu', 'Georgia', 0, 'Algorithms|Computer Simulation|Models, Genetic|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1186/1471-2105-7-527', '17147805', 'Studies on the distribution of indel sizes have consistently found that they obey a power law. This finding has lead several scientists to propose that logarithmic gap costs, G (k) = a + c ln k, are more biologically realistic than affine gap costs, G (k) = a + bk, for sequence alignment. Since quick and efficient affine costs are currently the most popular way to globally align sequences, the goal of this paper is to determine whether logarithmic gap costs improve alignment accuracy significantly enough the merit their use over the faster affine gap costs.'),
(91226, 2006, 'bmc', 'A specialized learner for inferring structured cis-regulatory modules', 'Noto, Keith|Craven, Mark', 'Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA. noto@cs.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA. noto@cs.wisc.edu', 'United States|United States', 2, 'Algorithms|Artificial Intelligence|Base Sequence|Molecular Sequence Data|Pattern Recognition, Automated|Regulatory Elements, Transcriptional|Regulatory Sequences, Nucleic Acid|Sequence Analysis, DNA|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-7-528', '17147812', 'The process of transcription is controlled by systems of transcription factors, which bind to specific patterns of binding sites in the transcriptional control regions of genes, called cis-regulatory modules (CRMs). We present an expressive and easily comprehensible CRM representation which is capable of capturing several aspects of a CRMs structure and distinguishing between DNA sequences which do or do not contain it. We also present a learning algorithm tailored for this domain, and a novel method to avoid overfitting by controlling the expressivity of the model.'),
(91227, 2006, 'bmc', 'Fast estimation of the difference between two PAM/JTT evolutionary distances in triplets of homologous sequences', 'Dessimoz, Christophe|Gil, Manuel|Schneider, Adrian|Gonnet, Gaston H', 'ETH Zurich, Institute of Computational Science, 8092 Zürich, Switzerland. cdessimoz@inf.ethz.ch|ETH Zurich, Institute of Computational Science, 8092 Zürich, Switzerland. cdessimoz@inf.ethz.ch|ETH Zurich, Institute of Computational Science, 8092 Zürich, Switzerland. cdessimoz@inf.ethz.ch|ETH Zurich, Institute of Computational Science, 8092 Zürich, Switzerland. cdessimoz@inf.ethz.ch', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Evolution, Molecular|Linkage Disequilibrium|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-7-529', '17147817', 'The estimation of the difference between two evolutionary distances within a triplet of homologs is a common operation that is used for example to determine which of two sequences is closer to a third one. The most accurate method is currently maximum likelihood over the entire triplet. However, this approach is relatively time consuming.'),
(91228, 2006, 'bmc', 'MathDAMP: a package for differential analysis of metabolite profiles', 'Baran, Richard|Kochi, Hayataro|Saito, Natsumi|Suematsu, Makoto|Soga, Tomoyoshi|Nishioka, Takaaki|Robert, Martin|Tomita, Masaru', 'Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>|Institute for Advanced Biosciences, Keio University, Tsuruoka, Yamagata 997-0017, Japan. richard.baran@gmail.com <richard.baran@gmail.com>', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Biomarkers|Computational Biology|Energy Metabolism|Mathematical Computing', 'Journal Article', '10.1186/1471-2105-7-530', '17166258', 'With the advent of metabolomics as a powerful tool for both functional and biomarker discovery, the identification of specific differences between complex metabolite profiles is becoming a major challenge in the data analysis pipeline. The task remains difficult, given the datasets size, complexity, and common shifts in migration (elution/retention) times between samples analyzed by hyphenated mass spectrometry methods.'),
