INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(89995, 2002, 'bmc', 'The limit fold change model: a practical approach for selecting differentially expressed genes from microarray data', 'Mutch, David M|Berger, Alvin|Mansourian, Robert|Rytz, Andreas|Roberts, Matthew-Alan', 'Metabolic and Genomic Regulation, Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland. david.mutch@rdls.nestle.com|Metabolic and Genomic Regulation, Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland. david.mutch@rdls.nestle.com|Metabolic and Genomic Regulation, Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland. david.mutch@rdls.nestle.com|Metabolic and Genomic Regulation, Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland. david.mutch@rdls.nestle.com|Metabolic and Genomic Regulation, Nestlé Research Center, Vers-chez-les-Blanc, CH-1000 Lausanne 26, Switzerland. david.mutch@rdls.nestle.com', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Animals|Computational Biology|Diet|Gene Expression Profiling|Genes|Genetic Variation|Liver|Male|Mice|Mice, Inbred Strains|Models, Genetic|Oligonucleotide Array Sequence Analysis|Organ Specificity|RNA, Complementary|Reverse Transcriptase Polymerase Chain Reaction', 'Journal Article', '10.1186/1471-2105-1-1', '12095422', 'The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic and global mathematical approaches that can be readily applied to a large number of experimental designs become fundamental to correctly handle the otherwise overwhelming data sets.'),
(89996, 2002, 'bmc', 'Visualizing the genome: techniques for presenting human genome data and annotations', 'Loraine, Ann E|Helt, Gregg A', 'Bioinformatics Department, Affymetrix, Inc, 6550 Vallejo Street, Ste 100, Emeryville, CA 94608, USA. ann_loraine@affymetrix.com|Bioinformatics Department, Affymetrix, Inc, 6550 Vallejo Street, Ste 100, Emeryville, CA 94608, USA. ann_loraine@affymetrix.com', 'United States|United States', 198, 'Alternative Splicing|Base Sequence|Chromosome Mapping|Computational Biology|Computer Graphics|Database Management Systems|Databases, Genetic|Exons|Genes|Genome, Human|Human Genome Project|Humans|Introns|Protein Isoforms|Proteins|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-1-1', '12149135', 'In order to take full advantage of the newly available public human genome sequence data and associated annotations, biologists require visualization tools (genome browsers) that can accommodate the high frequency of alternative splicing in human genes and other complexities.'),
(89997, 2002, 'bmc', 'Kangaroo--a pattern-matching program for biological sequences', 'Betel, Doron|Hogue, Christopher W V', 'Department of Biochemistry, University of Toronto, Toronto, Ontario, M5S 1A8, Canada. betel@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, M5S 1A8, Canada. betel@mshri.on.ca', 'Canada|Canada', 0, 'Base Pair Mismatch|Computational Biology|DNA Repair|Databases, Genetic|Gene Expression Profiling|Humans|Internet|Mutation|Sequence Alignment|Short Interspersed Nucleotide Elements|Software', 'Journal Article', '10.1186/1471-2105-1-1', '12150718', 'Biologists are often interested in performing a simple database search to identify proteins or genes that contain a well-defined sequence pattern. Many databases do not provide straightforward or readily available query tools to perform simple searches, such as identifying transcription binding sites, protein motifs, or repetitive DNA sequences. However, in many cases simple pattern-matching searches can reveal a wealth of information. We present in this paper a regular expression pattern-matching tool that was used to identify short repetitive DNA sequences in human coding regions for the purpose of identifying potential mutation sites in mismatch repair deficient cells.'),
(89998, 2002, 'bmc', 'The SGS3 protein involved in PTGS finds a family', 'Bateman, Alex', 'The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. agb@sanger.ac.uk', 'United Kingdom', 0, 'Amino Acid Sequence|Arabidopsis Proteins|Computational Biology|Molecular Sequence Data|Multigene Family|Peptides|Protein Structure, Tertiary|RNA Interference|RNA Processing, Post-Transcriptional|RNA, Plant|Sequence Alignment|Sequence Homology, Amino Acid', 'Comparative Study', '10.1186/1471-2105-1-1', '12162795', 'Post transcriptional gene silencing (PTGS) is a recently discovered phenomenon that is an area of intense research interest. Components of the PTGS machinery are being discovered by genetic and bioinformatics approaches, but the picture is not yet complete.'),
(89999, 2002, 'bmc', 'Microarray results: how accurate are they?', 'Kothapalli, Ravi|Yoder, Sean J|Mane, Shrikant|Loughran, Thomas P', 'Hematologic Malignancies, Molecular Oncology and Clinical Investigations Programs, Department of Interdisciplinary Oncology Program, H, Lee Moffitt Cancer Center and Research Institute. kothapar@moffitt.usf.edu|Hematologic Malignancies, Molecular Oncology and Clinical Investigations Programs, Department of Interdisciplinary Oncology Program, H, Lee Moffitt Cancer Center and Research Institute. kothapar@moffitt.usf.edu|Hematologic Malignancies, Molecular Oncology and Clinical Investigations Programs, Department of Interdisciplinary Oncology Program, H, Lee Moffitt Cancer Center and Research Institute. kothapar@moffitt.usf.edu|Hematologic Malignancies, Molecular Oncology and Clinical Investigations Programs, Department of Interdisciplinary Oncology Program, H, Lee Moffitt Cancer Center and Research Institute. kothapar@moffitt.usf.edu', 'Mali|Mali|Mali|Mali', 198, 'Alleles|Cells, Cultured|Computational Biology|DNA, Complementary|Gene Expression Profiling|Gene Expression Regulation, Enzymologic|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Granzymes|Humans|Leukemia, Lymphoid|Leukocytes, Mononuclear|Oligonucleotide Array Sequence Analysis|RNA, Messenger|RNA, Neoplasm|Reproducibility of Results|Sensitivity and Specificity|Serine Endopeptidases', 'Comparative Study', '10.1186/1471-2105-1-1', '12194703', 'DNA microarray technology is a powerful technique that was recently developed in order to analyze thousands of genes in a short time. Presently, microarrays, or chips, of the cDNA type and oligonucleotide type are available from several sources. The number of publications in this area is increasing exponentially.'),
(90000, 2002, 'bmc', 'Computational method for reducing variance with Affymetrix microarrays', 'Welle, Stephen|Brooks, Andrew I|Thornton, Charles A', 'Department of Medicine, University of Rochester, Rochester, NY 14642, USA. stephen_welle@urmc.rochester.edu|Department of Medicine, University of Rochester, Rochester, NY 14642, USA. stephen_welle@urmc.rochester.edu|Department of Medicine, University of Rochester, Rochester, NY 14642, USA. stephen_welle@urmc.rochester.edu', 'United States|United States|United States', 198, 'Adult|Aged|Algorithms|Analysis of Variance|Computational Biology|Gene Expression Profiling|Humans|Male|Middle Aged|Muscle, Skeletal|Oligonucleotide Array Sequence Analysis|RNA Probes|RNA, Messenger|Thigh', 'Comparative Study', '10.1186/1471-2105-1-1', '12204100', 'Affymetrix microarrays are used by many laboratories to generate gene expression profiles. Generally, only large differences (> 1.7-fold) between conditions have been reported. Computational methods to reduce inter-array variability might be of value when attempting to detect smaller differences. We examined whether inter-array variability could be reduced by using data based on the Affymetrix algorithm for pairwise comparisons between arrays (ratio method) rather than data based on the algorithm for analysis of individual arrays (signal method). Six HG-U95A arrays that probed mRNA from young (21-31 yr old) human muscle were compared with six arrays that probed mRNA from older (62-77 yr old) muscle.'),
(90001, 2002, 'bmc', 'The functional importance of disease-associated mutation', 'Mooney, Sean D|Klein, Teri E', 'Department of Genetics and Stanford Medical Informatics Division, Stanford University, Stanford, California, 94305, USA. mooney@smi.stanford.edu|Department of Genetics and Stanford Medical Informatics Division, Stanford University, Stanford, California, 94305, USA. mooney@smi.stanford.edu', 'United States|United States', 198, 'Computational Biology|Conserved Sequence|Genetic Diseases, Inborn|Humans|Mutation|Sequence Alignment|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-1-1', '12220483', 'For many years, scientists believed that point mutations in genes are the genetic switches for somatic and inherited diseases such as cystic fibrosis, phenylketonuria and cancer. Some of these mutations likely alter a proteins function in a manner that is deleterious, and they should occur in functionally important regions of the protein products of genes. Here we show that disease-associated mutations occur in regions of genes that are conserved, and can identify likely disease-causing mutations.'),
(90002, 2002, 'bmc', 'Prediction of MHC class I binding peptides, using SVMHC', 'Dönnes, Pierre|Elofsson, Arne', 'Center for Bioinformatics Saar, Saarland University, D-660 41 Saarbrücken, Germany. pierre@bioinf.uni-sb.de|Center for Bioinformatics Saar, Saarland University, D-660 41 Saarbrücken, Germany. pierre@bioinf.uni-sb.de', 'Germany|Germany', 0, 'Animals|Artificial Intelligence|Computational Biology|Databases, Protein|Epitopes, T-Lymphocyte|HLA Antigens|Histocompatibility Antigens Class I|Humans|Peptides|Predictive Value of Tests|Protein Binding|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-1-1', '12225620', 'T-cells are key players in regulating a specific immune response. Activation of cytotoxic T-cells requires recognition of specific peptides bound to Major Histocompatibility Complex (MHC) class I molecules. MHC-peptide complexes are potential tools for diagnosis and treatment of pathogens and cancer, as well as for the development of peptide vaccines. Only one in 100 to 200 potential binders actually binds to a certain MHC molecule, therefore a good prediction method for MHC class I binding peptides can reduce the number of candidate binders that need to be synthesized and tested.'),
(90003, 2002, 'bmc', 'Expression profiling of human renal carcinomas with functional taxonomic analysis', 'Gieseg, Michael A|Cody, Theresa|Man, Michael Z|Madore, Steven J|Rubin, Mark A|Kaldjian, Eric P', 'Pfizer Global Research & Development, 2800 Plymouth Rd, Ann Arbor, Michigan 48105, USA. Michael.Gieseg@pfizer.com|Pfizer Global Research & Development, 2800 Plymouth Rd, Ann Arbor, Michigan 48105, USA. Michael.Gieseg@pfizer.com|Pfizer Global Research & Development, 2800 Plymouth Rd, Ann Arbor, Michigan 48105, USA. Michael.Gieseg@pfizer.com|Pfizer Global Research & Development, 2800 Plymouth Rd, Ann Arbor, Michigan 48105, USA. Michael.Gieseg@pfizer.com|Pfizer Global Research & Development, 2800 Plymouth Rd, Ann Arbor, Michigan 48105, USA. Michael.Gieseg@pfizer.com|Pfizer Global Research & Development, 2800 Plymouth Rd, Ann Arbor, Michigan 48105, USA. Michael.Gieseg@pfizer.com', 'United States|United States|United States|United States|United States|United States', 0, 'Adenocarcinoma, Clear Cell|Algorithms|Carcinoma, Renal Cell|Cell Adhesion|Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Kidney Neoplasms|Oligonucleotide Array Sequence Analysis|Organ Specificity|Pilot Projects|RNA Probes|RNA, Messenger|Signal Transduction', 'Journal Article', '10.1186/1471-2105-1-1', '12356337', 'Molecular characterization has contributed to the understanding of the inception, progression, treatment and prognosis of cancer. Nucleic acid array-based technologies extend molecular characterization of tumors to thousands of gene products. To effectively discriminate between tumor sub-types, reliable laboratory techniques and analytic methods are required.'),
(90004, 2002, 'bmc', 'Oliz, a suite of Perl scripts that assist in the design of microarrays using 50mer oligonucleotides from the 3 untranslated region', 'Chen, Hao|Sharp, Burt M', 'Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA. hchen@utmem.edu|Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN 38163, USA. hchen@utmem.edu', 'United States|United States', 198, '3 Untranslated Regions|Animals|Brain Chemistry|Computational Biology|Contig Mapping|Databases, Genetic|Gene Expression Profiling|Multigene Family|Oligonucleotide Probes|Oligonucleotides|Programming Languages|RNA, Messenger|Rats|Software', 'Journal Article', '10.1186/1471-2105-1-1', '12366869', 'Identifying reliable oligonucleotide sequences for use in microarray experiments is a complex process. Two key issues are the accuracy of the input sequences and the specificity of the oligonucleotide sequences.'),
(90005, 2002, 'bmc', 'Efficient Boolean implementation of universal sequence maps (bUSM)', 'Schwacke, John|Almeida, Jonas S', 'Department of Biometry and Epidemiology, Medical University of South Carolina, 135 Cannon Street, Suite 303, PO Box 250835, Charleston, SC 29425, USA. schwacke@musc.edu|Department of Biometry and Epidemiology, Medical University of South Carolina, 135 Cannon Street, Suite 303, PO Box 250835, Charleston, SC 29425, USA. schwacke@musc.edu', 'United States|United States', 198, 'Algorithms|Computational Biology|Logic|Nonlinear Dynamics|Programming Languages|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-1-1', '12387731', 'Recently, Almeida and Vinga offered a new approach for the representation of arbitrary discrete sequences, referred to as Universal Sequence Maps (USM), and discussed its applicability to genomic sequence analysis. Their work generalizes and extends Chaos Game Representation (CGR) of DNA for arbitrary discrete sequences.'),
(90006, 2002, 'bmc', 'Simulation of DNA array hybridization experiments and evaluation of critical parameters during subsequent image and data analysis', 'Wierling, Christoph K|Steinfath, Matthias|Elge, Thorsten|Schulze-Kremer, Steffen|Aanstad, Pia|Clark, Matthew|Lehrach, Hans|Herwig, Ralf', 'Department of Vertebrate Genomics, Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, D-14195 Berlin-Dahlem, Germany. wierling@molgen.mpg.de|Department of Vertebrate Genomics, Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, D-14195 Berlin-Dahlem, Germany. wierling@molgen.mpg.de|Department of Vertebrate Genomics, Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, D-14195 Berlin-Dahlem, Germany. wierling@molgen.mpg.de|Department of Vertebrate Genomics, Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, D-14195 Berlin-Dahlem, Germany. wierling@molgen.mpg.de|Department of Vertebrate Genomics, Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, D-14195 Berlin-Dahlem, Germany. wierling@molgen.mpg.de|Department of Vertebrate Genomics, Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, D-14195 Berlin-Dahlem, Germany. wierling@molgen.mpg.de|Department of Vertebrate Genomics, Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, D-14195 Berlin-Dahlem, Germany. wierling@molgen.mpg.de|Department of Vertebrate Genomics, Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, D-14195 Berlin-Dahlem, Germany. wierling@molgen.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Arabidopsis|Computational Biology|Computer Simulation|DNA, Complementary|DNA, Plant|Gene Expression Profiling|Genome, Plant|Models, Genetic|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Research Design', 'Evaluation Studies', '10.1186/1471-2105-1-1', '12390683', 'Gene expression analyses based on complex hybridization measurements have increased rapidly in recent years and have given rise to a huge amount of bioinformatic tools such as image analyses and cluster analyses. However, the amount of work done to integrate and evaluate these tools and the corresponding experimental procedures is not high. Although complex hybridization experiments are based on a data production pipeline that incorporates a significant amount of error parameters, the evaluation of these parameters has not been studied yet in sufficient detail.'),
(90007, 2002, 'bmc', 'Making sense of EST sequences by CLOBBing them', 'Parkinson, John|Guiliano, David B|Blaxter, Mark', 'Institute of Cell, Animal and Population Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. john.parkinson@ed.ac.uk|Institute of Cell, Animal and Population Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. john.parkinson@ed.ac.uk|Institute of Cell, Animal and Population Biology, University of Edinburgh, Edinburgh EH9 3JT, UK. john.parkinson@ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 198, 'Algorithms|Animals|Base Sequence|Benchmarking|Caenorhabditis elegans|Cluster Analysis|Computational Biology|Expressed Sequence Tags|Humans|Programming Languages|Sequence Alignment|Software|Zebrafish', 'Comparative Study', '10.1186/1471-2105-1-1', '12398795', 'Expressed sequence tags (ESTs) are single pass reads from randomly selected cDNA clones. They provide a highly cost-effective method to access and identify expressed genes. However, they are often prone to sequencing errors and typically define incomplete transcripts. To increase the amount of information obtainable from ESTs and reduce sequencing errors, it is necessary to cluster ESTs into groups sharing significant sequence similarity.'),
(90008, 2002, 'bmc', 'Computational detection of genomic cis-regulatory modules applied to body patterning in the early Drosophila embryo', 'Rajewsky, Nikolaus|Vergassola, Massimo|Gaul, Ulrike|Siggia, Eric D', 'Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY, USA. nr@edsb.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY, USA. nr@edsb.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY, USA. nr@edsb.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY, USA. nr@edsb.rockefeller.edu', 'United States|United States|United States|United States', 198, 'Algorithms|Amino Acid Motifs|Animals|Binding Sites|Body Patterning|Chromosome Mapping|Computational Biology|Consensus Sequence|Drosophila Proteins|Drosophila melanogaster|Gene Expression Regulation, Developmental|Genomics|Software|Trans-Activators|Transcription, Genetic', 'Comparative Study', '10.1186/1471-2105-1-1', '12398796', 'Regulation of gene transcription is crucial for the function and development of all organisms. While gene prediction programs that identify protein coding sequence are used with remarkable success in the annotation of genomes, the development of computational methods to analyze noncoding regions and to delineate transcriptional control elements is still in its infancy.'),
(90009, 2002, 'bmc', 'SeqHound: biological sequence and structure database as a platform for bioinformatics research', 'Michalickova, Katerina|Bader, Gary D|Dumontier, Michel|Lieu, Hao|Betel, Doron|Isserlin, Ruth|Hogue, Christopher W V', 'Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8. katerina@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8. katerina@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8. katerina@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8. katerina@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8. katerina@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8. katerina@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8. katerina@mshri.on.ca', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Amino Acid Sequence|Base Sequence|Computational Biology|Databases, Genetic|Information Storage and Retrieval|Internet|Models, Genetic|Models, Molecular|Molecular Sequence Data|Software|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-1-1', '12401134', 'SeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platform for bioinformatics research in a locally-hosted environment.'),
(90010, 2002, 'bmc', 'Automated modelling of signal transduction networks', 'Steffen, Martin|Petti, Allegra|Aach, John|Dhaeseleer, Patrik|Church, George', 'Dept of Genetics, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts, 02115, USA. steffen@rascal.med.harvard.edu|Dept of Genetics, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts, 02115, USA. steffen@rascal.med.harvard.edu|Dept of Genetics, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts, 02115, USA. steffen@rascal.med.harvard.edu|Dept of Genetics, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts, 02115, USA. steffen@rascal.med.harvard.edu|Dept of Genetics, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts, 02115, USA. steffen@rascal.med.harvard.edu', 'United States|United States|United States|United States|United States', 198, 'Computational Biology|MAP Kinase Signaling System|Models, Genetic|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1186/1471-2105-1-1', '12413400', 'Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ultimately effect transcriptional changes. Understanding the mechanisms cells use to accomplish this important process requires a detailed molecular description of the networks involved.'),
(90011, 2002, 'bmc', 'FunSpec: a web-based cluster interpreter for yeast', 'Robinson, Mark D|Grigull, Jörg|Mohammad, Naveed|Hughes, Timothy R', 'Banting and Best Department of Medical Research, University of Toronto, Toronto, Canada. m.robinson@utoronto.ca|Banting and Best Department of Medical Research, University of Toronto, Toronto, Canada. m.robinson@utoronto.ca|Banting and Best Department of Medical Research, University of Toronto, Toronto, Canada. m.robinson@utoronto.ca|Banting and Best Department of Medical Research, University of Toronto, Toronto, Canada. m.robinson@utoronto.ca', 'Canada|Canada|Canada|Canada', 0, 'Cluster Analysis|Computational Biology|Databases, Genetic|Databases, Protein|Fungal Proteins|Genes, Fungal|Internet|Multigene Family|Software', 'Journal Article', '10.1186/1471-2105-1-1', '12431279', 'For effective exposition of biological information, especially with regard to analysis of large-scale data types, researchers need immediate access to multiple categorical knowledge bases and need summary information presented to them on collections of genes, as opposed to the typical one gene at a time.'),
(90012, 2002, 'bmc', 'Total sequence decomposition distinguishes functional modules, molegos in apurinic/apyrimidinic endonucleases', 'Schein, Catherine H|Ozgün, Numan|Izumi, Tadahide|Braun, Werner', 'Sealy Center for Structural Biology, Department of Human Biological Chemistry and Genetics, University of Texas Medical Branch, Galveston TX 77555-1157, USA. cathy@newton.utmb.edu|Sealy Center for Structural Biology, Department of Human Biological Chemistry and Genetics, University of Texas Medical Branch, Galveston TX 77555-1157, USA. cathy@newton.utmb.edu|Sealy Center for Structural Biology, Department of Human Biological Chemistry and Genetics, University of Texas Medical Branch, Galveston TX 77555-1157, USA. cathy@newton.utmb.edu|Sealy Center for Structural Biology, Department of Human Biological Chemistry and Genetics, University of Texas Medical Branch, Galveston TX 77555-1157, USA. cathy@newton.utmb.edu', 'United States|United States|United States|United States', 0, 'Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Conserved Sequence|DNA-(Apurinic or Apyrimidinic Site) Lyase|Deoxyribonuclease I|Humans|Models, Molecular|Molecular Sequence Data|Nerve Tissue Proteins|Phosphoric Monoester Hydrolases|Protein Structure, Tertiary|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-1-1', '12445335', 'Total sequence decomposition, using the web-based MASIA tool, identifies areas of conservation in aligned protein sequences. By structurally annotating these motifs, the sequence can be parsed into individual building blocks, molecular legos (molegos), that can eventually be related to function. Here, the approach is applied to the apurinic/apyrimidinic endonuclease (APE) DNA repair proteins, essential enzymes that have been highly conserved throughout evolution. The APEs, DNase-1 and inositol 5-polyphosphate phosphatases (IPP) form a superfamily that catalyze metal ion based phosphorolysis, but recognize different substrates.'),
(90013, 2002, 'bmc', 'Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study', 'Wang, Junbai|Delabie, Jan|Aasheim, Hans|Smeland, Erlend|Myklebost, Ola', 'Department of Tumor Biology, Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no', 'Norway|Norway|Norway|Norway|Norway', 198, 'Cluster Analysis|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genome, Human|Humans|Internet|Leukemia, Lymphocytic, Chronic, B-Cell|Lymphoma|Lymphoma, B-Cell|Lymphoma, Follicular|Lymphoma, Large B-Cell, Diffuse|Lymphoma, Non-Hodgkin|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-1-1', '12445336', 'A method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expression. Because of the complexity and the high dimensionality of microarray gene expression profiles, the dimensional reduction of raw expression data and the feature selections necessary for, for example, classification of disease samples remains a challenge. To solve the problem we propose a two-level analysis. First self-organizing map (SOM) is used. SOM is a vector quantization method that simplifies and reduces the dimensionality of original measurements and visualizes individual tumor sample in a SOM component plane. Next, hierarchical clustering and K-means clustering is used to identify patterns of gene expression useful for classification of samples.'),
(90014, 2002, 'bmc', 'Development and production of an oligonucleotide MuscleChip: use for validation of ambiguous ESTs', 'Borup, Rehannah H A|Toppo, Stefano|Chen, Yi-Wen|Teslovich, Tanya M|Lanfranchi, Gerolamo|Valle, Giorgio|Hoffman, Eric P', 'Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue N.W., Washington, DC 20010, USA. rborup@cnmcresearch.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue N.W., Washington, DC 20010, USA. rborup@cnmcresearch.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue N.W., Washington, DC 20010, USA. rborup@cnmcresearch.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue N.W., Washington, DC 20010, USA. rborup@cnmcresearch.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue N.W., Washington, DC 20010, USA. rborup@cnmcresearch.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue N.W., Washington, DC 20010, USA. rborup@cnmcresearch.org|Research Center for Genetic Medicine, Childrens National Medical Center, 111 Michigan Avenue N.W., Washington, DC 20010, USA. rborup@cnmcresearch.org', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Computational Biology|Databases, Genetic|Expressed Sequence Tags|Gene Library|Genome, Human|Humans|Kinetics|Muscles|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Oligonucleotides|RNA, Complementary|Software|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-1-1', '12456269', 'We describe the development, validation, and use of a highly redundant 120,000 oligonucleotide microarray (MuscleChip) containing 4,601 probe sets representing 1,150 known genes expressed in muscle and 2,075 EST clusters from a non-normalized subtracted muscle EST sequencing project (28,074 EST sequences). This set included 369 novel EST clusters showing no match to previously characterized proteins in any database. Each probe set was designed to contain 20-32 25 mer oligonucleotides (10-16 paired perfect match and mismatch probe pairs per gene), with each probe evaluated for hybridization kinetics (Tm) and similarity to other sequences. The 120,000 oligonucleotides were synthesized by photolithography and light-activated chemistry on each microarray.'),
(90015, 2002, 'bmc', 'Quantifying robustness of biochemical network models', 'Ma, Lan|Iglesias, Pablo A', 'Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD USA. lma@jhu.edu|Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD USA. lma@jhu.edu', 'United States|United States', 198, 'Biochemical Phenomena|Computational Biology|Cyclic AMP|Models, Biological|Nonlinear Dynamics', 'Comparative Study', '10.1186/1471-2105-1-1', '12482327', 'Robustness of mathematical models of biochemical networks is important for validation purposes and can be used as a means of selecting between different competing models. Tools for quantifying parametric robustness are needed.'),
(90016, 2002, 'bmc', 'Species-specific protein sequence and fold optimizations', 'Dumontier, Michel|Michalickova, Katerina|Hogue, Christopher W V', 'Department of Biochemistry, University of Toronto, Toronto, Ontario, M5S 1A8, Canada. micheld@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, M5S 1A8, Canada. micheld@mshri.on.ca|Department of Biochemistry, University of Toronto, Toronto, Ontario, M5S 1A8, Canada. micheld@mshri.on.ca', 'Canada|Canada|Canada', 0, 'Adaptation, Physiological|Animals|Archaeal Proteins|Bacterial Proteins|Caenorhabditis elegans Proteins|Computational Biology|Fungal Proteins|Genome|Genome, Archaeal|Genome, Bacterial|Genome, Fungal|Genome, Human|Humans|Predictive Value of Tests|Protein Folding|Protein Structure, Secondary|Proteins|Proteome|Proteomics|Species Specificity', 'Comparative Study', '10.1186/1471-2105-1-1', '12487631', 'An organisms ability to adapt to its particular environmental niche is of fundamental importance to its survival and proliferation. In the largest study of its kind, we sought to identify and exploit the amino-acid signatures that make species-specific protein adaptation possible across 100 complete genomes.'),
(90017, 2002, 'bmc', 'ORFer--retrieval of protein sequences and open reading frames from GenBank and storage into relational databases or text files', 'Büssow, Konrad|Hoffmann, Steve|Sievert, Volker', 'Protein Structure Factory, Max Planck Institute of Molecular Genetics, Heubnerweg 6, 14059 Berlin, Germany. buessow@molgen.mpg.de|Protein Structure Factory, Max Planck Institute of Molecular Genetics, Heubnerweg 6, 14059 Berlin, Germany. buessow@molgen.mpg.de|Protein Structure Factory, Max Planck Institute of Molecular Genetics, Heubnerweg 6, 14059 Berlin, Germany. buessow@molgen.mpg.de', 'Germany|Germany|Germany', 0, 'Animals|Anopheles|Bacillus subtilis|Bacterial Proteins|Cytomegalovirus|Databases, Genetic|Databases, Nucleic Acid|Databases, Protein|Genome|Genome, Bacterial|Genomics|Humans|Information Storage and Retrieval|Insect Proteins|Open Reading Frames|Programming Languages|Protein Structure, Secondary|Proteome|Software|Software Design|Species Specificity|Terminology as Topic|Viral Proteins', 'Journal Article', '10.1186/1471-2105-1-1', '12493080', 'Functional genomics involves the parallel experimentation with large sets of proteins. This requires management of large sets of open reading frames as a prerequisite of the cloning and recombinant expression of these proteins.'),
(90018, 2003, 'bmc', 'SeqVISTA: a graphical tool for sequence feature visualization and comparison', 'Hu, Zhenjun|Frith, Martin|Niu, Tianhua|Weng, Zhiping', 'Bioinformatics Program, Boston University, Boston, MA, 02215, USA. zjhu@bu.edu|Bioinformatics Program, Boston University, Boston, MA, 02215, USA. zjhu@bu.edu|Bioinformatics Program, Boston University, Boston, MA, 02215, USA. zjhu@bu.edu|Bioinformatics Program, Boston University, Boston, MA, 02215, USA. zjhu@bu.edu', 'United States|United States|United States|United States', 198, 'Amino Acid Sequence|Base Sequence|Computational Biology|Computer Graphics|Databases, Nucleic Acid|Genome, Viral|Humans|Molecular Sequence Data|Sequence Alignment|Simian virus 40|Software|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-1-1', '12513700', 'Many readers will sympathize with the following story. You are viewing a gene sequence in Entrez, and you want to find whether it contains a particular sequence motif. You reach for the browsers find in page button, but those darn spaces every 10 bp get in the way. And what if the motif is on the opposite strand? Subsequently, your favorite sequence analysis software informs you that there is an interesting feature at position 13982-14013. By painstakingly counting the 10 bp blocks, you are able to examine the sequence at this location. But now you want to see what other features have been annotated close by, and this information is buried several screenfuls higher up the web page.'),
(90019, 2003, 'bmc', 'An automated method for finding molecular complexes in large protein interaction networks', 'Bader, Gary D|Hogue, Christopher W V', 'Samuel Lunenfeld Research Institute, Mt, Sinai Hospital, Toronto ON Canada M5G 1X5, Dept, of Biochemistry, University of Toronto, Toronto ON Canada M5S 1A8. gary.bader@utoronto.ca|Samuel Lunenfeld Research Institute, Mt, Sinai Hospital, Toronto ON Canada M5G 1X5, Dept, of Biochemistry, University of Toronto, Toronto ON Canada M5S 1A8. gary.bader@utoronto.ca', 'Canada|Canada', 0, 'Algorithms|Cluster Analysis|Computational Biology|Computer Graphics|Macromolecular Substances|Predictive Value of Tests|Protein Interaction Mapping|Proteomics|Saccharomyces cerevisiae Proteins|Software Validation', 'Evaluation Studies', '10.1186/1471-2105-1-1', '12525261', 'Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery.'),
(90020, 2003, 'bmc', 'Optimal step length EM algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping', 'Zhang, Peisen|Sheng, Huitao|Morabia, Alfredo|Gilliam, T Conrad', 'Columbia Genome Center, Columbia University, New York NY 10032, USA. pz6@columbia.edu|Columbia Genome Center, Columbia University, New York NY 10032, USA. pz6@columbia.edu|Columbia Genome Center, Columbia University, New York NY 10032, USA. pz6@columbia.edu|Columbia Genome Center, Columbia University, New York NY 10032, USA. pz6@columbia.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Arteriosclerosis|Case-Control Studies|Computational Biology|Gene Frequency|Genotype|Haplotypes|Humans|Lipoprotein Lipase|Polymorphism, Single Nucleotide', 'Comparative Study', '10.1186/1471-2105-1-1', '12529185', 'Haplotype based linkage disequilibrium (LD) mapping has become a powerful and cost-effective method for performing genetic association studies, particularly in the search for genetic markers in linkage disequilibrium with complex disease loci. Various methods (e.g. Monte-Carlo (Gibbs sampling), EM (expectation maximization), and Clarks method) have been used to estimate haplotype frequencies from routine genotyping data.'),
(90021, 2003, 'bmc', 'Computer aided analysis of additional chromosome aberrations in Philadelphia chromosome positive acute lymphoblastic leukaemia using a simplified computer readable cytogenetic notation', 'Bradtke, Jutta|Balz, Harald|Fonatsch, Christa|Heinze, Barbara|Jauch, Anna|Mohr, Brigitte|Schoch, Claudia|Rieder, Harald', 'Institute of Clinical Genetics, Philipps-University, Bahnhofstrabetae 7, Marburg, 35037, Germany. bradtke@mailer.uni-marburg.de|Institute of Clinical Genetics, Philipps-University, Bahnhofstrabetae 7, Marburg, 35037, Germany. bradtke@mailer.uni-marburg.de|Institute of Clinical Genetics, Philipps-University, Bahnhofstrabetae 7, Marburg, 35037, Germany. bradtke@mailer.uni-marburg.de|Institute of Clinical Genetics, Philipps-University, Bahnhofstrabetae 7, Marburg, 35037, Germany. bradtke@mailer.uni-marburg.de|Institute of Clinical Genetics, Philipps-University, Bahnhofstrabetae 7, Marburg, 35037, Germany. bradtke@mailer.uni-marburg.de|Institute of Clinical Genetics, Philipps-University, Bahnhofstrabetae 7, Marburg, 35037, Germany. bradtke@mailer.uni-marburg.de|Institute of Clinical Genetics, Philipps-University, Bahnhofstrabetae 7, Marburg, 35037, Germany. bradtke@mailer.uni-marburg.de|Institute of Clinical Genetics, Philipps-University, Bahnhofstrabetae 7, Marburg, 35037, Germany. bradtke@mailer.uni-marburg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Adolescent|Adult|Aged|Chromosome Aberrations|Chromosome Deletion|Chromosomes, Human, Pair 22|Computer Graphics|Cytogenetics|Databases, Factual|Female|Gene Amplification|Humans|Image Interpretation, Computer-Assisted|Isochromosomes|Karyotyping|Male|Middle Aged|Philadelphia Chromosome|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Translocation, Genetic', 'Journal Article', '10.1186/1471-2105-1-1', '12549981', 'The analysis of complex cytogenetic databases of distinct leukaemia entities may help to detect rare recurring chromosome aberrations, minimal common regions of gains and losses, and also hot spots of genomic rearrangements. The patterns of the karyotype alterations may provide insights into the genetic pathways of disease progression.'),
(90022, 2003, 'bmc', 'Genomic data sampling and its effect on classification performance assessment', 'Azuaje, Francisco', 'School of Computing and Mathematics, University of Ulster, Jordanstown, Nothern Ireland, UK. fj.azuaje@ulster.ac.uk', 'Ireland', 0, 'Computational Biology|Data Collection|Entropy|Exons|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genomics|Humans|Introns|Neoplasms|Neural Networks (Computer)|Predictive Value of Tests|RNA Splice Sites|Sampling Studies', 'Journal Article', '10.1186/1471-2105-1-1', '12553886', 'Supervised classification is fundamental in bioinformatics. Machine learning models, such as neural networks, have been applied to discover genes and expression patterns. This process is achieved by implementing training and test phases. In the training phase, a set of cases and their respective labels are used to build a classifier. During testing, the classifier is used to predict new cases. One approach to assessing its predictive quality is to estimate its accuracy during the test phase. Key limitations appear when dealing with small-data samples. This paper investigates the effect of data sampling techniques on the assessment of neural network classifiers.'),