(91229, 2006, 'bmc', 'The NeuARt II system: a viewing tool for neuroanatomical data based on published neuroanatomical atlases', 'Burns, Gully A P C|Cheng, Wei-Cheng|Thompson, Richard H|Swanson, Larry W', 'Information Sciences Institute, 4676 Admiralty Way, Marina Del Rey, CA 90292, USA. gully@usc.edu|Information Sciences Institute, 4676 Admiralty Way, Marina Del Rey, CA 90292, USA. gully@usc.edu|Information Sciences Institute, 4676 Admiralty Way, Marina Del Rey, CA 90292, USA. gully@usc.edu|Information Sciences Institute, 4676 Admiralty Way, Marina Del Rey, CA 90292, USA. gully@usc.edu', 'United States|United States|United States|United States', 14, 'Anatomy, Artistic|Computer Graphics|Imaging, Three-Dimensional|Medical Illustration|Models, Anatomic|Neuroanatomy|Periodicals as Topic|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-531', '17166289', 'Anatomical studies of neural circuitry describing the basic wiring diagram of the brain produce intrinsically spatial, highly complex data of great value to the neuroscience community. Published neuroanatomical atlases provide a spatial framework for these studies. We have built an informatics framework based on these atlases for the representation of neuroanatomical knowledge. This framework not only captures current methods of anatomical data acquisition and analysis, it allows these studies to be collated, compared and synthesized within a single system.'),
(91230, 2006, 'bmc', 'Model-driven user interfaces for bioinformatics data resources: regenerating the wheel as an alternative to reinventing it', 'Garwood, Kevin|Garwood, Christopher|Hedeler, Cornelia|Griffiths, Tony|Swainston, Neil|Oliver, Stephen G|Paton, Norman W', 'School of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK. garwood@cs.man.ac.uk <garwood@cs.man.ac.uk>|School of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK. garwood@cs.man.ac.uk <garwood@cs.man.ac.uk>|School of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK. garwood@cs.man.ac.uk <garwood@cs.man.ac.uk>|School of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK. garwood@cs.man.ac.uk <garwood@cs.man.ac.uk>|School of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK. garwood@cs.man.ac.uk <garwood@cs.man.ac.uk>|School of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK. garwood@cs.man.ac.uk <garwood@cs.man.ac.uk>|School of Computer Science, University of Manchester, Oxford Road, Manchester M13 9PL, UK. garwood@cs.man.ac.uk <garwood@cs.man.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Databases, Factual|Models, Biological|Software Design', 'Journal Article', '10.1186/1471-2105-7-532', '17169146', 'The proliferation of data repositories in bioinformatics has resulted in the development of numerous interfaces that allow scientists to browse, search and analyse the data that they contain. Interfaces typically support repository access by means of web pages, but other means are also used, such as desktop applications and command line tools. Interfaces often duplicate functionality amongst each other, and this implies that associated development activities are repeated in different laboratories. Interfaces developed by public laboratories are often created with limited developer resources. In such environments, reducing the time spent on creating user interfaces allows for a better deployment of resources for specialised tasks, such as data integration or analysis. Laboratories maintaining data resources are challenged to reconcile requirements for software that is reliable, functional and flexible with limitations on software development resources.'),
(91231, 2006, 'bmc', 'Effect of various normalization methods on Applied Biosystems expression array system data', 'Barbacioru, Catalin C|Wang, Yulei|Canales, Roger D|Sun, Yongming A|Keys, David N|Chan, Frances|Poulter, Karen A|Samaha, Raymond R', 'Molecular Biology Division, Applied Biosystems, Foster City, CA 94404, USA. catalin.barbacioru@appliedbiosystems.com|Molecular Biology Division, Applied Biosystems, Foster City, CA 94404, USA. catalin.barbacioru@appliedbiosystems.com|Molecular Biology Division, Applied Biosystems, Foster City, CA 94404, USA. catalin.barbacioru@appliedbiosystems.com|Molecular Biology Division, Applied Biosystems, Foster City, CA 94404, USA. catalin.barbacioru@appliedbiosystems.com|Molecular Biology Division, Applied Biosystems, Foster City, CA 94404, USA. catalin.barbacioru@appliedbiosystems.com|Molecular Biology Division, Applied Biosystems, Foster City, CA 94404, USA. catalin.barbacioru@appliedbiosystems.com|Molecular Biology Division, Applied Biosystems, Foster City, CA 94404, USA. catalin.barbacioru@appliedbiosystems.com|Molecular Biology Division, Applied Biosystems, Foster City, CA 94404, USA. catalin.barbacioru@appliedbiosystems.com', 'United States|United States|United States|United States|United States|United States|United States|United States', 32, 'Algorithms|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reference Values|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-7-533', '17173684', 'DNA microarray technology provides a powerful tool for characterizing gene expression on a genome scale. While the technology has been widely used in discovery-based medical and basic biological research, its direct application in clinical practice and regulatory decision-making has been questioned. A few key issues, including the reproducibility, reliability, compatibility and standardization of microarray analysis and results, must be critically addressed before any routine usage of microarrays in clinical laboratory and regulated areas can occur. In this study we investigate some of these issues for the Applied Biosystems Human Genome Survey Microarrays.'),