(90023, 2003, 'bmc', 'A format for databasing and comparison of AFLP fingerprint profiles', 'Hong, Yan|Chuah, Aaron', 'Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore 117604. hongy@tll.org.sg|Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore 117604. hongy@tll.org.sg', 'Singapore|Singapore', 198, 'Algorithms|DNA Fingerprinting|Databases, Genetic|Orchidaceae|Polymorphism, Restriction Fragment Length|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-1-1', '12600280', 'Amplified fragment length polymorphism (AFLP) is a PCR-based technique that involves restriction of genomic DNA followed by ligation of adaptors to the fragments generated and selective PCR amplification of a subset of these fragments. The amplified fragments are separated on a sequencing gel and visualized by autoradiography or fluorescent sequencing equipment. AFLP allows high-resolution genotyping but the lack of a format for databasing and comparison of AFLP fingerprint profiles limits its wider applications in profiling large numbers of biological samples.'),
(90024, 2003, 'bmc', 'Modeling gene expression measurement error: a quasi-likelihood approach', 'Strimmer, Korbinian', 'Department of Statistics, University of Munich, Ludwigstrasse 33, D-80539 Munich, Germany. strimmer@stat.uni-muenchen.de', 'Germany', 0, 'Calibration|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Neoplastic|Humans|Leukemia|Likelihood Functions|Models, Genetic|Models, Statistical|Research Design', 'Journal Article', '10.1186/1471-2105-1-1', '12659637', 'Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution) or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale).'),
(90025, 2003, 'bmc', 'Characterization of the cofactor-binding site in the SPOUT-fold methyltransferases by computational docking of S-adenosylmethionine to three crystal structures', 'Kurowski, Michal A|Sasin, Joanna M|Feder, Marcin|Debski, Janusz|Bujnicki, Janusz M', 'Bioinformatics Laboratory, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland. michal@genesilico.pl|Bioinformatics Laboratory, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland. michal@genesilico.pl|Bioinformatics Laboratory, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland. michal@genesilico.pl|Bioinformatics Laboratory, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland. michal@genesilico.pl|Bioinformatics Laboratory, International Institute of Molecular and Cell Biology, Trojdena 4, 02-109 Warsaw, Poland. michal@genesilico.pl', 'Poland|Poland|Poland|Poland|Poland', 0, 'Binding Sites|Catalytic Domain|Coenzymes|Computational Biology|Computer Simulation|Crystallography, X-Ray|Protein Conformation|Protein Folding|S-Adenosylmethionine|Structure-Activity Relationship|tRNA Methyltransferases', 'Comparative Study', '10.1186/1471-2105-1-1', '12689347', 'There are several evolutionarily unrelated and structurally dissimilar superfamilies of S-adenosylmethionine (AdoMet)-dependent methyltransferases (MTases). A new superfamily (SPOUT) has been recently characterized on a sequence level and three structures of its members (1gz0, 1ipa, and 1k3r) have been solved. However, none of these structures include the cofactor or the substrate. Due to the strong evolutionary divergence and the paucity of experimental information, no confident predictions of protein-ligand and protein-substrate interactions could be made, which hampered the study of sequence-structure-function relationships in the SPOUT superfamily.'),
(90026, 2003, 'bmc', 'Amino acid empirical contact energy definitions for fold recognition in the space of contact maps', 'Berrera, Marco|Molinari, Henriette|Fogolari, Federico', 'International School for Advanced Studies Via Beirut 4, 34014 Trieste, Italy. berrera@sissa.it|International School for Advanced Studies Via Beirut 4, 34014 Trieste, Italy. berrera@sissa.it|International School for Advanced Studies Via Beirut 4, 34014 Trieste, Italy. berrera@sissa.it', 'Italy|Italy|Italy', 198, 'Amino Acids|Computational Biology|Models, Molecular|Predictive Value of Tests|Protein Conformation|Protein Folding|Protein Structure, Tertiary|Reference Values|Solvents|Surface Properties|Thermodynamics', 'Journal Article', '10.1186/1471-2105-1-1', '12689348', 'Contradicting evidence has been presented in the literature concerning the effectiveness of empirical contact energies for fold recognition. Empirical contact energies are calculated on the basis of information available from selected protein structures, with respect to a defined reference state, according to the quasi-chemical approximation. Protein-solvent interactions are estimated from residue solvent accessibility.'),
(90027, 2003, 'bmc', 'GapCoder automates the use of indel characters in phylogenetic analysis', 'Young, Nelson D|Healy, John', 'Department of Biological Sciences, Duquesne University, Pittsburgh, PA 15219, USA. youngnd@duq.edu|Department of Biological Sciences, Duquesne University, Pittsburgh, PA 15219, USA. youngnd@duq.edu', 'United States|United States', 0, 'Algorithms|Computational Biology|Databases, Genetic|Mutagenesis, Insertional|Nucleic Acids|Phylogeny|Sequence Analysis, DNA|Sequence Deletion|Software', 'Journal Article', '10.1186/1471-2105-1-1', '12689349', 'Several ways of incorporating indels into phylogenetic analysis have been suggested. Simple indel coding has two strengths: (1) biological realism and (2) efficiency of analysis. In the method, each indel with different start and/or end positions is considered to be a separate character. The presence/absence of these indel characters is then added to the data set.'),
(90028, 2003, 'bmc', 'PreBIND and Textomy--mining the biomedical literature for protein-protein interactions using a support vector machine', 'Donaldson, Ian|Martin, Joel|de Bruijn, Berry|Wolting, Cheryl|Lay, Vicki|Tuekam, Brigitte|Zhang, Shudong|Baskin, Berivan|Bader, Gary D|Michalickova, Katerina|Pawson, Tony|Hogue, Christopher W V', 'Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca|Samuel Lunenfeld Research Institute, Toronto, M5G 1X5, Canada. ian.donaldson@utoronto.ca', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 198, 'Algorithms|Artificial Intelligence|Computational Biology|Databases, Factual|Databases, Protein|Genome, Fungal|Information Storage and Retrieval|Protein Interaction Mapping|PubMed|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Comparative Study', '10.1186/1471-2105-1-1', '12689350', 'The majority of experimentally verified molecular interaction and biological pathway data are present in the unstructured text of biomedical journal articles where they are inaccessible to computational methods. The Biomolecular interaction network database (BIND) seeks to capture these data in a machine-readable format. We hypothesized that the formidable task-size of backfilling the database could be reduced by using Support Vector Machine technology to first locate interaction information in the literature. We present an information extraction system that was designed to locate protein-protein interaction data in the literature and present these data to curators and the public for review and entry into BIND.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90029, 2003, 'bmc', 'Neural network analysis of lymphoma microarray data: prognosis and diagnosis near-perfect', 'ONeill, Michael C|Song, Li', 'Department of Biological Sciences, University of Maryland, Baltimore County Baltimore, Maryland 21250, USA. moneill@umbc.edu|Department of Biological Sciences, University of Maryland, Baltimore County Baltimore, Maryland 21250, USA. moneill@umbc.edu', 'United States|United States', 198, 'Algorithms|Decision Making, Computer-Assisted|Disease-Free Survival|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Humans|Lymphoma, B-Cell|Lymphoma, Large B-Cell, Diffuse|Neural Networks (Computer)|Oligonucleotide Array Sequence Analysis|Predictive Value of Tests|Prognosis', 'Journal Article', '10.1186/1471-2105-1-1', '12697066', 'Microarray chips are being rapidly deployed as a major tool in genomic research. To date most of the analysis of the enormous amount of information provided on these chips has relied on clustering techniques and other standard statistical procedures. These methods, particularly with regard to cancer patient prognosis, have generally been inadequate in providing the reduced gene subsets required for perfect classification.'),
(90030, 2003, 'bmc', 'Significance analysis of lexical bias in microarray data', 'Kim, Charles C|Falkow, Stanley', 'Microbiology and Immunology, Stanford University Medical Center, Stanford, CA, 94305, USA. cckim@stanford.edu|Microbiology and Immunology, Stanford University Medical Center, Stanford, CA, 94305, USA. cckim@stanford.edu', 'United States|United States', 0, '2,2-Dipyridyl|Artifacts|Binomial Distribution|Chelating Agents|Computational Biology|Gene Expression Regulation, Bacterial|Genomic Islands|Oligonucleotide Array Sequence Analysis|Poisson Distribution|Research Design|Salmonella enterica|Serotyping|Software|Software Design|Up-Regulation', 'Comparative Study', '10.1186/1471-2105-1-1', '12697067', 'Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users.'),
(90031, 2003, 'bmc', 'SNP haplotype tagging from DNA pools of two individuals', 'Hoh, Josephine|Matsuda, Fumihiko|Peng, Xu|Markovic, Daniela|Lathrop, Mark G|Ott, Jurg', 'Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, USA. jhoh@linkage.rockefeller.edu|Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, USA. jhoh@linkage.rockefeller.edu|Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, USA. jhoh@linkage.rockefeller.edu|Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, USA. jhoh@linkage.rockefeller.edu|Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, USA. jhoh@linkage.rockefeller.edu|Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, USA. jhoh@linkage.rockefeller.edu', 'United States|United States|United States|United States|United States|United States', 8, 'Algorithms|Alleles|Calmodulin-Binding Proteins|Computational Biology|Cytoskeletal Proteins|DNA|Genotype|Haplotypes|Humans|Phenotype|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-4-14', '12709267', 'DNA pooling is a technique to reduce genotyping effort while incurring only minor losses in accuracy of allele frequency estimates for single nucleotide polymorphism (SNP) markers.'),
(90032, 2003, 'bmc', 'DNA microarray data and contextual analysis of correlation graphs', 'Rougemont, Jacques|Hingamp, Pascal', 'TAGC, INSERM-ERM 206, Parc Scientifique de Luminy Case 906, 13288 Marseille Cedex 09, France. rougemont@tagc.univ-mrs.fr|TAGC, INSERM-ERM 206, Parc Scientifique de Luminy Case 906, 13288 Marseille Cedex 09, France. rougemont@tagc.univ-mrs.fr', 'France|France', 36, 'Algorithms|Cluster Analysis|Computational Biology|Computer Graphics|Computer Terminals|Gene Expression Profiling|Gene Expression Regulation, Fungal|Gene Expression Regulation, Neoplastic|Humans|Leukemia, Lymphocytic, Chronic, B-Cell|Lymphoma, B-Cell|Lymphoma, Large B-Cell, Diffuse|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Software|Terminology as Topic', 'Journal Article', '10.1186/1471-2105-4-15', '12720549', 'DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation.'),
(90033, 2003, 'bmc', 'Domain fusion analysis by applying relational algebra to protein sequence and domain databases', 'Truong, Kevin|Ikura, Mitsuhiko', 'Department of Medical Biophysics, University of Toronto, Toronto, M3N 1L6, Canada. ktruong@uhnres.utoronto.ca|Department of Medical Biophysics, University of Toronto, Toronto, M3N 1L6, Canada. ktruong@uhnres.utoronto.ca', 'Canada|Canada', 0, 'Alternative Splicing|Animals|Arabidopsis Proteins|Caenorhabditis elegans Proteins|Computational Biology|Databases, Protein|Drosophila Proteins|Humans|Mathematical Computing|Predictive Value of Tests|Protein Structure, Tertiary|Recombination, Genetic|Saccharomyces cerevisiae Proteins|Schizosaccharomyces pombe Proteins|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1186/1471-2105-4-15', '12734020', 'Domain fusion analysis is a useful method to predict functionally linked proteins that may be involved in direct protein-protein interactions or in the same metabolic or signaling pathway. As separate domain databases like BLOCKS, PROSITE, Pfam, SMART, PRINTS-S, ProDom, TIGRFAMs, and amalgamated domain databases like InterPro continue to grow in size and quality, a computational method to perform domain fusion analysis that leverages on these efforts will become increasingly powerful.'),
(90034, 2003, 'bmc', 'A comparison of Pfam and MEROPS: two databases, one comprehensive, and one specialised', 'Studholme, David J|Rawlings, Neil D|Barrett, Alan J|Bateman, Alex', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. ds2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. ds2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. ds2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. ds2@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Animals|Bacterial Proteins|Caenorhabditis elegans Proteins|Cysteine Endopeptidases|Databases, Protein|Drosophila Proteins|Multienzyme Complexes|Mycobacterium tuberculosis|Peptide Hydrolases|Proteasome Endopeptidase Complex|Retroviridae|Sensitivity and Specificity|Viral Proteins', 'Comparative Study', '10.1186/1471-2105-4-17', '12740029', 'We wished to compare two databases based on sequence similarity: one that aims to be comprehensive in its coverage of known sequences, and one that specialises in a relatively small subset of known sequences. One of the motivations behind this study was quality control. Pfam is a comprehensive collection of alignments and hidden Markov models representing families of proteins and domains. MEROPS is a catalogue and classification of enzymes with proteolytic activity (peptidases or proteases). These secondary databases are used by researchers worldwide, yet their contents are not peer reviewed. Therefore, we hoped that a systematic comparison of the contents of Pfam and MEROPS would highlight missing members and false-positives leading to improvements in quality of both databases. An additional reason for carrying out this study was to explore the extent of consensus in the definition of a protein family.'),
(90035, 2003, 'bmc', 'Genome wide identification of regulatory motifs in Bacillus subtilis', 'Mwangi, Michael M|Siggia, Eric D', 'Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY, USA. mmm37@cornell.edu|Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY, USA. mmm37@cornell.edu', 'United States|United States', 30, 'Algorithms|Bacillus subtilis|Base Composition|Computational Biology|Consensus Sequence|Gene Expression Regulation, Bacterial|Genome, Bacterial|Models, Statistical|Operon|Predictive Value of Tests|Regulatory Sequences, Nucleic Acid|Regulon', 'Journal Article', '10.1186/1471-2105-4-18', '12749771', 'To explain the vastly different phenotypes exhibited by the same organism under different conditions, it is essential that we understand how the organisms genes are coordinately regulated. While there are many excellent tools for predicting sequences encoding proteins or RNA genes, few algorithms exist to predict regulatory sequences on a genome wide scale with no prior information.'),
(90036, 2003, 'bmc', 'Identification of signature and primers specific to genus Pseudomonas using mismatched patterns of 16S rDNA sequences', 'Purohit, H J|Raje, D V|Kapley, A', 'Environmental Modeling and Genomics Division, National Environmental Engineering Research Institute, Nehru Marg, Nagpur - 440020 (MS) India. hemantdrd@hotmail.com|Environmental Modeling and Genomics Division, National Environmental Engineering Research Institute, Nehru Marg, Nagpur - 440020 (MS) India. hemantdrd@hotmail.com|Environmental Modeling and Genomics Division, National Environmental Engineering Research Institute, Nehru Marg, Nagpur - 440020 (MS) India. hemantdrd@hotmail.com', 'India|India|India', 0, 'Base Pair Mismatch|Conserved Sequence|DNA Primers|DNA, Bacterial|DNA, Ribosomal|Genetic Variation|Heteroduplex Analysis|Nucleic Acid Heteroduplexes|Polymerase Chain Reaction|Pseudomonas|RNA, Ribosomal, 16S|Repetitive Sequences, Nucleic Acid|Species Specificity', 'Journal Article', '10.1186/1471-2105-4-19', '12769821', 'Pseudomonas, a soil bacterium, has been observed as a dominant genus that survives in different habitats with wide hostile conditions. We had a basic assumption that the species level variation in 16S rDNA sequences of a bacterial genus is mainly due to substitutions rather than insertion or deletion of bases. Keeping this in view, the aim was to identify a region of 16S rDNA sequence and within that focus on substitution prone stretches indicating species level variation and to derive patterns from these stretches that are specific to the genus.'),
(90037, 2003, 'bmc', 'Information extraction from full text scientific articles: where are the keywords?', 'Shah, Parantu K|Perez-Iratxeta, Carolina|Bork, Peer|Andrade, Miguel A', 'Biocomputing, European Molecular Biology Laboratory, Heidelberg, Germany. shah@embl.de|Biocomputing, European Molecular Biology Laboratory, Heidelberg, Germany. shah@embl.de|Biocomputing, European Molecular Biology Laboratory, Heidelberg, Germany. shah@embl.de|Biocomputing, European Molecular Biology Laboratory, Heidelberg, Germany. shah@embl.de', 'Germany|Germany|Germany|Germany', 128, 'Anatomy|Animal Population Groups|Animals|Bacteria|Genetics|Humans|Information Storage and Retrieval|Information Systems|Internet|Online Systems|Periodicals as Topic|Plants|Proteomics|Selection Bias|Species Specificity|Terminology as Topic|Vocabulary, Controlled', 'Evaluation Studies', '10.1186/1471-2105-4-20', '12775220', 'To date, many of the methods for information extraction of biological information from scientific articles are restricted to the abstract of the article. However, full text articles in electronic version, which offer larger sources of data, are currently available. Several questions arise as to whether the effort of scanning full text articles is worthy, or whether the information that can be extracted from the different sections of an article can be relevant.'),
(90038, 2003, 'bmc', 'EasyGene--a prokaryotic gene finder that ranks ORFs by statistical significance', 'Larsen, Thomas Schou|Krogh, Anders', 'Center for Biological Sequence Analysis BioCentrum, Technical University of Denmark Building 208, 2800 Lyngby, Denmark. thsl@novozymes.com|Center for Biological Sequence Analysis BioCentrum, Technical University of Denmark Building 208, 2800 Lyngby, Denmark. thsl@novozymes.com', 'Denmark|Denmark', 121, 'Bacillus subtilis|Bacterial Proteins|Binding Sites|Computational Biology|Escherichia coli|Escherichia coli Proteins|Genes, Bacterial|Genome, Bacterial|Helicobacter pylori|Markov Chains|Models, Genetic|Models, Statistical|Mycobacterium tuberculosis|Open Reading Frames|Predictive Value of Tests|Ribosomes|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-4-21', '12783628', 'Contrary to other areas of sequence analysis, a measure of statistical significance of a putative gene has not been devised to help in discriminating real genes from the masses of random Open Reading Frames (ORFs) in prokaryotic genomes. Therefore, many genomes have too many short ORFs annotated as genes.'),
(90039, 2003, 'bmc', 'Poly: a quantitative analysis tool for simple sequence repeat (SSR) tracts in DNA', 'Bizzaro, Jeff W|Marx, Kenneth A', 'Bioinformatics Organization, Inc, 28 Pope Street, Hudson, MA 01749 USA. jeff@bioinformatics.org|Bioinformatics Organization, Inc, 28 Pope Street, Hudson, MA 01749 USA. jeff@bioinformatics.org', 'United States|United States', 19, 'Algorithms|Animals|Chlamydomonas reinhardtii|Computational Biology|DNA, Plant|DNA, Protozoan|Dictyostelium|GC Rich Sequence|Internet|Models, Genetic|Oryza|Repetitive Sequences, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-4-22', '12791171', 'Simple sequence repeats (SSRs), microsatellites or polymeric sequences are common in DNA and are important biologically. From mononucleotide to trinucleotide repeats and beyond, they can be found in long (> 6 repeating units) tracts and may be characterized by quantifying the frequencies in which they are found and their tract lengths. However, most of the existing computer programs that find SSR tracts do not include these methods.'),
(90040, 2003, 'bmc', 'Importing statistical measures into Artemis enhances gene identification in the Leishmania genome project', 'Aggarwal, Gautam|Worthey, E A|McDonagh, Paul D|Myler, Peter J', 'Seattle Biomedical Research Institute 4 Nickerson Street, Seattle, WA 98109, USA. gaggarwal@sbri.org|Seattle Biomedical Research Institute 4 Nickerson Street, Seattle, WA 98109, USA. gaggarwal@sbri.org|Seattle Biomedical Research Institute 4 Nickerson Street, Seattle, WA 98109, USA. gaggarwal@sbri.org|Seattle Biomedical Research Institute 4 Nickerson Street, Seattle, WA 98109, USA. gaggarwal@sbri.org', 'United States|United States|United States|United States', 16, 'Algorithms|Amino Acid Sequence|Animals|Base Sequence|Computational Biology|Genes, Protozoan|Genome, Protozoan|Leishmania major|Models, Statistical|Molecular Sequence Data|Predictive Value of Tests|Programming Languages|Protozoan Proteins', 'Journal Article', '10.1186/1471-2105-4-23', '12793912', 'Seattle Biomedical Research Institute (SBRI) as part of the Leishmania Genome Network (LGN) is sequencing chromosomes of the trypanosomatid protozoan species Leishmania major. At SBRI, chromosomal sequence is annotated using a combination of trained and untrained non-consensus gene-prediction algorithms with ARTEMIS, an annotation platform with rich and user-friendly interfaces.'),
(90041, 2003, 'bmc', 'A data review and re-assessment of ovarian cancer serum proteomic profiling', 'Sorace, James M|Zhan, Min', 'Department of Pathology and Laboratory Services, Veterans Administration Maryland Health Care System, Baltimore 21201, USA. jmsorace@ix.netcom.com|Department of Pathology and Laboratory Services, Veterans Administration Maryland Health Care System, Baltimore 21201, USA. jmsorace@ix.netcom.com', 'United States|United States', 267, 'Artificial Intelligence|Blood Proteins|Computational Biology|Databases, Protein|Diagnostic Techniques, Obstetrical and Gynecological|Female|Humans|Mass Spectrometry|Middle Aged|Normal Distribution|Ovarian Neoplasms|Protein Array Analysis|Proteome|Sensitivity and Specificity|Statistics, Nonparametric', 'Comparative Study', '10.1186/1471-2105-4-24', '12795817', 'The early detection of ovarian cancer has the potential to dramatically reduce mortality. Recently, the use of mass spectrometry to develop profiles of patient serum proteins, combined with advanced data mining algorithms has been reported as a promising method to achieve this goal. In this report, we analyze the Ovarian Dataset 8-7-02 downloaded from the Clinical Proteomics Program Databank website, using nonparametric statistics and stepwise discriminant analysis to develop rules to diagnose patients, as well as to understand general patterns in the data that may guide future research.'),
(90042, 2003, 'bmc', 'AGRIS: Arabidopsis gene regulatory information server, an information resource of Arabidopsis cis-regulatory elements and transcription factors', 'Davuluri, Ramana V|Sun, Hao|Palaniswamy, Saranyan K|Matthews, Nicole|Molina, Carlos|Kurtz, Mike|Grotewold, Erich', 'Human Cancer Genetics Program, Comprehensive Cancer Center, Dept of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH 43210, USA. Davuluri-1@medctr.osu.edu|Human Cancer Genetics Program, Comprehensive Cancer Center, Dept of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH 43210, USA. Davuluri-1@medctr.osu.edu|Human Cancer Genetics Program, Comprehensive Cancer Center, Dept of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH 43210, USA. Davuluri-1@medctr.osu.edu|Human Cancer Genetics Program, Comprehensive Cancer Center, Dept of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH 43210, USA. Davuluri-1@medctr.osu.edu|Human Cancer Genetics Program, Comprehensive Cancer Center, Dept of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH 43210, USA. Davuluri-1@medctr.osu.edu|Human Cancer Genetics Program, Comprehensive Cancer Center, Dept of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH 43210, USA. Davuluri-1@medctr.osu.edu|Human Cancer Genetics Program, Comprehensive Cancer Center, Dept of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, Columbus, OH 43210, USA. Davuluri-1@medctr.osu.edu', 'United States|United States|United States|United States|United States|United States|United States', 282, '3 Untranslated Regions|5 Untranslated Regions|Arabidopsis|Arabidopsis Proteins|Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Regulation, Plant|Genes, Plant|Information Systems|Internet|Regulatory Sequences, Nucleic Acid|Trans-Activators|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-4-25', '12820902', 'The gene regulatory information is hardwired in the promoter regions formed by cis-regulatory elements that bind specific transcription factors (TFs). Hence, establishing the architecture of plant promoters is fundamental to understanding gene expression. The determination of the regulatory circuits controlled by each TF and the identification of the cis-regulatory sequences for all genes have been identified as two of the goals of the Multinational Coordinated Arabidopsis thaliana Functional Genomics Project by the Multinational Arabidopsis Steering Committee (June 2002).'),
(90043, 2003, 'bmc', 'Reproducibility of gene expression across generations of Affymetrix microarrays', 'Nimgaonkar, Ashish|Sanoudou, Despina|Butte, Atul J|Haslett, Judith N|Kunkel, Louis M|Beggs, Alan H|Kohane, Isaac S', 'Informatics Program, Childrens Hospital, Harvard Medical School, Boston, MA, USA. ashish@chip.org|Informatics Program, Childrens Hospital, Harvard Medical School, Boston, MA, USA. ashish@chip.org|Informatics Program, Childrens Hospital, Harvard Medical School, Boston, MA, USA. ashish@chip.org|Informatics Program, Childrens Hospital, Harvard Medical School, Boston, MA, USA. ashish@chip.org|Informatics Program, Childrens Hospital, Harvard Medical School, Boston, MA, USA. ashish@chip.org|Informatics Program, Childrens Hospital, Harvard Medical School, Boston, MA, USA. ashish@chip.org|Informatics Program, Childrens Hospital, Harvard Medical School, Boston, MA, USA. ashish@chip.org', 'United States|United States|United States|United States|United States|United States|United States', 54, 'Calibration|Computational Biology|DNA, Complementary|Gene Expression Profiling|Gene Expression Regulation|Humans|Muscle, Skeletal|Oligonucleotide Array Sequence Analysis|RNA|RNA Probes|RNA, Complementary|Statistical Distributions', 'Comparative Study', '10.1186/1471-2105-4-27', '12823866', 'The development of large-scale gene expression profiling technologies is rapidly changing the norms of biological investigation. But the rapid pace of change itself presents challenges. Commercial microarrays are regularly modified to incorporate new genes and improved target sequences. Although the ability to compare datasets across generations is crucial for any long-term research project, to date no means to allow such comparisons have been developed. In this study the reproducibility of gene expression levels across two generations of Affymetrix GeneChips (HuGeneFL and HG-U95A) was measured.'),
(90044, 2003, 'bmc', 'Statistical implications of pooling RNA samples for microarray experiments', 'Peng, Xuejun|Wood, Constance L|Blalock, Eric M|Chen, Kuey Chu|Landfield, Philip W|Stromberg, Arnold J', 'Department of Statistics, University of Kentucky, Lexington, KY 40506, USA. peng@ms.uky.edu|Department of Statistics, University of Kentucky, Lexington, KY 40506, USA. peng@ms.uky.edu|Department of Statistics, University of Kentucky, Lexington, KY 40506, USA. peng@ms.uky.edu|Department of Statistics, University of Kentucky, Lexington, KY 40506, USA. peng@ms.uky.edu|Department of Statistics, University of Kentucky, Lexington, KY 40506, USA. peng@ms.uky.edu|Department of Statistics, University of Kentucky, Lexington, KY 40506, USA. peng@ms.uky.edu', 'United States|United States|United States|United States|United States|United States', 248, 'Computational Biology|Computer Simulation|Empirical Research|Gene Expression Profiling|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pilot Projects|RNA|Research Design|Sample Size', 'Journal Article', '10.1186/1471-2105-4-26', '12823867', 'Microarray technology has become a very important tool for studying gene expression profiles under various conditions. Biologists often pool RNA samples extracted from different subjects onto a single microarray chip to help defray the cost of microarray experiments as well as to correct for the technical difficulty in getting sufficient RNA from a single subject. However, the statistical, technical and financial implications of pooling have not been explicitly investigated.'),
(90045, 2003, 'bmc', 'Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases', 'Ritchie, Marylyn D|White, Bill C|Parker, Joel S|Hahn, Lance W|Moore, Jason H', 'Program in Human Genetics and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN, 37232-0700, USA. ritchie@phg.mc.vanderbilt.edu|Program in Human Genetics and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN, 37232-0700, USA. ritchie@phg.mc.vanderbilt.edu|Program in Human Genetics and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN, 37232-0700, USA. ritchie@phg.mc.vanderbilt.edu|Program in Human Genetics and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN, 37232-0700, USA. ritchie@phg.mc.vanderbilt.edu|Program in Human Genetics and Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN, 37232-0700, USA. ritchie@phg.mc.vanderbilt.edu', 'United States|United States|United States|United States|United States', 171, 'Algorithms|Artificial Intelligence|Epistasis, Genetic|Gene Expression Regulation|Humans|Models, Genetic|Molecular Epidemiology|Neural Networks (Computer)|Polymorphism, Single Nucleotide|Predictive Value of Tests|Research Design|Software|Software Validation', 'Journal Article', '10.1186/1471-2105-4-28', '12846935', 'Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases.'),
(90046, 2003, 'bmc', 'MatGAT: an application that generates similarity/identity matrices using protein or DNA sequences', 'Campanella, James J|Bitincka, Ledion|Smalley, John', 'Montclair State University, Department of Biology and Molecular Biology, 1 Normal Avenue, Montclair, New Jersey 07043 USA. james.campanella@montclair.edu|Montclair State University, Department of Biology and Molecular Biology, 1 Normal Avenue, Montclair, New Jersey 07043 USA. james.campanella@montclair.edu|Montclair State University, Department of Biology and Molecular Biology, 1 Normal Avenue, Montclair, New Jersey 07043 USA. james.campanella@montclair.edu', 'Jersey|Jersey|Jersey', 636, 'Animals|Computational Biology|Computer Graphics|Databases, Nucleic Acid|Humans|Internet|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-4-29', '12854978', 'The rapid increase in the amount of protein and DNA sequence information available has become almost overwhelming to researchers. So much information is now accessible that high-quality, functional gene analysis and categorization has become a major goal for many laboratories. To aid in this categorization, there is a need for non-commercial software that is able to both align sequences and also calculate pairwise levels of similarity/identity.'),
(90047, 2003, 'bmc', 'Evolutionary algorithms for the selection of single nucleotide polymorphisms', 'Hubley, Robert M|Zitzler, Eckart|Roach, Jared C', 'Institute for Systems Biology, Seattle, WA, USA. rhubley@systemsbiology.org|Institute for Systems Biology, Seattle, WA, USA. rhubley@systemsbiology.org|Institute for Systems Biology, Seattle, WA, USA. rhubley@systemsbiology.org', 'United States|United States|United States', 18, 'Algorithms|Computational Biology|Computer Simulation|Evolution, Molecular|Genetic Markers|Humans|Major Histocompatibility Complex|Models, Genetic|Polymorphism, Single Nucleotide|Programming Languages|Selection, Genetic|Software', 'Journal Article', '10.1186/1471-2105-4-30', '12875658', 'Large databases of single nucleotide polymorphisms (SNPs) are available for use in genomics studies. Typically, investigators must choose a subset of SNPs from these databases to employ in their studies. The choice of subset is influenced by many factors, including estimated or known reliability of the SNP, biochemical factors, intellectual property, cost, and effectiveness of the subset for mapping genes or identifying disease loci. We present an evolutionary algorithm for multiobjective SNP selection.'),
(90048, 2003, 'bmc', 'Comparison of mode estimation methods and application in molecular clock analysis', 'Hedges, S Blair|Shah, Prachi', 'NASA Astrobiology Institute and Department of Biology, Pennsylvania State University, 208 Mueller Laboratory, University Park, PA 16802-5301, U,S,A. sbh1@psu.edu|NASA Astrobiology Institute and Department of Biology, Pennsylvania State University, 208 Mueller Laboratory, University Park, PA 16802-5301, U,S,A. sbh1@psu.edu', '-|-', 39, 'Ascomycota|Basidiomycota|Biological Clocks|Bryophyta|Chlorophyta|Computational Biology|Computer Simulation|Evolution, Molecular|Models, Statistical|Normal Distribution|Plants', 'Comparative Study', '10.1186/1471-2105-4-31', '12892571', 'Distributions of time estimates in molecular clock studies are sometimes skewed or contain outliers. In those cases, the mode is a better estimator of the overall time of divergence than the mean or median. However, different methods are available for estimating the mode. We compared these methods in simulations to determine their strengths and weaknesses and further assessed their performance when applied to real data sets from a molecular clock study.'),
(90049, 2003, 'bmc', 'The Longhorn Array Database (LAD): an open-source, MIAME compliant implementation of the Stanford Microarray Database (SMD)', 'Killion, Patrick J|Sherlock, Gavin|Iyer, Vishwanath R', 'Section of Molecular Genetics and Microbiology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712-0159, USA.|Section of Molecular Genetics and Microbiology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712-0159, USA.|Section of Molecular Genetics and Microbiology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712-0159, USA.', 'United States|United States|United States', 74, 'Database Management Systems|Databases, Genetic|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-4-32', '12930545', 'The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms.'),
(90050, 2003, 'bmc', 'Evaluation of normalization methods for microarray data', 'Park, Taesung|Yi, Sung-Gon|Kang, Sung-Hyun|Lee, SeungYeoun|Lee, Yong-Sung|Simon, Richard', 'Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr|Department of Statistics, Seoul National University, Seoul, Korea. tspark@stats.snu.ac.kr', '-|-|-|-|-|-', 116, 'Analysis of Variance|Animals|Cell Differentiation|Cerebral Cortex|Computer Simulation|Gene Expression Regulation, Developmental|Neurons|Normal Distribution|Oligonucleotide Array Sequence Analysis|Rats|Stem Cells', 'Comparative Study', '10.1186/1471-2105-4-33', '12950995', 'Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. This novel technique helps us to understand gene regulation as well as gene by gene interactions more systematically. In the microarray experiment, however, many undesirable systematic variations are observed. Even in replicated experiment, some variations are commonly observed. Normalization is the process of removing some sources of variation which affect the measured gene expression levels. Although a number of normalization methods have been proposed, it has been difficult to decide which methods perform best. Normalization plays an important role in the earlier stage of microarray data analysis. The subsequent analysis results are highly dependent on normalization.'),
(90051, 2003, 'bmc', 'OrthoParaMap: distinguishing orthologs from paralogs by integrating comparative genome data and gene phylogenies', 'Cannon, Steven B|Young, Nevin D', 'Plant Biology Department, University of Minnesota, St, Paul, MN 55108, USA. cann0010@umn.edu|Plant Biology Department, University of Minnesota, St, Paul, MN 55108, USA. cann0010@umn.edu', 'United States|United States', 53, 'Animals|Antigens, Neoplasm|Arabidopsis|Cysteine Endopeptidases|DNA, Plant|Gene Duplication|Genes, Plant|Genome, Plant|Humans|Melanoma|Mice|Multienzyme Complexes|Phylogeny|Proteasome Endopeptidase Complex|Protein Subunits|Sequence Homology, Nucleic Acid|Software|X Chromosome', 'Comparative Study', '10.1186/1471-2105-4-35', '12952558', 'In eukaryotic genomes, most genes are members of gene families. When comparing genes from two species, therefore, most genes in one species will be homologous to multiple genes in the second. This often makes it difficult to distinguish orthologs (separated through speciation) from paralogs (separated by other types of gene duplication). Combining phylogenetic relationships and genomic position in both genomes helps to distinguish between these scenarios. This kind of comparison can also help to describe how gene families have evolved within a single genome that has undergone polyploidy or other large-scale duplications, as in the case of Arabidopsis thaliana - and probably most plant genomes.'),