(91232, 2006, 'bmc', 'iHOPerator: user-scripting a personalized bioinformatics Web, starting with the iHOP website', 'Good, Benjamin M|Kawas, Edward A|Kuo, Byron Yu-Lin|Wilkinson, Mark D', 'The James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, Providence Health Care/University of British Columbia, St, Pauls Hospital, Rm, 166, 1081 Burrard St, Vancouver, British Columbia, V6Z 1Y6, Canada. goodb@interchange.ubc.ca|The James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, Providence Health Care/University of British Columbia, St, Pauls Hospital, Rm, 166, 1081 Burrard St, Vancouver, British Columbia, V6Z 1Y6, Canada. goodb@interchange.ubc.ca|The James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, Providence Health Care/University of British Columbia, St, Pauls Hospital, Rm, 166, 1081 Burrard St, Vancouver, British Columbia, V6Z 1Y6, Canada. goodb@interchange.ubc.ca|The James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, Providence Health Care/University of British Columbia, St, Pauls Hospital, Rm, 166, 1081 Burrard St, Vancouver, British Columbia, V6Z 1Y6, Canada. goodb@interchange.ubc.ca', 'Canada|Canada|Canada|Canada', 16, 'Computational Biology|Databases, Factual|Internet|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-534', '17173692', 'User-scripts are programs stored in Web browsers that can manipulate the content of websites prior to display in the browser. They provide a novel mechanism by which users can conveniently gain increased control over the content and the display of the information presented to them on the Web. As the Web is the primary medium by which scientists retrieve biological information, any improvements in the mechanisms that govern the utility or accessibility of this information may have profound effects. GreaseMonkey is a Mozilla Firefox extension that facilitates the development and deployment of user-scripts for the Firefox web-browser. We utilize this to enhance the content and the presentation of the iHOP (information Hyperlinked Over Proteins) website.'),
(91233, 2006, 'bmc', 'PageMan: an interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments', 'Usadel, Björn|Nagel, Axel|Steinhauser, Dirk|Gibon, Yves|Bläsing, Oliver E|Redestig, Henning|Sreenivasulu, Nese|Krall, Leonard|Hannah, Matthew A|Poree, Fabien|Fernie, Alisdair R|Stitt, Mark', 'Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam, Germany. usadel@mpimp-golm.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 248, 'Database Management Systems|Databases, Genetic|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-535', '17176458', 'Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis.'),
(91234, 2006, 'bmc', 'TaxMan: a taxonomic database manager', 'Jones, Martin|Blaxter, Mark', 'Institute of Evolutionary Biology, Kings Buildings, Ashworth Laboratories, West Mains Road, Edinburgh EH9 3JT, UK. martin.jones@ed.ac.uk|Institute of Evolutionary Biology, Kings Buildings, Ashworth Laboratories, West Mains Road, Edinburgh EH9 3JT, UK. martin.jones@ed.ac.uk', 'United Kingdom|United Kingdom', 4, 'Database Management Systems|Databases, Genetic|Databases, Nucleic Acid|Phylogeny|Software', 'Journal Article', '10.1186/1471-2105-7-536', '17176465', 'Phylogenetic analysis of large, multiple-gene datasets, assembled from public sequence databases, is rapidly becoming a popular way to approach difficult phylogenetic problems. Supermatrices (concatenated multiple sequence alignments of multiple genes) can yield more phylogenetic signal than individual genes. However, manually assembling such datasets for a large taxonomic group is time-consuming and error-prone. Additionally, sequence curation, alignment and assessment of the results of phylogenetic analysis are made particularly difficult by the potential for a given gene in a given species to be unrepresented, or to be represented by multiple or partial sequences. We have developed a software package, TaxMan, that largely automates the processes of sequence acquisition, consensus building, alignment and taxon selection to facilitate this type of phylogenetic study.'),
(91235, 2006, 'bmc', 'Empirical study of supervised gene screening', 'Ma, Shuangge', 'Department of Epidemiology and Public Health, Yale University, New Haven, CT 06520, USA. shuangge.ma@yale.edu', 'United States', 0, 'Artificial Intelligence|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Gene Expression Profiling|Genetic Predisposition to Disease|Genetic Testing|Humans|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-7-537', '17176468', 'Microarray studies provide a way of linking variations of phenotypes with their genetic causations. Constructing predictive models using high dimensional microarray measurements usually consists of three steps: (1) unsupervised gene screening, (2) supervised gene screening, and (3) statistical model building. Supervised gene screening based on marginal gene ranking is commonly used to reduce the number of genes in the model building. Various simple statistics, such as t-statistic or signal to noise ratio, have been used to rank genes in the supervised screening. Despite of its extensive usage, statistical study of supervised gene screening remains scarce. Our study is partly motivated by the differences in gene discovery results caused by using different supervised gene screening methods.'),
(91236, 2006, 'bmc', 'Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments', 'Sartor, Maureen A|Tomlinson, Craig R|Wesselkamper, Scott C|Sivaganesan, Siva|Leikauf, George D|Medvedovic, Mario', 'Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA. maureen.sartor@uc.edu <maureen.sartor@uc.edu>|Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA. maureen.sartor@uc.edu <maureen.sartor@uc.edu>|Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA. maureen.sartor@uc.edu <maureen.sartor@uc.edu>|Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA. maureen.sartor@uc.edu <maureen.sartor@uc.edu>|Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA. maureen.sartor@uc.edu <maureen.sartor@uc.edu>|Department of Environmental Health, University of Cincinnati, Cincinnati, OH, USA. maureen.sartor@uc.edu <maureen.sartor@uc.edu>', 'United States|United States|United States|United States|United States|United States', 170, 'Animals|Aquaporin 5|Basic Helix-Loop-Helix Transcription Factors|Bayes Theorem|Cells, Cultured|Computer Simulation|Female|Fibroblast Growth Factor 2|Gene Expression Profiling|Mice|Mice, Knockout|Models, Genetic|Nickel|Oligonucleotide Array Sequence Analysis|Receptors, Aryl Hydrocarbon|Signal Transduction|Transforming Growth Factor beta', 'Comparative Study', '10.1186/1471-2105-7-538', '17177995', 'The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating variability of gene expression measurements in microarray experiments is essential for correctly identifying differentially expressed genes. Several recently developed methods for testing differential expression of genes utilize hierarchical Bayesian models to pool information from multiple genes. We have developed a statistical testing procedure that further improves upon current methods by incorporating the well-documented relationship between the absolute gene expression level and the variance of gene expression measurements into the general empirical Bayes framework.'),
(91237, 2006, 'bmc', 'A minimally invasive multiple marker approach allows highly efficient detection of meningioma tumors', 'Keller, Andreas|Ludwig, Nicole|Comtesse, Nicole|Hildebrandt, Andreas|Meese, Eckart|Lenhof, Hans-Peter', 'Center for Bioinformatics, Saarland University, Building 3,11, 66041 Saarbrücken, Germany. ack@bioinf.uni-sb.de <ack@bioinf.uni-sb.de>|Center for Bioinformatics, Saarland University, Building 3,11, 66041 Saarbrücken, Germany. ack@bioinf.uni-sb.de <ack@bioinf.uni-sb.de>|Center for Bioinformatics, Saarland University, Building 3,11, 66041 Saarbrücken, Germany. ack@bioinf.uni-sb.de <ack@bioinf.uni-sb.de>|Center for Bioinformatics, Saarland University, Building 3,11, 66041 Saarbrücken, Germany. ack@bioinf.uni-sb.de <ack@bioinf.uni-sb.de>|Center for Bioinformatics, Saarland University, Building 3,11, 66041 Saarbrücken, Germany. ack@bioinf.uni-sb.de <ack@bioinf.uni-sb.de>|Center for Bioinformatics, Saarland University, Building 3,11, 66041 Saarbrücken, Germany. ack@bioinf.uni-sb.de <ack@bioinf.uni-sb.de>', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Antigens, Neoplasm|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Immunoassay|Meningeal Neoplasms|Meningioma|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-7-539', '17184519', 'The development of effective frameworks that permit an accurate diagnosis of tumors, especially in their early stages, remains a grand challenge in the field of bioinformatics. Our approach uses statistical learning techniques applied to multiple antigen tumor antigen markers utilizing the immune system as a very sensitive marker of molecular pathological processes. For validation purposes we choose the intracranial meningioma tumors as model system since they occur very frequently, are mostly benign, and are genetically stable.'),