(90052, 2003, 'bmc', 'ELISA: structure-function inferences based on statistically significant and evolutionarily inspired observations', 'Shakhnovich, Boris E|Harvey, John M|Comeau, Steve|Lorenz, David|DeLisi, Charles|Shakhnovich, Eugene', 'BioInformatics Program, Boston University, Boston, MA, 02215, USA. borya@bu.edu|BioInformatics Program, Boston University, Boston, MA, 02215, USA. borya@bu.edu|BioInformatics Program, Boston University, Boston, MA, 02215, USA. borya@bu.edu|BioInformatics Program, Boston University, Boston, MA, 02215, USA. borya@bu.edu|BioInformatics Program, Boston University, Boston, MA, 02215, USA. borya@bu.edu|BioInformatics Program, Boston University, Boston, MA, 02215, USA. borya@bu.edu', 'United States|United States|United States|United States|United States|United States', 13, 'Amino Acid Sequence|Bacterial Proteins|Computational Biology|Databases, Protein|Evolution, Molecular|Internet|Models, Genetic|Models, Statistical|Molecular Sequence Data|Phylogeny|Protein Structure, Quaternary|Protein Structure, Tertiary|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Comparative Study', '10.1186/1471-2105-4-34', '12952559', 'The problem of functional annotation based on homology modeling is primary to current bioinformatics research. Researchers have noted regularities in sequence, structure and even chromosome organization that allow valid functional cross-annotation. However, these methods provide a lot of false negatives due to limited specificity inherent in the system. We want to create an evolutionarily inspired organization of data that would approach the issue of structure-function correlation from a new, probabilistic perspective. Such organization has possible applications in phylogeny, modeling of functional evolution and structural determination. ELISA (Evolutionary Lineage Inferred from Structural Analysis, http://romi.bu.edu/elisa) is an online database that combines functional annotation with structure and sequence homology modeling to place proteins into sequence-structure-function neighborhoods. The atomic unit of the database is a set of sequences and structural templates that those sequences encode. A graph that is built from the structural comparison of these templates is called PDUG (protein domain universe graph). We introduce a method of functional inference through a probabilistic calculation done on an arbitrary set of PDUG nodes. Further, all PDUG structures are mapped onto all fully sequenced proteomes allowing an easy interface for evolutionary analysis and research into comparative proteomics. ELISA is the first database with applicability to evolutionary structural genomics explicitly in mind.'),
(90053, 2003, 'bmc', 'Cluster stability scores for microarray data in cancer studies', 'Smolkin, Mark|Ghosh, Debashis', 'Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA. Marksmolkin@hotmail.com|Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA. Marksmolkin@hotmail.com', 'United States|United States', 83, 'Algorithms|Child|Cluster Analysis|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Humans|Lymphoma, B-Cell|Lymphoma, Large B-Cell, Diffuse|Melanoma|Neoplasms|Oligonucleotide Array Sequence Analysis|Sarcoma, Ewing', 'Comparative Study', '10.1186/1471-2105-4-36', '12959646', 'A potential benefit of profiling of tissue samples using microarrays is the generation of molecular fingerprints that will define subtypes of disease. Hierarchical clustering has been the primary analytical tool used to define disease subtypes from microarray experiments in cancer settings. Assessing cluster reliability poses a major complication in analyzing output from clustering procedures. While most work has focused on estimating the number of clusters in a dataset, the question of stability of individual-level clusters has not been addressed.'),
(90054, 2003, 'bmc', 'Genome-wide prediction, display and refinement of binding sites with information theory-based models', 'Gadiraju, Sashidhar|Vyhlidal, Carrie A|Leeder, J Steven|Rogan, Peter K', 'Laboratory of Human Molecular Genetics, Childrens Mercy Hospital and Clinics, School of Medicine, and School of Interdisciplinary Computer Science and Engineering University of Missouri-Kansas City, Kansas City, MO 64108 USA. sashidharg@yahoo.com|Laboratory of Human Molecular Genetics, Childrens Mercy Hospital and Clinics, School of Medicine, and School of Interdisciplinary Computer Science and Engineering University of Missouri-Kansas City, Kansas City, MO 64108 USA. sashidharg@yahoo.com|Laboratory of Human Molecular Genetics, Childrens Mercy Hospital and Clinics, School of Medicine, and School of Interdisciplinary Computer Science and Engineering University of Missouri-Kansas City, Kansas City, MO 64108 USA. sashidharg@yahoo.com|Laboratory of Human Molecular Genetics, Childrens Mercy Hospital and Clinics, School of Medicine, and School of Interdisciplinary Computer Science and Engineering University of Missouri-Kansas City, Kansas City, MO 64108 USA. sashidharg@yahoo.com', 'United States|United States|United States|United States', 14, 'Binding Sites|Computer Graphics|Computer Systems|E-Box Elements|Genome, Human|Humans|Information Theory|Models, Genetic|Predictive Value of Tests|Programming Languages|RNA Splice Sites|Response Elements|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-4-38', '12962546', 'We present Delila-genome, a software system for identification, visualization and analysis of protein binding sites in complete genome sequences. Binding sites are predicted by scanning genomic sequences with information theory-based (or user-defined) weight matrices. Matrices are refined by adding experimentally-defined binding sites to published binding sites. Delila-Genome was used to examine the accuracy of individual information contents of binding sites detected with refined matrices as a measure of the strengths of the corresponding protein-nucleic acid interactions. The software can then be used to predict novel sites by rescanning the genome with the refined matrices.'),
(90055, 2003, 'bmc', 'Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction', 'Galfalvy, Hanga C|Erraji-Benchekroun, Loubna|Smyrniotopoulos, Peggy|Pavlidis, Paul|Ellis, Steven P|Mann, J John|Sibille, Etienne|Arango, Victoria', 'Department of Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA. hanga@neuron.cpmc.columbia.edu|Department of Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA. hanga@neuron.cpmc.columbia.edu|Department of Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA. hanga@neuron.cpmc.columbia.edu|Department of Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA. hanga@neuron.cpmc.columbia.edu|Department of Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA. hanga@neuron.cpmc.columbia.edu|Department of Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA. hanga@neuron.cpmc.columbia.edu|Department of Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA. hanga@neuron.cpmc.columbia.edu|Department of Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA. hanga@neuron.cpmc.columbia.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 50, 'Algorithms|Chromosomes, Human, Y|Computational Biology|Female|Gene Expression Profiling|Gene Expression Regulation, Developmental|Genetic Linkage|Genomics|Humans|Male|Models, Genetic|Oligonucleotide Array Sequence Analysis|Prefrontal Cortex|Quality Control|RNA Probes|Sensitivity and Specificity|Sex Chromosomes|Sex Differentiation', 'Comparative Study', '10.1186/1471-2105-4-37', '12962547', 'Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a gold standard. We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods.'),
(90056, 2003, 'bmc', 'cDNA2Genome: a tool for mapping and annotating cDNAs', 'Del Val, Coral|Glatting, Karl-Heinz|Suhai, Sandor', 'Department of Molecular Biophysics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de|Department of Molecular Biophysics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de|Department of Molecular Biophysics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.delval@dkfz.de', 'Germany|Germany|Germany', 10, 'Chromosome Mapping|Computational Biology|DNA|DNA, Complementary|Databases, Genetic|Exons|Genome, Human|Humans|Internet|Introns|Predictive Value of Tests|Sequence Alignment|Software|Software Design|Time Factors', 'Comparative Study', '10.1186/1471-2105-4-39', '12964951', 'In the last years several high-throughput cDNA sequencing projects have been funded worldwide with the aim of identifying and characterizing the structure of complete novel human transcripts. However some of these cDNAs are error prone due to frameshifts and stop codon errors caused by low sequence quality, or to cloning of truncated inserts, among other reasons. Therefore, accurate CDS prediction from these sequences first require the identification of potentially problematic cDNAs in order to speed up the posterior annotation process.'),
(90057, 2003, 'bmc', 'Probabilistic estimation of microarray data reliability and underlying gene expression', 'Bilke, Sven|Breslin, Thomas|Sigvardsson, Mikael', 'Complex Systems Division, Department of Theoretical Physics, University of Lund, Sölvegatan 14A, SE-223 62 Lund, Sweden. sven@thep.lu.se|Complex Systems Division, Department of Theoretical Physics, University of Lund, Sölvegatan 14A, SE-223 62 Lund, Sweden. sven@thep.lu.se|Complex Systems Division, Department of Theoretical Physics, University of Lund, Sölvegatan 14A, SE-223 62 Lund, Sweden. sven@thep.lu.se', 'Sweden|Sweden|Sweden', 7, 'Algorithms|Animals|B-Lymphocytes|Cell Differentiation|Computational Biology|Gene Expression Profiling|Gene Expression Regulation|Mice|Models, Statistical|Oligonucleotide Array Sequence Analysis|Phenotype|Probability|RNA, Messenger', 'Comparative Study', '10.1186/1471-2105-4-40', '12967349', 'The availability of high throughput methods for measurement of mRNA concentrations makes the reliability of conclusions drawn from the data and global quality control of samples and hybridization important issues. We address these issues by an information theoretic approach, applied to discretized expression values in replicated gene expression data.'),
(90058, 2003, 'bmc', 'The COG database: an updated version includes eukaryotes', 'Tatusov, Roman L|Fedorova, Natalie D|Jackson, John D|Jacobs, Aviva R|Kiryutin, Boris|Koonin, Eugene V|Krylov, Dmitri M|Mazumder, Raja|Mekhedov, Sergei L|Nikolskaya, Anastasia N|Rao, B Sridhar|Smirnov, Sergei|Sverdlov, Alexander V|Vasudevan, Sona|Wolf, Yuri I|Yin, Jodie J|Natale, Darren A', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA. tatusov@ncbi.nlm.nih.gov', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Databases, Nucleic Acid|Databases, Protein|Eukaryotic Cells|Evolution, Molecular|Humans|National Institutes of Health (U.S.)|Proteins|Terminology as Topic|United States', 'Journal Article', '10.1186/1471-2105-4-41', '12969510', 'The availability of multiple, essentially complete genome sequences of prokaryotes and eukaryotes spurred both the demand and the opportunity for the construction of an evolutionary classification of genes from these genomes. Such a classification system based on orthologous relationships between genes appears to be a natural framework for comparative genomics and should facilitate both functional annotation of genomes and large-scale evolutionary studies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90059, 2003, 'bmc', 'Molecular phylogeny of the kelch-repeat superfamily reveals an expansion of BTB/kelch proteins in animals', 'Prag, Soren|Adams, Josephine C', 'Dept of Cell Biology, Lerner Research Institute, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, Ohio 44195, USA. sprag@tiscali.co.uk|Dept of Cell Biology, Lerner Research Institute, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, Ohio 44195, USA. sprag@tiscali.co.uk', 'United States|United States', 118, 'Amino Acid Motifs|Amino Acid Sequence|Animals|Anopheles|Caenorhabditis elegans Proteins|Carrier Proteins|DNA Repeat Expansion|Drosophila Proteins|Evolution, Molecular|Genome, Fungal|Genome, Human|Genome, Protozoan|Humans|Mice|Molecular Sequence Data|Multigene Family|Phylogeny|Poxviridae|Rats|Saccharomyces cerevisiae Proteins|Schizosaccharomyces pombe Proteins|Sequence Alignment|Viral Proteins', 'Comparative Study', '10.1186/1471-2105-4-42', '13678422', 'The kelch motif is an ancient and evolutionarily-widespread sequence motif of 44-56 amino acids in length. It occurs as five to seven repeats that form a beta-propeller tertiary structure. Over 28 kelch-repeat proteins have been sequenced and functionally characterised from diverse organisms spanning from viruses, plants and fungi to mammals and it is evident from expressed sequence tag, domain and genome databases that many additional hypothetical proteins contain kelch-repeats. In general, kelch-repeat beta-propellers are involved in protein-protein interactions, however the modest sequence identity between kelch motifs, the diversity of domain architectures, and the partial information on this protein family in any single species, all present difficulties to developing a coherent view of the kelch-repeat domain and the kelch-repeat protein superfamily. To understand the complexity of this superfamily of proteins, we have analysed by bioinformatics the complement of kelch-repeat proteins encoded in the human genome and have made comparisons to the kelch-repeat proteins encoded in other sequenced genomes.'),
(90060, 2003, 'bmc', 'RSEARCH: finding homologs of single structured RNA sequences', 'Klein, Robert J|Eddy, Sean R', 'Howard Hughes Medical Institute & Department of Genetics, Washington University School of Medicine, Saint Louis, Missouri 63110, USA. rjklein@linkage.rockefeller.edu|Howard Hughes Medical Institute & Department of Genetics, Washington University School of Medicine, Saint Louis, Missouri 63110, USA. rjklein@linkage.rockefeller.edu', 'United States|United States', 0, 'Animals|Arabidopsis|Archaeoglobus fulgidus|Base Composition|Computational Biology|Databases, Genetic|MicroRNAs|Models, Genetic|Nucleic Acid Conformation|Pyrococcus horikoshii|RNA|RNA, Archaeal|RNA, Fungal|RNA, Helminth|RNA, Plant|RNA, Transfer, Ala|RNA, Transfer, Asn|Ribonuclease P|Saccharomyces cerevisiae|Sequence Homology, Nucleic Acid|Signal Recognition Particle|Software|Software Validation', 'Comparative Study', '10.1186/1471-2105-4-44', '14499004', 'For many RNA molecules, secondary structure rather than primary sequence is the evolutionarily conserved feature. No programs have yet been published that allow searching a sequence database for homologs of a single RNA molecule on the basis of secondary structure.'),
(90061, 2003, 'bmc', 'Relationship of SARS-CoV to other pathogenic RNA viruses explored by tetranucleotide usage profiling', 'Yap, Yee Leng|Zhang, Xue Wu|Danchin, Antoine', 'HKU-Pasteur Research Centre, Dexter H,C, Man Building, 8 Sassoon Road Pokfulam, Hong Kong. daniely@hkusua.hku.hk|HKU-Pasteur Research Centre, Dexter H,C, Man Building, 8 Sassoon Road Pokfulam, Hong Kong. daniely@hkusua.hku.hk|HKU-Pasteur Research Centre, Dexter H,C, Man Building, 8 Sassoon Road Pokfulam, Hong Kong. daniely@hkusua.hku.hk', 'Hong Kong|Hong Kong|Hong Kong', 16, 'Algorithms|Animals|Cattle|Coronavirus 229E, Human|Coronavirus, Bovine|Dinucleotide Repeats|Gene Expression Profiling|Gene Expression Regulation, Viral|Genome, Viral|Hemorrhagic Disease Virus, Rabbit|Humans|Microsatellite Repeats|Multivariate Analysis|Open Reading Frames|Phylogeny|RNA Viruses|RNA, Viral|Rabbits|SARS Virus', 'Comparative Study', '10.1186/1471-2105-4-43', '14499005', 'The exact origin of the cause of the Severe Acute Respiratory Syndrome (SARS) is still an open question. The genomic sequence relationship of SARS-CoV with 30 different single-stranded RNA (ssRNA) viruses of various families was studied using two non-standard approaches. Both approaches began with the vectorial profiling of the tetra-nucleotide usage pattern V for each virus. In approach one, a distance measure of a vector V, based on correlation coefficient was devised to construct a relationship tree by the neighbor-joining algorithm. In approach two, a multivariate factor analysis was performed to derive the embedded tetra-nucleotide usage patterns. These patterns were subsequently used to classify the selected viruses.'),
(90062, 2003, 'bmc', 'Visualisation and graph-theoretic analysis of a large-scale protein structural interactome', 'Bolser, Dan|Dafas, Panos|Harrington, Richard|Park, Jong|Schroeder, Michael', 'Department of Computing, City University, London EC1V 0HB, UK. dmb@mrc-dunn.cam.ac.uk|Department of Computing, City University, London EC1V 0HB, UK. dmb@mrc-dunn.cam.ac.uk|Department of Computing, City University, London EC1V 0HB, UK. dmb@mrc-dunn.cam.ac.uk|Department of Computing, City University, London EC1V 0HB, UK. dmb@mrc-dunn.cam.ac.uk|Department of Computing, City University, London EC1V 0HB, UK. dmb@mrc-dunn.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Archaeal Proteins|Bacterial Proteins|Computational Biology|Computer Graphics|Databases, Protein|Evolution, Molecular|Genetic Variation|Imaging, Three-Dimensional|Models, Molecular|Multienzyme Complexes|Protein Interaction Mapping|Protein Structure, Quaternary|Species Specificity|Viral Proteins', 'Journal Article', '10.1186/1471-2105-4-45', '14531933', 'Large-scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in the PDB. PSIMAP incorporates both functional and evolutionary information into a single network.'),
(90063, 2003, 'bmc', 'Domain analysis of the tubulin cofactor system: a model for tubulin folding and dimerization', 'Grynberg, Marcin|Jaroszewski, Lukasz|Godzik, Adam', 'Institute of Biochemistry and Biophysics, Polish Academy of Sciences, 5A Pawinskiego St, 02-106 Warsaw, Poland. marcin@ljcrf.edu|Institute of Biochemistry and Biophysics, Polish Academy of Sciences, 5A Pawinskiego St, 02-106 Warsaw, Poland. marcin@ljcrf.edu|Institute of Biochemistry and Biophysics, Polish Academy of Sciences, 5A Pawinskiego St, 02-106 Warsaw, Poland. marcin@ljcrf.edu', 'Poland|Poland|Poland', 34, 'Amino Acid Sequence|Animals|Caenorhabditis|Carps|Dimerization|Fish Proteins|Fungal Proteins|Helminth Proteins|Humans|Models, Molecular|Molecular Chaperones|Molecular Sequence Data|Peptides|Predictive Value of Tests|Protein Folding|Protein Structure, Tertiary|Rabbits|Schizosaccharomyces pombe Proteins|Sequence Homology, Amino Acid|Tubulin', 'Comparative Study', '10.1186/1471-2105-4-46', '14536023', 'The correct folding and dimerization of tubulins, before their addition to the microtubular structure, needs a group of conserved proteins called cofactors A to E. The biochemical analysis of cofactors gave an insight to their general functions, however not much is known about the domain structure and detailed, molecular function of these proteins.'),
(90064, 2003, 'bmc', 'Trustworthiness and metrics in visualizing similarity of gene expression', 'Kaski, Samuel|Nikkilä, Janne|Oja, Merja|Venna, Jarkko|Törönen, Petri|Castrén, Eero', 'Neural Networks Research Centre, Helsinki University of Technology P,O, Box 9800, FIN-02015 HUT, Finland. samuel.kaski@hut.fi|Neural Networks Research Centre, Helsinki University of Technology P,O, Box 9800, FIN-02015 HUT, Finland. samuel.kaski@hut.fi|Neural Networks Research Centre, Helsinki University of Technology P,O, Box 9800, FIN-02015 HUT, Finland. samuel.kaski@hut.fi|Neural Networks Research Centre, Helsinki University of Technology P,O, Box 9800, FIN-02015 HUT, Finland. samuel.kaski@hut.fi|Neural Networks Research Centre, Helsinki University of Technology P,O, Box 9800, FIN-02015 HUT, Finland. samuel.kaski@hut.fi|Neural Networks Research Centre, Helsinki University of Technology P,O, Box 9800, FIN-02015 HUT, Finland. samuel.kaski@hut.fi', 'Finland|Finland|Finland|Finland|Finland|Finland', 94, 'Animals|Cluster Analysis|Computer Graphics|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Fungal|Humans|Mice|Oligonucleotide Array Sequence Analysis|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1186/1471-2105-4-48', '14552657', 'Conventionally, the first step in analyzing the large and high-dimensional data sets measured by microarrays is visual exploration. Dendrograms of hierarchical clustering, self-organizing maps (SOMs), and multidimensional scaling have been used to visualize similarity relationships of data samples. We address two central properties of the methods: (i) Are the visualizations trustworthy, i.e., if two samples are visualized to be similar, are they really similar? (ii) The metric. The measure of similarity determines the result, we propose using a new learning metrics principle to derive a metric from interrelationships among data sets.'),
(90065, 2003, 'bmc', 'OXBench: a benchmark for evaluation of protein multiple sequence alignment accuracy', 'Raghava, G P S|Searle, Stephen M J|Audley, Patrick C|Barber, Jonathan D|Barton, Geoffrey J', 'School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, Scotland, UK. raghava@imtech.res.in|School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, Scotland, UK. raghava@imtech.res.in|School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, Scotland, UK. raghava@imtech.res.in|School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, Scotland, UK. raghava@imtech.res.in|School of Life Sciences, University of Dundee, Dow St, Dundee, DD1 5EH, Scotland, UK. raghava@imtech.res.in', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Amino Acid Sequence|Benchmarking|Cluster Analysis|Computational Biology|Computer Graphics|Conserved Sequence|Databases, Protein|Ferredoxins|Internet|Molecular Sequence Data|Proteins|Reproducibility of Results|Sequence Alignment|Sequence Homology, Amino Acid|Software|Software Design|Software Validation|Statistical Distributions', 'Comparative Study', '10.1186/1471-2105-4-47', '14552658', 'The alignment of two or more protein sequences provides a powerful guide in the prediction of the protein structure and in identifying key functional residues, however, the utility of any prediction is completely dependent on the accuracy of the alignment. In this paper we describe a suite of reference alignments derived from the comparison of protein three-dimensional structures together with evaluation measures and software that allow automatically generated alignments to be benchmarked. We test the OXBench benchmark suite on alignments generated by the AMPS multiple alignment method, then apply the suite to compare eight different multiple alignment algorithms. The benchmark shows the current state-of-the art for alignment accuracy and provides a baseline against which new alignment algorithms may be judged.'),
(90066, 2003, 'bmc', 'The TROVE module: a common element in Telomerase, Ro and Vault ribonucleoproteins', 'Bateman, Alex|Kickhoefer, Valerie', 'The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. agb@sanger.ac.uk|The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. agb@sanger.ac.uk', 'United Kingdom|United Kingdom', 22, 'Amino Acid Motifs|Amino Acid Sequence|Animals|Autoantigens|Bacterial Proteins|Carrier Proteins|Clostridium|Cyanobacteria|Cytophaga|Deinococcus|Humans|Mice|Molecular Sequence Data|Protozoan Proteins|Pseudomonas fluorescens|RNA, Small Cytoplasmic|RNA-Binding Proteins|Ribonucleoproteins|Salmonella typhimurium|Streptomyces|Telomerase|Telomere|Tetrahymena|Vault Ribonucleoprotein Particles', 'Comparative Study', '10.1186/1471-2105-4-49', '14563212', 'Ribonucleoproteins carry out a variety of important tasks in the cell. In this study we show that a number of these contain a novel module, that we speculate mediates RNA-binding.'),
(90067, 2003, 'bmc', 'Eval: a software package for analysis of genome annotations', 'Keibler, Evan|Brent, Michael R', 'Department of Computer Science and Engineering, Washington University, St, Louis, MO 63130, USA. evan@cse.wustl.edu|Department of Computer Science and Engineering, Washington University, St, Louis, MO 63130, USA. evan@cse.wustl.edu', 'United States|United States', 0, 'Computational Biology|Computer Graphics|Genome|Software', 'Comparative Study', '10.1186/1471-2105-4-50', '14565849', 'Eval is a flexible tool for analyzing the performance of gene annotation systems. It provides summaries and graphical distributions for many descriptive statistics about any set of annotations, regardless of their source. It also compares sets of predictions to standard annotations and to one another. Input is in the standard Gene Transfer Format (GTF). Eval can be run interactively or via the command line, in which case output options include easily parsable tab-delimited files.'),
(90068, 2003, 'bmc', 'LEAping to conclusions: a computational reanalysis of late embryogenesis abundant proteins and their possible roles', 'Wise, Michael J', 'Department of Genetics, Cambridge University, Cambridge, UK. mw263@cam.ac.uk', 'United Kingdom', 195, 'Algorithms|Amino Acids|Artificial Intelligence|Computational Biology|Hydrophobic and Hydrophilic Interactions|Peptides|Plant Proteins|Plant Structures|Predictive Value of Tests|Protein Structure, Secondary|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1186/1471-2105-4-52', '14583099', 'The late embryogenesis abundant (LEA) proteins cover a number of loosely related groups of proteins, originally found in plants but now being found in non-plant species. Their precise function is unknown, though considerable evidence suggests that LEA proteins are involved in desiccation resistance. Using a number of statistically-based bioinformatics tools the classification of a large set of LEA proteins, covering all Groups, is reexamined together with some previous findings. Searches based on peptide composition return proteins with similar composition to different LEA Groups, keyword clustering is then applied to reveal keywords and phrases suggestive of the Groups properties.'),
(90069, 2003, 'bmc', 'A knowledge discovery object model API for Java', 'Zuyderduyn, Scott D|Jones, Steven J M', 'Canadas Michael Smith Genome Sciences Centre, BC Cancer Agency, 600 West 10th Ave, Vancouver, Canada. scottz@bcgsc.ca|Canadas Michael Smith Genome Sciences Centre, BC Cancer Agency, 600 West 10th Ave, Vancouver, Canada. scottz@bcgsc.ca', 'Canada|Canada', 0, 'Artificial Intelligence|Computer Graphics|Database Management Systems|Databases, Genetic|Programming Languages|Software|Software Design|Systems Integration|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-4-51', '14583100', 'Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized.'),
(90070, 2003, 'bmc', 'GeneViTo: visualizing gene-product functional and structural features in genomic datasets', 'Vernikos, Georgios S|Gkogkas, Christos G|Promponas, Vasilis J|Hamodrakas, Stavros J', 'Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, 15701, Athens, Greece. gverniko@yahoo.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, 15701, Athens, Greece. gverniko@yahoo.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, 15701, Athens, Greece. gverniko@yahoo.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, 15701, Athens, Greece. gverniko@yahoo.gr', 'Greece|Greece|Greece|Greece', 10, 'Bacterial Proton-Translocating ATPases|Base Sequence|Binding Sites|Chlamydia trachomatis|Chromosome Mapping|Chromosomes, Bacterial|Computational Biology|Computer Graphics|DNA Restriction Enzymes|Databases, Genetic|Genes, Bacterial|Genes, rRNA|Genome, Bacterial|Methanococcus|Molecular Sequence Data|Phylogeny|Protein Subunits|RNA, Bacterial|RNA, Transfer|Software|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-4-53', '14594459', 'The availability of increasing amounts of sequence data from completely sequenced genomes boosts the development of new computational methods for automated genome annotation and comparative genomics. Therefore, there is a need for tools that facilitate the visualization of raw data and results produced by bioinformatics analysis, providing new means for interactive genome exploration. Visual inspection can be used as a basis to assess the quality of various analysis algorithms and to aid in-depth genomic studies.'),
(90071, 2003, 'bmc', 'PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for Arabidopsis', 'Pan, Deyun|Sun, Ning|Cheung, Kei-Hoi|Guan, Zhong|Ma, Ligeng|Holford, Matthew|Deng, Xingwang|Zhao, Hongyu', 'Division of Biostatistics, Yale University, New Haven, CT 06520, USA. deyun.pan@yale.edu|Division of Biostatistics, Yale University, New Haven, CT 06520, USA. deyun.pan@yale.edu|Division of Biostatistics, Yale University, New Haven, CT 06520, USA. deyun.pan@yale.edu|Division of Biostatistics, Yale University, New Haven, CT 06520, USA. deyun.pan@yale.edu|Division of Biostatistics, Yale University, New Haven, CT 06520, USA. deyun.pan@yale.edu|Division of Biostatistics, Yale University, New Haven, CT 06520, USA. deyun.pan@yale.edu|Division of Biostatistics, Yale University, New Haven, CT 06520, USA. deyun.pan@yale.edu|Division of Biostatistics, Yale University, New Haven, CT 06520, USA. deyun.pan@yale.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Arabidopsis|Arabidopsis Proteins|Computational Biology|Computer Graphics|Darkness|Databases, Genetic|Enzyme Activation|Gene Expression Profiling|Gene Expression Regulation, Plant|Genetic Markers|Light|Oligonucleotide Array Sequence Analysis|Phosphoric Monoester Hydrolases|Programming Languages|Ribulose-Bisphosphate Carboxylase|Software|Software Design', 'Journal Article', '10.1186/1471-2105-4-56', '14604444', 'To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis.'),
(90072, 2003, 'bmc', 'Reannotation of the CELO genome characterizes a set of previously unassigned open reading frames and points to novel modes of host interaction in avian adenoviruses', 'Washietl, Stefan|Eisenhaber, Frank', 'Research Institute of Molecular Pathology, Dr, Bohrgasse 7, A-1030 Vienna, Austria. wash@tbi.univie.ac.at|Research Institute of Molecular Pathology, Dr, Bohrgasse 7, A-1030 Vienna, Austria. wash@tbi.univie.ac.at', 'Austria|Austria', 18, 'ADP Ribose Transferases|Adenosine Triphosphatases|Adenoviridae Infections|Alphaherpesvirinae|Amino Acid Sequence|Conserved Sequence|DNA Helicases|Fowl adenovirus A|Genes, Viral|Genome, Viral|Glycoproteins|Immunoglobulins|Lipase|Membrane Proteins|Molecular Sequence Data|Open Reading Frames|Peptides|Protein Structure, Tertiary|Sequence Alignment|Sequence Homology, Amino Acid|Viral Proteins|Viral Structural Proteins', 'Journal Article', '10.1186/1471-2105-4-55', '14604445', 'The genome of the avian adenovirus Chicken Embryo Lethal Orphan (CELO) has two terminal regions without detectable homology in mammalian adenoviruses that are left without annotation in the initial analysis. Since adenoviruses have been a rich source of new insights into molecular cell biology and practical applications of CELO as gene a delivery vector are being considered, this genome appeared worth revisiting. We conducted a systematic reannotation and in-depth sequence analysis of the CELO genome.'),
(90073, 2003, 'bmc', 'Entropy-based gene ranking without selection bias for the predictive classification of microarray data', 'Furlanello, Cesare|Serafini, Maria|Merler, Stefano|Jurman, Giuseppe', 'ITC-irst, Trento, Italy. furlan@itc.it|ITC-irst, Trento, Italy. furlan@itc.it|ITC-irst, Trento, Italy. furlan@itc.it|ITC-irst, Trento, Italy. furlan@itc.it', 'Italy|Italy|Italy|Italy', 0, 'Adenocarcinoma|Algorithms|Artificial Intelligence|Colonic Neoplasms|DNA, Complementary|DNA, Neoplasm|Databases, Genetic|Entropy|Gene Expression Profiling|Genes|Genes, Neoplasm|Humans|Lymphoma|Models, Statistical|Oligonucleotide Array Sequence Analysis|Predictive Value of Tests|Reproducibility of Results|Selection Bias', 'Comparative Study', '10.1186/1471-2105-4-54', '14604446', 'We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process).'),
(90074, 2003, 'bmc', 'Online tool for the discrimination of equi-distributions', 'Pöschel, Thorsten|Frömmel, Cornelius|Gille, Christoph', 'Charité, Institut für Biochemie, Monbijoustrasse 2, D-10117, Berlin, Germany. thorsten.poeschel@charite.de|Charité, Institut für Biochemie, Monbijoustrasse 2, D-10117, Berlin, Germany. thorsten.poeschel@charite.de|Charité, Institut für Biochemie, Monbijoustrasse 2, D-10117, Berlin, Germany. thorsten.poeschel@charite.de', 'Germany|Germany|Germany', 1, 'Amino Acid Sequence|Cystic Fibrosis Transmembrane Conductance Regulator|Genes|Internet|Models, Statistical|Molecular Sequence Data|Online Systems|Point Mutation|Polymorphism, Genetic|Software|Statistical Distributions', 'Journal Article', '10.1186/1471-2105-4-58', '14629779', 'For many applications one wishes to decide whether a certain set of numbers originates from an equiprobability distribution or whether they are unequally distributed. Distributions of relative frequencies may deviate significantly from the corresponding probability distributions due to finite sample effects. Hence, it is not trivial to discriminate between an equiprobability distribution and non-equally distributed probabilities when knowing only frequencies.'),
(90075, 2003, 'bmc', 'Conservation of regulatory elements between two species of Drosophila', 'Emberly, Eldon|Rajewsky, Nikolaus|Siggia, Eric D', 'Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY, USA. eemberly@edsc.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY, USA. eemberly@edsc.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY, USA. eemberly@edsc.rockefeller.edu', 'United States|United States|United States', 0, 'Algorithms|Animals|Base Composition|Binding Sites|Computational Biology|Conserved Sequence|Databases, Genetic|Drosophila|Drosophila melanogaster|Genes, Insect|Genes, Regulator|Genetic Markers|Sequence Alignment|Species Specificity', 'Journal Article', '10.1186/1471-2105-4-57', '14629780', 'One of the important goals in the post-genomic era is to determine the regulatory elements within the non-coding DNA of a given organisms genome. The identification of functional cis-regulatory modules has proven difficult since the component factor binding sites are small and the rules governing their arrangement are poorly understood. However, the genomes of suitably diverged species help to predict regulatory elements based on the generally accepted assumption that conserved blocks of genomic sequence are likely to be functional. To judge the efficacy of strategies that prefilter by sequence conservation it is important to know to what extent the converse assumption holds, namely that functional elements common to both species will fall within these conserved blocks. The recently completed sequence of a second Drosophila species provides an opportunity to test this assumption for one of the experimentally best studied regulatory networks in multicellular organisms, the body patterning of the fly embryo.'),
(90076, 2003, 'bmc', 'Cross-platform comparison and visualisation of gene expression data using co-inertia analysis', 'Culhane, Aedín C|Perrière, Guy|Higgins, Desmond G', 'Department of Biochemistry, Biosciences Institute, University College Cork, Cork, Ireland. Aedin.Culhane@ucd.ie|Department of Biochemistry, Biosciences Institute, University College Cork, Cork, Ireland. Aedin.Culhane@ucd.ie|Department of Biochemistry, Biosciences Institute, University College Cork, Cork, Ireland. Aedin.Culhane@ucd.ie', 'Ireland|Ireland|Ireland', 102, 'Breast Neoplasms|Carcinoma, Non-Small-Cell Lung|Cell Line|Cell Line, Tumor|Central Nervous System Neoplasms|Computational Biology|Computer Graphics|Databases, Genetic|Epithelial Cells|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Glioblastoma|HT29 Cells|Humans|Kidney Neoplasms|Leukemia|Lung Neoplasms|Melanoma|Mesoderm|Models, Statistical', 'Comparative Study', '10.1186/1471-2105-4-59', '14633289', 'Rapid development of DNA microarray technology has resulted in different laboratories adopting numerous different protocols and technological platforms, which has severely impacted on the comparability of array data. Current cross-platform comparison of microarray gene expression data are usually based on cross-referencing the annotation of each gene transcript represented on the arrays, extracting a list of genes common to all arrays and comparing expression data of this gene subset. Unfortunately, filtering of genes to a subset represented across all arrays often excludes many thousands of genes, because different subsets of genes from the genome are represented on different arrays. We wish to describe the application of a powerful yet simple method for cross-platform comparison of gene expression data. Co-inertia analysis (CIA) is a multivariate method that identifies trends or co-relationships in multiple datasets which contain the same samples. CIA simultaneously finds ordinations (dimension reduction diagrams) from the datasets that are most similar. It does this by finding successive axes from the two datasets with maximum covariance. CIA can be applied to datasets where the number of variables (genes) far exceeds the number of samples (arrays) such is the case with microarray analyses.'),