(91238, 2006, 'bmc', 'A method for estimation of elasticities in metabolic networks using steady state and dynamic metabolomics data and linlog kinetics', 'Nikerel, I Emrah|van Winden, Wouter A|van Gulik, Walter M|Heijnen, Joseph J', 'Department of Biotechnology, TU Delft, Julianalaan 67, 2628 BC Delft, The Netherlands. i.e.nikerel@tnw.tudelft.nl|Department of Biotechnology, TU Delft, Julianalaan 67, 2628 BC Delft, The Netherlands. i.e.nikerel@tnw.tudelft.nl|Department of Biotechnology, TU Delft, Julianalaan 67, 2628 BC Delft, The Netherlands. i.e.nikerel@tnw.tudelft.nl|Department of Biotechnology, TU Delft, Julianalaan 67, 2628 BC Delft, The Netherlands. i.e.nikerel@tnw.tudelft.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Glucose|Glycolysis|Kinetics|Linear Models|Metabolic Clearance Rate|Models, Biological|Proteome|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Evaluation Studies', '10.1186/1471-2105-7-540', '17184531', 'Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (dis)functioning of living cells. So far dynamic metabolic models generally have been based on mechanistic rate equations which often contain so many parameters that their identifiability from experimental data forms a serious problem. Recently, approximative rate equations, based on the linear logarithmic (linlog) format have been proposed as a suitable alternative with fewer parameters.'),
(91239, 2006, 'bmc', 'How repetitive are genomes?', 'Haubold, Bernhard|Wiehe, Thomas', 'Department of Biotechnology & Bioinformatics, University of Applied Sciences Weihenstephan, Freising, Germany. bernhard.haubold@fh-weihenstephan.de|Department of Biotechnology & Bioinformatics, University of Applied Sciences Weihenstephan, Freising, Germany. bernhard.haubold@fh-weihenstephan.de', 'Germany|Germany', 0, 'Algorithms|Animals|Chromosome Mapping|Computer Simulation|Genome|Models, Genetic|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-7-541', '17187668', 'Genome sequences vary strongly in their repetitiveness and the causes for this are still debated. Here we propose a novel measure of genome repetitiveness, the index of repetitiveness, Ir, which can be computed in time proportional to the length of the sequences analyzed. We apply it to 336 genomes from all three domains of life.'),
(91240, 2006, 'bmc', 'HaploRec: efficient and accurate large-scale reconstruction of haplotypes', 'Eronen, Lauri|Geerts, Floris|Toivonen, Hannu', 'HIIT-BRU, Department of Computer Science, University of Helsinki, Finland. lauri.eronen@cs.helsinki.fi|HIIT-BRU, Department of Computer Science, University of Helsinki, Finland. lauri.eronen@cs.helsinki.fi|HIIT-BRU, Department of Computer Science, University of Helsinki, Finland. lauri.eronen@cs.helsinki.fi', 'Finland|Finland|Finland', 0, 'Chromosome Mapping|Databases, Genetic|Haplotypes|Humans|Linkage Disequilibrium|Markov Chains|Models, Genetic|Software', 'Comparative Study', '10.1186/1471-2105-7-542', '17187677', 'Haplotypes extracted from human DNA can be used for gene mapping and other analysis of genetic patterns within and across populations. A fundamental problem is, however, that current practical laboratory methods do not give haplotype information. Estimation of phased haplotypes of unrelated individuals given their unphased genotypes is known as the haplotype reconstruction or phasing problem.'),
(91241, 2006, 'bmc', 'Recursive gene selection based on maximum margin criterion: a comparison with SVM-RFE', 'Niijima, Satoshi|Kuhara, Satoru', 'Department of Bioinformatics, Graduate School of Systems Life Sciences, Kyushu University, Hakozaki 6-10-1, Higashi-ku, Fukuoka 812-8581, Japan. niijima@grt.kyushu-u.ac.jp|Department of Bioinformatics, Graduate School of Systems Life Sciences, Kyushu University, Hakozaki 6-10-1, Higashi-ku, Fukuoka 812-8581, Japan. niijima@grt.kyushu-u.ac.jp', 'Japan|Japan', 32, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Comparative Study', '10.1186/1471-2105-7-543', '17187691', 'In class prediction problems using microarray data, gene selection is essential to improve the prediction accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVM-RFE) has become one of the leading methods and is being widely used. The SVM-based approach performs gene selection using the weight vector of the hyperplane constructed by the samples on the margin. However, the performance can be easily affected by noise and outliers, when it is applied to noisy, small sample size microarray data.'),