(90077, 2003, 'bmc', 'Tumor classification and marker gene prediction by feature selection and fuzzy c-means clustering using microarray data', 'Wang, Junbai|Bø, Trond Hellem|Jonassen, Inge|Myklebost, Ola|Hovig, Eivind', 'Department of Tumor Biology, The Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, The Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, The Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, The Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, The Norwegian Radium Hospital, N0310 Oslo, Norway. junbaiw@radium.uio.no', 'Norway|Norway|Norway|Norway|Norway', 65, 'Biomarkers, Tumor|Brain Neoplasms|Cell Line, Tumor|Chromosome Mapping|Cluster Analysis|Colonic Neoplasms|Computational Biology|Female|Fuzzy Logic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Humans|Leukemia|Neoplasms|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Predictive Value of Tests', 'Comparative Study', '10.1186/1471-2105-4-60', '14651757', 'Using DNA microarrays, we have developed two novel models for tumor classification and target gene prediction. First, gene expression profiles are summarized by optimally selected Self-Organizing Maps (SOMs), followed by tumor sample classification by Fuzzy C-means clustering. Then, the prediction of marker genes is accomplished by either manual feature selection (visualizing the weighted/mean SOM component plane) or automatic feature selection (by pair-wise Fishers linear discriminant).'),
(90078, 2003, 'bmc', 'Statistical significance for hierarchical clustering in genetic association and microarray expression studies', 'Levenstien, Mark A|Yang, Yaning|Ott, Jürg', 'Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, United States. markl@linkage.rockefeller.edu|Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, United States. markl@linkage.rockefeller.edu|Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, United States. markl@linkage.rockefeller.edu', 'United States|United States|United States', 0, 'Cluster Analysis|Confidence Intervals|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Predisposition to Disease|Haplotypes|Humans|Linkage Disequilibrium|Lung Neoplasms|Lymphoma|Models, Statistical|Oligonucleotide Array Sequence Analysis|Substance-Related Disorders', 'Journal Article', '10.1186/1471-2105-4-62', '14667254', 'With the increasing amount of data generated in molecular genetics laboratories, it is often difficult to make sense of results because of the vast number of different outcomes or variables studied. Examples include expression levels for large numbers of genes and haplotypes at large numbers of loci. It is then natural to group observations into smaller numbers of classes that allow for an easier overview and interpretation of the data. This grouping is often carried out in multiple steps with the aid of hierarchical cluster analysis, each step leading to a smaller number of classes by combining similar observations or classes. At each step, either implicitly or explicitly, researchers tend to interpret results and eventually focus on that set of classes providing the best (most significant) result. While this approach makes sense, the overall statistical significance of the experiment must include the clustering process, which modifies the grouping structure of the data and often removes variation.'),
(90079, 2003, 'bmc', 'PubMatrix: a tool for multiplex literature mining', 'Becker, Kevin G|Hosack, Douglas A|Dennis, Glynn|Lempicki, Richard A|Bright, Tiffani J|Cheadle, Chris|Engel, Jim', 'Gene Expression and Genomics Unit, National Institutes of Health, Baltimore, MD, USA. beckerk@grc.nia.nih.gov|Gene Expression and Genomics Unit, National Institutes of Health, Baltimore, MD, USA. beckerk@grc.nia.nih.gov|Gene Expression and Genomics Unit, National Institutes of Health, Baltimore, MD, USA. beckerk@grc.nia.nih.gov|Gene Expression and Genomics Unit, National Institutes of Health, Baltimore, MD, USA. beckerk@grc.nia.nih.gov|Gene Expression and Genomics Unit, National Institutes of Health, Baltimore, MD, USA. beckerk@grc.nia.nih.gov|Gene Expression and Genomics Unit, National Institutes of Health, Baltimore, MD, USA. beckerk@grc.nia.nih.gov|Gene Expression and Genomics Unit, National Institutes of Health, Baltimore, MD, USA. beckerk@grc.nia.nih.gov', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Cell Line, Tumor|Cisplatin|Computational Biology|Computer Graphics|Databases, Genetic|Drug Resistance, Neoplasm|Female|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Neoplastic|Genes|Genes, Neoplasm|Genomics|Humans|Internet|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Proteomics|PubMed|Software', 'Comparative Study', '10.1186/1471-2105-4-61', '14667255', 'Molecular experiments using multiplex strategies such as cDNA microarrays or proteomic approaches generate large datasets requiring biological interpretation. Text based data mining tools have recently been developed to query large biological datasets of this type of data. PubMatrix is a web-based tool that allows simple text based mining of the NCBI literature search service PubMed using any two lists of keywords terms, resulting in a frequency matrix of term co-occurrence.'),
(90080, 2003, 'bmc', 'AnaBench: a Web/CORBA-based workbench for biomolecular sequence analysis', 'Badidi, Elarbi|De Sousa, Cristina|Lang, B Franz|Burger, Gertraud', 'The Canadian Institute for Advanced Research, Program in Evolutionary Biology, Département de Biochimie, Université de Montréal, 2900, Boul, Edouard Montpetit, Montréal, QC H3T 1J4, Canada. me.badidi@umontreal.ca|The Canadian Institute for Advanced Research, Program in Evolutionary Biology, Département de Biochimie, Université de Montréal, 2900, Boul, Edouard Montpetit, Montréal, QC H3T 1J4, Canada. me.badidi@umontreal.ca|The Canadian Institute for Advanced Research, Program in Evolutionary Biology, Département de Biochimie, Université de Montréal, 2900, Boul, Edouard Montpetit, Montréal, QC H3T 1J4, Canada. me.badidi@umontreal.ca|The Canadian Institute for Advanced Research, Program in Evolutionary Biology, Département de Biochimie, Université de Montréal, 2900, Boul, Edouard Montpetit, Montréal, QC H3T 1J4, Canada. me.badidi@umontreal.ca', 'Canada|Canada|Canada|Canada', 20, 'Computational Biology|Computer Graphics|Database Management Systems|Databases, Genetic|Humans|Internet|Nucleic Acids|Phylogeny|Programming Languages|Proteins|Sequence Analysis|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-4-63', '14678565', 'Sequence data analyses such as gene identification, structure modeling or phylogenetic tree inference involve a variety of bioinformatics software tools. Due to the heterogeneity of bioinformatics tools in usage and data requirements, scientists spend much effort on technical issues including data format, storage and management of input and output, and memorization of numerous parameters and multi-step analysis procedures.'),
(90081, 2003, 'bmc', 'The PAM domain, a multi-protein complex-associated module with an all-alpha-helix fold', 'Ciccarelli, Francesca D|Izaurralde, Elisa|Bork, Peer', 'European Molecular Biology Laboratory, Meyerhofstr, 1, 69012 Heidelberg, Germany. francesca.ciccarelli@embl.de|European Molecular Biology Laboratory, Meyerhofstr, 1, 69012 Heidelberg, Germany. francesca.ciccarelli@embl.de|European Molecular Biology Laboratory, Meyerhofstr, 1, 69012 Heidelberg, Germany. francesca.ciccarelli@embl.de', 'Germany|Germany|Germany', 0, 'Amino Acid Sequence|Animals|Anopheles|Arabidopsis Proteins|COP9 Signalosome Complex|Cell Cycle Proteins|Consensus Sequence|Drosophila Proteins|Helix-Loop-Helix Motifs|Humans|Macromolecular Substances|Molecular Sequence Data|Multienzyme Complexes|Multiprotein Complexes|Neurospora crassa|Nuclear Proteins|Peptide Hydrolases|Phylogeny|Proteasome Endopeptidase Complex|Protein Kinases|Protein-Serine-Threonine Kinases|Repressor Proteins|Ribonucleoproteins|Saccharomyces cerevisiae Proteins|Schizosaccharomyces pombe Proteins|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-4-64', '14687415', 'Multimeric protein complexes have a role in many cellular pathways and are highly interconnected with various other proteins. The characterization of their domain composition and organization provides useful information on the specific role of each region of their sequence.'),
(90082, 2003, 'bmc', 'Statistical extraction of Drosophila cis-regulatory modules using exhaustive assessment of local word frequency', 'Nazina, Anna G|Papatsenko, Dmitri A', 'Department of Biology, New York University, New York, USA. agn202@nyu.edu|Department of Biology, New York University, New York, USA. agn202@nyu.edu', 'United States|United States', 20, 'Animals|Computational Biology|DNA|DNA Footprinting|Drosophila melanogaster|Gene Expression Profiling|Gene Expression Regulation, Developmental|Genome|Internet|Phylogeny|Regulatory Sequences, Nucleic Acid', 'Comparative Study', '10.1186/1471-2105-4-65', '14690551', 'Transcription regulatory regions in higher eukaryotes are often represented by cis-regulatory modules (CRM) and are responsible for the formation of specific spatial and temporal gene expression patterns. These extended, approximately 1 KB, regions are found far from coding sequences and cannot be extracted from genome on the basis of their relative position to the coding regions.'),
(90083, 2003, 'bmc', 'Fast and sensitive multiple alignment of large genomic sequences', 'Brudno, Michael|Chapman, Michael|Göttgens, Berthold|Batzoglou, Serafim|Morgenstern, Burkhard', 'Department of Computer Science, Stanford University, Stanford, CA 94305, USA. brudno@cs.stanford.edu|Department of Computer Science, Stanford University, Stanford, CA 94305, USA. brudno@cs.stanford.edu|Department of Computer Science, Stanford University, Stanford, CA 94305, USA. brudno@cs.stanford.edu|Department of Computer Science, Stanford University, Stanford, CA 94305, USA. brudno@cs.stanford.edu|Department of Computer Science, Stanford University, Stanford, CA 94305, USA. brudno@cs.stanford.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Chickens|Computational Biology|DNA, Neoplasm|Genes, Neoplasm|Genome|Humans|Leukemia|Mice|Rats|Regulatory Sequences, Nucleic Acid|Sensitivity and Specificity|Sequence Alignment|Software|Software Validation|Stem Cells|Tetraodontiformes|Zebrafish', 'Comparative Study', '10.1186/1471-2105-4-66', '14693042', 'Genomic sequence alignment is a powerful method for genome analysis and annotation, as alignments are routinely used to identify functional sites such as genes or regulatory elements. With a growing number of partially or completely sequenced genomes, multiple alignment is playing an increasingly important role in these studies. In recent years, various tools for pair-wise and multiple genomic alignment have been proposed. Some of them are extremely fast, but often efficiency is achieved at the expense of sensitivity. One way of combining speed and sensitivity is to use an anchored-alignment approach. In a first step, a fast search program identifies a chain of strong local sequence similarities. In a second step, regions between these anchor points are aligned using a slower but more accurate method.'),
(90084, 2004, 'bmc', 'PyEvolve: a toolkit for statistical modelling of molecular evolution', 'Butterfield, Andrew|Vedagiri, Vivek|Lang, Edward|Lawrence, Cath|Wakefield, Matthew J|Isaev, Alexander|Huttley, Gavin A', 'Centre for Bioinformation Science, John Curtin School of Medical Research and Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. andrew.butterfield@anu.edu.au|Centre for Bioinformation Science, John Curtin School of Medical Research and Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. andrew.butterfield@anu.edu.au|Centre for Bioinformation Science, John Curtin School of Medical Research and Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. andrew.butterfield@anu.edu.au|Centre for Bioinformation Science, John Curtin School of Medical Research and Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. andrew.butterfield@anu.edu.au|Centre for Bioinformation Science, John Curtin School of Medical Research and Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. andrew.butterfield@anu.edu.au|Centre for Bioinformation Science, John Curtin School of Medical Research and Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. andrew.butterfield@anu.edu.au|Centre for Bioinformation Science, John Curtin School of Medical Research and Mathematical Sciences Institute, Australian National University, Canberra, ACT 0200, Australia. andrew.butterfield@anu.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Animals|Benchmarking|Evolution, Molecular|Gorilla gorilla|Humans|Likelihood Functions|Mice|Models, Genetic|Mutagenesis|Pan troglodytes|Rats|Software|Software Design', 'Comparative Study', '10.1186/1471-2105-5-1', '14706121', 'Examining the distribution of variation has proven an extremely profitable technique in the effort to identify sequences of biological significance. Most approaches in the field, however, evaluate only the conserved portions of sequences - ignoring the biological significance of sequence differences. A suite of sophisticated likelihood based statistical models from the field of molecular evolution provides the basis for extracting the information from the full distribution of sequence variation. The number of different problems to which phylogeny-based maximum likelihood calculations can be applied is extensive. Available software packages that can perform likelihood calculations suffer from a lack of flexibility and scalability, or employ error-prone approaches to model parameterisation.'),
(90085, 2004, 'bmc', 'Identification of polymorphic tandem repeats by direct comparison of genome sequence from different bacterial strains: a web-based resource', 'Denoeud, France|Vergnaud, Gilles', 'Laboratoire GPMS, Institut de Génétique et Microbiologie, Bat 400, Université Paris-Sud, 91405 Orsay cedex, France. France.Denoeud@igmors.u-psud.fr|Laboratoire GPMS, Institut de Génétique et Microbiologie, Bat 400, Université Paris-Sud, 91405 Orsay cedex, France. France.Denoeud@igmors.u-psud.fr', 'France|France', 89, 'Bacteria|Bacterial Typing Techniques|DNA, Bacterial|DNA, Viral|Databases, Genetic|Genome, Bacterial|Genome, Viral|Gram-Negative Aerobic Bacteria|Gram-Negative Bacteria|Gram-Negative Facultatively Anaerobic Rods|Gram-Positive Cocci|Internet|Listeria|Orthopoxvirus|Polymorphism, Genetic|Sensitivity and Specificity|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Species Specificity|Tandem Repeat Sequences', 'Comparative Study', '10.1186/1471-2105-5-4', '14715089', 'Polymorphic tandem repeat typing is a new generic technology which has been proved to be very efficient for bacterial pathogens such as B. anthracis, M. tuberculosis, P. aeruginosa, L. pneumophila, Y. pestis. The previously developed tandem repeats database takes advantage of the release of genome sequence data for a growing number of bacteria to facilitate the identification of tandem repeats. The development of an assay then requires the evaluation of tandem repeat polymorphism on well-selected sets of isolates. In the case of major human pathogens, such as S. aureus, more than one strain is being sequenced, so that tandem repeats most likely to be polymorphic can now be selected in silico based on genome sequence comparison.'),
(90086, 2004, 'bmc', 'VKCDB: voltage-gated potassium channel database', 'Li, Bin|Gallin, Warren J', 'Department of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canada. bli@ualberta.ca|Department of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canada. bli@ualberta.ca', 'Canada|Canada', 18, 'Animals|Databases, Protein|Humans|Potassium Channels, Voltage-Gated', 'Journal Article', '10.1186/1471-2105-5-3', '14715090', 'The family of voltage-gated potassium channels comprises a functionally diverse group of membrane proteins. They help maintain and regulate the potassium ion-based component of the membrane potential and are thus central to many critical physiological processes. VKCDB (Voltage-gated potassium [K] Channel DataBase) is a database of structural and functional data on these channels. It is designed as a resource for research on the molecular basis of voltage-gated potassium channel function.'),
(90087, 2004, 'bmc', 'Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures', 'Alexandrov, Vadim|Gerstein, Mark', 'Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Ave, New Haven, CT 06511, USA. vadim.alexandrov@yale.edu|Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Ave, New Haven, CT 06511, USA. vadim.alexandrov@yale.edu', 'United States|United States', 0, 'Algorithms|Computational Biology|Flavin-Adenine Dinucleotide|Flavodoxin|Imaging, Three-Dimensional|Immunoglobulins|Markov Chains|Models, Molecular|Muramidase|NAD|Protein Folding|Protein Structure, Quaternary|Sequence Alignment|Thioredoxins', 'Comparative Study', '10.1186/1471-2105-5-2', '14715091', 'Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction. Thus far, however, they have been confined to representing 1D sequence (or the aspects of structure that could be represented by character strings).'),
(90088, 2004, 'bmc', 'Three-parameter lognormal distribution ubiquitously found in cDNA microarray data and its application to parametric data treatment', 'Konishi, Tomokazu', 'Faculty of Bioresource Sciences, Akita Prefectural University, Akita 010-0195, Japan. konishi@akita-pu.ac.jp', 'Japan', 43, 'Blotting, Northern|DNA, Complementary|Data Interpretation, Statistical|Fibroblasts|Gene Expression Profiling|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|Oryza|RNA, Plant|Reproducibility of Results|Seeds|Statistical Distributions', 'Comparative Study', '10.1186/1471-2105-5-5', '14718068', 'To cancel experimental variations, microarray data must be normalized prior to analysis. Where an appropriate model for statistical data distribution is available, a parametric method can normalize a group of data sets that have common distributions. Although such models have been proposed for microarray data, they have not always fit the distribution of real data and thus have been inappropriate for normalization. Consequently, microarray data in most cases have been normalized with non-parametric methods that adjust data in a pair-wise manner. However, data analysis and the integration of resultant knowledge among experiments have been difficult, since such normalization concepts lack a universal standard.'),