(91242, 2006, 'bmc', 'The Virtual Insect Brain protocol: creating and comparing standardized neuroanatomy', 'Jenett, Arnim|Schindelin, Johannes E|Heisenberg, Martin', 'Lehrstuhl für Genetik und Neurobiologie, Biozentrum, Am Hubland, D-97074 Würzburg, Germany. arnim.jenett@biozentrum.uni-wuerzburg.de|Lehrstuhl für Genetik und Neurobiologie, Biozentrum, Am Hubland, D-97074 Würzburg, Germany. arnim.jenett@biozentrum.uni-wuerzburg.de|Lehrstuhl für Genetik und Neurobiologie, Biozentrum, Am Hubland, D-97074 Würzburg, Germany. arnim.jenett@biozentrum.uni-wuerzburg.de', 'Germany|Germany|Germany', 37, 'Animals|Brain|Computer Graphics|Computer Simulation|Drosophila melanogaster|Imaging, Three-Dimensional|Models, Anatomic|Models, Neurological|Neuroanatomy|Software|Subtraction Technique|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-7-544', '17196102', 'In the fly Drosophila melanogaster, new genetic, physiological, molecular and behavioral techniques for the functional analysis of the brain are rapidly accumulating. These diverse investigations on the function of the insect brain use gene expression patterns that can be visualized and provide the means for manipulating groups of neurons as a common ground. To take advantage of these patterns one needs to know their typical anatomy.'),
(91243, 2007, 'bmc', 'Comparing sequences without using alignments: application to HIV/SIV subtyping', 'Didier, Gilles|Debomy, Laurent|Pupin, Maude|Zhang, Ming|Grossmann, Alexander|Devauchelle, Claudine|Laprevotte, Ivan', 'Institut Mathématique de Luminy, UMR 6206, Campus de Luminy, Case 907, 13288 Marseille Cedex 9, France. didier@iml.univ-mrs.fr <didier@iml.univ-mrs.fr>|Institut Mathématique de Luminy, UMR 6206, Campus de Luminy, Case 907, 13288 Marseille Cedex 9, France. didier@iml.univ-mrs.fr <didier@iml.univ-mrs.fr>|Institut Mathématique de Luminy, UMR 6206, Campus de Luminy, Case 907, 13288 Marseille Cedex 9, France. didier@iml.univ-mrs.fr <didier@iml.univ-mrs.fr>|Institut Mathématique de Luminy, UMR 6206, Campus de Luminy, Case 907, 13288 Marseille Cedex 9, France. didier@iml.univ-mrs.fr <didier@iml.univ-mrs.fr>|Institut Mathématique de Luminy, UMR 6206, Campus de Luminy, Case 907, 13288 Marseille Cedex 9, France. didier@iml.univ-mrs.fr <didier@iml.univ-mrs.fr>|Institut Mathématique de Luminy, UMR 6206, Campus de Luminy, Case 907, 13288 Marseille Cedex 9, France. didier@iml.univ-mrs.fr <didier@iml.univ-mrs.fr>|Institut Mathématique de Luminy, UMR 6206, Campus de Luminy, Case 907, 13288 Marseille Cedex 9, France. didier@iml.univ-mrs.fr <didier@iml.univ-mrs.fr>', 'France|France|France|France|France|France|France', 0, 'Animals|Base Sequence|HIV|Humans|Molecular Sequence Data|Sequence Alignment|Serotyping|Simian Immunodeficiency Virus', 'Comparative Study', '10.1186/1471-2105-8-1', '17199892', 'In general, the construction of trees is based on sequence alignments. This procedure, however, leads to loss of informationwhen parts of sequence alignments (for instance ambiguous regions) are deleted before tree building. To overcome this difficulty, one of us previously introduced a new and rapid algorithm that calculates dissimilarity matrices between sequences without preliminary alignment.'),
(91244, 2007, 'bmc', 'TPRpred: a tool for prediction of TPR-, PPR- and SEL1-like repeats from protein sequences', 'Karpenahalli, Manjunatha R|Lupas, Andrei N|Söding, Johannes', 'Department of Protein Evolution, Max-Planck-lnstitute for Developmental Biology, Spemannstrasse 35, D-72076 Tübingen, Germany. manju@tuebingen.mpg.de <manju@tuebingen.mpg.de>|Department of Protein Evolution, Max-Planck-lnstitute for Developmental Biology, Spemannstrasse 35, D-72076 Tübingen, Germany. manju@tuebingen.mpg.de <manju@tuebingen.mpg.de>|Department of Protein Evolution, Max-Planck-lnstitute for Developmental Biology, Spemannstrasse 35, D-72076 Tübingen, Germany. manju@tuebingen.mpg.de <manju@tuebingen.mpg.de>', 'Germany|Germany|Germany', 133, 'Algorithms|Animals|Computational Biology|Databases, Protein|Humans|Internet|Models, Molecular|Models, Statistical|Programming Languages|Protein Structure, Tertiary|Proteomics|ROC Curve|Software', 'Journal Article', '10.1186/1471-2105-8-2', '17199898', 'Solenoid repeat proteins of the Tetratrico Peptide Repeat (TPR) family are involved as scaffolds in a broad range of protein-protein interactions. Several resources are available for the prediction of TPRs, however, they often fail to detect divergent repeat units.'),
(91245, 2007, 'bmc', 'FLAME, a novel fuzzy clustering method for the analysis of DNA microarray data', 'Fu, Limin|Medico, Enzo', 'Laboratory of Functional Genomics, The Oncogenomics Center, Institute for Cancer Research and Treatment, University of Torino, School of Medicine, 10060 Candiolo, Italy. limin.fu@ircc.it <limin.fu@ircc.it>|Laboratory of Functional Genomics, The Oncogenomics Center, Institute for Cancer Research and Treatment, University of Torino, School of Medicine, 10060 Candiolo, Italy. limin.fu@ircc.it <limin.fu@ircc.it>', 'Italy|Italy', 0, 'Algorithms|Animals|Cluster Analysis|Computational Biology|Databases, Genetic|Genomics|Humans|Hypoxia|Mice|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Programming Languages|Software', 'Journal Article', '10.1186/1471-2105-8-3', '17204155', 'Data clustering analysis has been extensively applied to extract information from gene expression profiles obtained with DNA microarrays. To this aim, existing clustering approaches, mainly developed in computer science, have been adapted to microarray data analysis. However, previous studies revealed that microarray datasets have very diverse structures, some of which may not be correctly captured by current clustering methods. We therefore approached the problem from a new starting point, and developed a clustering algorithm designed to capture dataset-specific structures at the beginning of the process.'),
(91246, 2007, 'bmc', 'VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines', 'Doytchinova, Irini A|Flower, Darren R', 'Faculty of Pharmacy, Medical University of Sofia, 2 Dunav St., 1000 Sofia, Bulgaria. idoytchinova@pharmfac.acad.bg <idoytchinova@pharmfac.acad.bg>|Faculty of Pharmacy, Medical University of Sofia, 2 Dunav St., 1000 Sofia, Bulgaria. idoytchinova@pharmfac.acad.bg <idoytchinova@pharmfac.acad.bg>', 'Bulgaria|Bulgaria', 0, 'Algorithms|Amino Acid Sequence|Antigens, Bacterial|Antigens, Neoplasm|Binding Sites|Molecular Sequence Data|Protein Binding|Protein Subunits|Sequence Analysis, Protein|Software|Vaccines, Subunit', 'Journal Article', '10.1186/1471-2105-8-4', '17207271', 'Vaccine development in the post-genomic era often begins with the in silico screening of genome information, with the most probable protective antigens being predicted rather than requiring causative microorganisms to be grown. Despite the obvious advantages of this approach--such as speed and cost efficiency--its success remains dependent on the accuracy of antigen prediction. Most approaches use sequence alignment to identify antigens. This is problematic for several reasons. Some proteins lack obvious sequence similarity, although they may share similar structures and biological properties. The antigenicity of a sequence may be encoded in a subtle and recondite manner not amendable to direct identification by sequence alignment. The discovery of truly novel antigens will be frustrated by their lack of similarity to antigens of known provenance. To overcome the limitations of alignment-dependent methods, we propose a new alignment-free approach for antigen prediction, which is based on auto cross covariance (ACC) transformation of protein sequences into uniform vectors of principal amino acid properties.'),
(91247, 2007, 'bmc', 'Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering', 'Pal, Nikhil R|Aguan, Kripamoy|Sharma, Animesh|Amari, Shun-ichi', 'Electronics and Communication Sciences Unit, Indian Statistical Institute, India. nikhil@isical.ac.in|Electronics and Communication Sciences Unit, Indian Statistical Institute, India. nikhil@isical.ac.in|Electronics and Communication Sciences Unit, Indian Statistical Institute, India. nikhil@isical.ac.in|Electronics and Communication Sciences Unit, Indian Statistical Institute, India. nikhil@isical.ac.in', 'India|India|India|India', 43, 'Biomarkers, Tumor|Cluster Analysis|Databases, Protein|Diagnosis, Computer-Assisted|Fuzzy Logic|Gene Expression Profiling|Humans|Neoplasm Proteins|Neoplasms|Neural Networks (Computer)|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-8-5', '17207284', 'The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT) and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set.'),
(91248, 2007, 'bmc', 'Phylogenetic tree information aids supervised learning for predicting protein-protein interaction based on distance matrices', 'Craig, Roger A|Liao, Li', 'Department of Computer & Information Sciences, University of Delaware, Newark, DE 19716, USA. rcraig@cis.udel.edu <rcraig@cis.udel.edu>|Department of Computer & Information Sciences, University of Delaware, Newark, DE 19716, USA. rcraig@cis.udel.edu <rcraig@cis.udel.edu>', 'United States|United States', 0, 'Computational Biology|Databases, Protein|Escherichia coli Proteins|Evolution, Molecular|Learning|Normal Distribution|Phylogeny|Predictive Value of Tests|Protein Interaction Mapping|ROC Curve|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-8-6', '17212819', 'Protein-protein interactions are critical for cellular functions. Recently developed computational approaches for predicting protein-protein interactions utilize co-evolutionary information of the interacting partners, e.g., correlations between distance matrices, where each matrix stores the pairwise distances between a protein and its orthologs from a group of reference genomes.'),
(91249, 2007, 'bmc', 'eQTL Viewer: visualizing how sequence variation affects genome-wide transcription', 'Zou, Wei|Aylor, David L|Zeng, Zhao-Bang', 'Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695-7566, USA. wzou@statgen.ncsu.edu <wzou@statgen.ncsu.edu>|Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695-7566, USA. wzou@statgen.ncsu.edu <wzou@statgen.ncsu.edu>|Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695-7566, USA. wzou@statgen.ncsu.edu <wzou@statgen.ncsu.edu>', 'United States|United States|United States', 15, 'Algorithms|Chromosome Mapping|Computer Graphics|Internet|Quantitative Trait Loci|Sequence Analysis, DNA|Software|Transcription, Genetic|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-8-7', '17212828', 'Expression Quantitative Trait Locus (eQTL) mapping methods have been used to identify the genetic basis of gene expression variations. To map eQTL, thousands of expression profiles are related with sequence polymorphisms across the genome through their correlated variations. These eQTL distribute in many chromosomal regions, each of which can include many genes. The large number of mapping results produced makes it difficult to consider simultaneously the relationships between multiple genomic regions and multiple expressional profiles. There is a need for informative bioinformatics tools to assist the visualization and interpretation of these mapping results.'),
(91250, 2007, 'bmc', 'Least-squares methods for identifying biochemical regulatory networks from noisy measurements', 'Kim, Jongrae|Bates, Declan G|Postlethwaite, Ian|Heslop-Harrison, Pat|Cho, Kwang-Hyun', 'Department of Engineering, University of Leicester, Leicester, LE1 7RH, UK. jrk7@le.ac.uk <jrk7@le.ac.uk>|Department of Engineering, University of Leicester, Leicester, LE1 7RH, UK. jrk7@le.ac.uk <jrk7@le.ac.uk>|Department of Engineering, University of Leicester, Leicester, LE1 7RH, UK. jrk7@le.ac.uk <jrk7@le.ac.uk>|Department of Engineering, University of Leicester, Leicester, LE1 7RH, UK. jrk7@le.ac.uk <jrk7@le.ac.uk>|Department of Engineering, University of Leicester, Leicester, LE1 7RH, UK. jrk7@le.ac.uk <jrk7@le.ac.uk>', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 14, 'Algorithms|Biochemistry|Computer Simulation|Data Interpretation, Statistical|Gene Expression Regulation|Least-Squares Analysis|Models, Biological|Models, Statistical|Protein Interaction Mapping|Signal Transduction|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-8-8', '17212835', 'We consider the problem of identifying the dynamic interactions in biochemical networks from noisy experimental data. Typically, approaches for solving this problem make use of an estimation algorithm such as the well-known linear Least-Squares (LS) estimation technique. We demonstrate that when time-series measurements are corrupted by white noise and/or drift noise, more accurate and reliable identification of network interactions can be achieved by employing an estimation algorithm known as Constrained Total Least Squares (CTLS). The Total Least Squares (TLS) technique is a generalised least squares method to solve an overdetermined set of equations whose coefficients are noisy. The CTLS is a natural extension of TLS to the case where the noise components of the coefficients are correlated, as is usually the case with time-series measurements of concentrations and expression profiles in gene networks.');