(90089, 2004, 'bmc', 'HMM Logos for visualization of protein families', 'Schuster-Böckler, Benjamin|Schultz, Jörg|Rahmann, Sven', 'Department of Mathematics and Computer Science, Freie Universität Berlin, Germany. bendaboots@gmx.de|Department of Mathematics and Computer Science, Freie Universität Berlin, Germany. bendaboots@gmx.de|Department of Mathematics and Computer Science, Freie Universität Berlin, Germany. bendaboots@gmx.de', 'Germany|Germany|Germany', 0, 'Amino Acid Motifs|Computational Biology|Computer Graphics|Databases, Protein|Markov Chains|Monomeric GTP-Binding Proteins|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-5-7', '14736340', 'Profile Hidden Markov Models (pHMMs) are a widely used tool for protein family research. Up to now, however, there exists no method to visualize all of their central aspects graphically in an intuitively understandable way.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90090, 2004, 'bmc', 'Benchmarking tools for the alignment of functional noncoding DNA', 'Pollard, Daniel A|Bergman, Casey M|Stoye, Jens|Celniker, Susan E|Eisen, Michael B', 'Biophysics Graduate Group, University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu|Biophysics Graduate Group, University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu|Biophysics Graduate Group, University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu|Biophysics Graduate Group, University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu|Biophysics Graduate Group, University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu', 'United States|United States|United States|United States|United States', 97, 'Animals|Benchmarking|Caenorhabditis|Caenorhabditis elegans|Computer Simulation|DNA, Helminth|DNA, Intergenic|Drosophila|Drosophila melanogaster|Evolution, Molecular|Genomics|Humans|Mice|Sensitivity and Specificity|Sequence Alignment|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1186/1471-2105-5-6', '14736341', 'Numerous tools have been developed to align genomic sequences. However, their relative performance in specific applications remains poorly characterized. Alignments of protein-coding sequences typically have been benchmarked against correct alignments inferred from structural data. For noncoding sequences, where such independent validation is lacking, simulation provides an effective means to generate correct alignments with which to benchmark alignment tools.'),
(90091, 2004, 'bmc', 'GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies', 'Zhang, Bing|Schmoyer, Denise|Kirov, Stefan|Snoddy, Jay', 'Graduate School in Genome Science and Technology, University of Tennessee-Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. zhangb@ornl.gov|Graduate School in Genome Science and Technology, University of Tennessee-Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. zhangb@ornl.gov|Graduate School in Genome Science and Technology, University of Tennessee-Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. zhangb@ornl.gov|Graduate School in Genome Science and Technology, University of Tennessee-Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. zhangb@ornl.gov', 'United States|United States|United States|United States', 354, 'Animals|Cluster Analysis|Computational Biology|Computer Graphics|Data Interpretation, Statistical|Databases, Genetic|Diptera|Gene Expression Profiling|Genes|Genes, Insect|Genome|Genome, Human|Humans|Internet|Mice|Oligonucleotide Array Sequence Analysis|Rats|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-5-16', '14975175', 'Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets.'),
(90092, 2004, 'bmc', 'An XML standard for the dissemination of annotated 2D gel electrophoresis data complemented with mass spectrometry results', 'Stanislaus, Romesh|Jiang, Liu Hong|Swartz, Martha|Arthur, John|Almeida, Jonas S', 'Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA. stanisrc@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA. stanisrc@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA. stanisrc@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA. stanisrc@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, Charleston, South Carolina, USA. stanisrc@musc.edu', 'United States|United States|United States|United States|United States', 0, 'Computational Biology|Computer Graphics|Electrophoresis, Gel, Two-Dimensional|Humans|Mass Spectrometry|Models, Theoretical|Programming Languages|Proteomics|Reference Standards|Software|Terminology as Topic|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-5-9', '15005801', 'Many proteomics initiatives require a seamless bioinformatics integration of a range of analytical steps between sample collection and systems modeling immediately assessable to the participants involved in the process. Proteomics profiling by 2D gel electrophoresis to the putative identification of differentially expressed proteins by comparison of mass spectrometry results with reference databases, includes many components of sample processing, not just analysis and interpretation, are regularly revisited and updated. In order for such updates and dissemination of data, a suitable data structure is needed. However, there are no such data structures currently available for the storing of data for multiple gels generated through a single proteomic experiments in a single XML file. This paper proposes a data structure based on XML standards to fill the void that exists between data generated by proteomics experiments and storing of data.'),
(90093, 2004, 'bmc', 'FRAGS: estimation of coding sequence substitution rates from fragmentary data', 'Swart, Estienne C|Hide, Winston A|Seoighe, Cathal', 'South African National Bioinformatics Institute, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa. estienne@sanbi.ac.za|South African National Bioinformatics Institute, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa. estienne@sanbi.ac.za|South African National Bioinformatics Institute, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa. estienne@sanbi.ac.za', 'South Africa|South Africa|South Africa', 3, 'Animals|Computational Biology|Databases, Genetic|Humans|Models, Genetic|Models, Statistical|Mutagenesis|Pan troglodytes|RNA, Messenger|Software', 'Journal Article', '10.1186/1471-2105-5-8', '15005802', 'Rates of substitution in protein-coding sequences can provide important insights into evolutionary processes that are of biomedical and theoretical interest. Increased availability of coding sequence data has enabled researchers to estimate more accurately the coding sequence divergence of pairs of organisms. However the use of different data sources, alignment protocols and methods to estimate substitution rates leads to widely varying estimates of key parameters that define the coding sequence divergence of orthologous genes. Although complete genome sequence data are not available for all organisms, fragmentary sequence data can provide accurate estimates of substitution rates provided that an appropriate and consistent methodology is used and that differences in the estimates obtainable from different data sources are taken into account.'),
(90094, 2004, 'bmc', 'Array-A-Lizer: a serial DNA microarray quality analyzer', 'Petri, Andreas|Fleckner, Jan|Matthiessen, Mads Wichmann', 'Department of Molecular Genetics, Novo Nordisk A/S, Bagsvaerd, 2880, Denmark. andp@novonordisk.com|Department of Molecular Genetics, Novo Nordisk A/S, Bagsvaerd, 2880, Denmark. andp@novonordisk.com|Department of Molecular Genetics, Novo Nordisk A/S, Bagsvaerd, 2880, Denmark. andp@novonordisk.com', 'Denmark|Denmark|Denmark', 11, 'Computer Graphics|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Quality Control|Software|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-5-12', '15018654', 'The proliferate nature of DNA microarray results have made it necessary to implement a uniform and quick quality control of experimental results to ensure the consistency of data across multiple experiments prior to actual data analysis.'),
(90095, 2004, 'bmc', 'MuTrack: a genome analysis system for large-scale mutagenesis in the mouse', 'Baker, Erich J|Galloway, Leslie|Jackson, Barbara|Schmoyer, Denise|Snoddy, Jay', 'Department of Computer Science, Baylor University, Waco, USA. Erich_Baker@Baylor.edu|Department of Computer Science, Baylor University, Waco, USA. Erich_Baker@Baylor.edu|Department of Computer Science, Baylor University, Waco, USA. Erich_Baker@Baylor.edu|Department of Computer Science, Baylor University, Waco, USA. Erich_Baker@Baylor.edu|Department of Computer Science, Baylor University, Waco, USA. Erich_Baker@Baylor.edu', 'United States|United States|United States|United States|United States', 18, 'Animals|DNA Mutational Analysis|Genome|Humans|Mice|Mutagenesis|Software', 'Journal Article', '10.1186/1471-2105-5-11', '15018655', 'Modern biological research makes possible the comprehensive study and development of heritable mutations in the mouse model at high-throughput. Using techniques spanning genetics, molecular biology, histology, and behavioral science, researchers may examine, with varying degrees of granularity, numerous phenotypic aspects of mutant mouse strains directly pertinent to human disease states. Success of these and other genome-wide endeavors relies on a well-structured bioinformatics core that brings together investigators from widely dispersed institutions and enables them to seamlessly integrate data, observations and discussions.'),
(90096, 2004, 'bmc', 'Aggregation of topological motifs in the Escherichia coli transcriptional regulatory network', 'Dobrin, Radu|Beg, Qasim K|Barabási, Albert-László|Oltvai, Zoltán N', 'Department of Pathology, Northwestern University, Chicago, IL 60611, USA. r-dobrin@northwestern.edu|Department of Pathology, Northwestern University, Chicago, IL 60611, USA. r-dobrin@northwestern.edu|Department of Pathology, Northwestern University, Chicago, IL 60611, USA. r-dobrin@northwestern.edu|Department of Pathology, Northwestern University, Chicago, IL 60611, USA. r-dobrin@northwestern.edu', 'United States|United States|United States|United States', 171, 'Base Composition|Cluster Analysis|Computational Biology|DNA, Bacterial|Escherichia coli|Genes, Bacterial|Genes, Regulator|Sequence Homology, Nucleic Acid|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-5-10', '15018656', 'Transcriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes and operons regulated by them. To better understand the system-level function of such networks simplification of their architecture was previously achieved by identifying the motifs present in the network, which are small, overrepresented, topologically distinct regulatory interaction patterns (subgraphs). However, the interaction of such motifs with each other, and their form of integration into the full network has not been previously examined.'),
(90097, 2004, 'bmc', 'VisANT: an online visualization and analysis tool for biological interaction data', 'Hu, Zhenjun|Mellor, Joseph|Wu, Jie|DeLisi, Charles', 'Bioinformatics Program, Boston University, Boston, MA 02215, USA. zjhu@bu.edu|Bioinformatics Program, Boston University, Boston, MA 02215, USA. zjhu@bu.edu|Bioinformatics Program, Boston University, Boston, MA 02215, USA. zjhu@bu.edu|Bioinformatics Program, Boston University, Boston, MA 02215, USA. zjhu@bu.edu', 'United States|United States|United States|United States', 170, 'Animals|Computational Biology|Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Genes, Fungal|Genes, Helminth|Helminth Proteins|Humans|Mice|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software|Software Design|Transcription Factors|Transcription, Genetic|Two-Hybrid System Techniques', 'Comparative Study', '10.1186/1471-2105-5-17', '15028117', 'New techniques for determining relationships between biomolecules of all types--genes, proteins, noncoding DNA, metabolites and small molecules--are now making a substantial contribution to the widely discussed explosion of facts about the cell. The data generated by these techniques promote a picture of the cell as an interconnected information network, with molecular components linked with one another in topologies that can encode and represent many features of cellular function. This networked view of biology brings the potential for systematic understanding of living molecular systems.'),
(90098, 2004, 'bmc', 'The tissue microarray data exchange specification: implementation by the Cooperative Prostate Cancer Tissue Resource', 'Berman, Jules J|Datta, Milton|Kajdacsy-Balla, Andre|Melamed, Jonathan|Orenstein, Jan|Dobbin, Kevin|Patel, Ashok|Dhir, Rajiv|Becich, Michael J', 'Cancer Diagnosis Program, National Cancer Institute, National Institutes of Health, Bethesda, USA. bermanj@mail.nih.gov|Cancer Diagnosis Program, National Cancer Institute, National Institutes of Health, Bethesda, USA. bermanj@mail.nih.gov|Cancer Diagnosis Program, National Cancer Institute, National Institutes of Health, Bethesda, USA. bermanj@mail.nih.gov|Cancer Diagnosis Program, National Cancer Institute, National Institutes of Health, Bethesda, USA. bermanj@mail.nih.gov|Cancer Diagnosis Program, National Cancer Institute, National Institutes of Health, Bethesda, USA. bermanj@mail.nih.gov|Cancer Diagnosis Program, National Cancer Institute, National Institutes of Health, Bethesda, USA. bermanj@mail.nih.gov|Cancer Diagnosis Program, National Cancer Institute, National Institutes of Health, Bethesda, USA. bermanj@mail.nih.gov|Cancer Diagnosis Program, National Cancer Institute, National Institutes of Health, Bethesda, USA. bermanj@mail.nih.gov|Cancer Diagnosis Program, National Cancer Institute, National Institutes of Health, Bethesda, USA. bermanj@mail.nih.gov', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 35, 'Confidentiality|Cooperative Behavior|Databases, Genetic|Gene Expression Profiling|Humans|Information Management|Internet|Male|Oligonucleotide Array Sequence Analysis|Prostatic Neoplasms', 'Journal Article', '10.1186/1471-2105-5-19', '15040818', 'Tissue Microarrays (TMAs) have emerged as a powerful tool for examining the distribution of marker molecules in hundreds of different tissues displayed on a single slide. TMAs have been used successfully to validate candidate molecules discovered in gene array experiments. Like gene expression studies, TMA experiments are data intensive, requiring substantial information to interpret, replicate or validate. Recently, an open access Tissue Microarray Data Exchange Specification has been released that allows TMA data to be organized in a self-describing XML document annotated with well-defined common data elements. While this specification provides sufficient information for the reproduction of the experiment by outside research groups, its initial description did not contain instructions or examples of actual implementations, and no implementation studies have been published. The purpose of this paper is to demonstrate how the TMA Data Exchange Specification is implemented in a prostate cancer TMA.'),
(90099, 2004, 'bmc', 'SeeGH--a software tool for visualization of whole genome array comparative genomic hybridization data', 'Chi, Bryan|DeLeeuw, Ronald J|Coe, Bradley P|MacAulay, Calum|Lam, Wan L', 'British Columbia Cancer Research Centre, British Columbia Cancer Agency, 601 W, 10th Ave, Vancouver, BC, V5Z 1L3 Canada. bchi@bccrc.ca|British Columbia Cancer Research Centre, British Columbia Cancer Agency, 601 W, 10th Ave, Vancouver, BC, V5Z 1L3 Canada. bchi@bccrc.ca|British Columbia Cancer Research Centre, British Columbia Cancer Agency, 601 W, 10th Ave, Vancouver, BC, V5Z 1L3 Canada. bchi@bccrc.ca|British Columbia Cancer Research Centre, British Columbia Cancer Agency, 601 W, 10th Ave, Vancouver, BC, V5Z 1L3 Canada. bchi@bccrc.ca|British Columbia Cancer Research Centre, British Columbia Cancer Agency, 601 W, 10th Ave, Vancouver, BC, V5Z 1L3 Canada. bchi@bccrc.ca', 'Canada|Canada|Canada|Canada|Canada', 73, 'Chromosome Mapping|Computer Graphics|DNA, Complementary|Data Interpretation, Statistical|Database Management Systems|Gene Dosage|Genome, Human|Humans|Information Storage and Retrieval|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Software|Software Design|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-5-13', '15040819', 'Array comparative genomic hybridization (CGH) is a technique which detects copy number differences in DNA segments. Complete sequencing of the human genome and the development of an array representing a tiling set of tens of thousands of DNA segments spanning the entire human genome has made high resolution copy number analysis throughout the genome possible. Since array CGH provides signal ratio for each DNA segment, visualization would require the reassembly of individual data points into chromosome profiles.'),
(90100, 2004, 'bmc', 'Selection of informative clusters from hierarchical cluster tree with gene classes', 'Toronen, Petri', 'A. I. Virtanen Institute for Molecular Sciences, Neulaniementie 2, P.O. Box 1627, FIN-70211 Kuopio, Finland. toronen@hytti.uku.fi', 'Finland', 40, 'Cluster Analysis|Computational Biology|Gene Expression Profiling|Gene Expression Regulation, Fungal|Genes, Fungal|Random Allocation|Saccharomyces cerevisiae', 'Comparative Study', '10.1186/1471-2105-5-32', '15043761', 'A common clustering method in the analysis of gene expression data has been hierarchical clustering. Usually the analysis involves selection of clusters by cutting the tree at a suitable level and/or analysis of a sorted gene list that is obtained with the tree. Cutting of the hierarchical tree requires the selection of a suitable level and it results in the loss of information on the other level. Sorted gene lists depend on the sorting method of the joined clusters. Author proposes that the clusters should be selected using the gene classifications.'),
(90101, 2004, 'bmc', 'A SNP-centric database for the investigation of the human genome', 'Riva, Alberto|Kohane, Isaac S', 'Childrens Hospital Informatics Program, Childrens Hospital Boston, 320 Longwood, Avenue, Boston, MA 02115, USA. alberto.riva@tch.harvard.edu|Childrens Hospital Informatics Program, Childrens Hospital Boston, 320 Longwood, Avenue, Boston, MA 02115, USA. alberto.riva@tch.harvard.edu', 'United States|United States', 67, 'Databases, Genetic|Genome, Human|Genomics|Humans|Internet|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-5-33', '15046636', 'Single Nucleotide Polymorphisms (SNPs) are an increasingly important tool for genetic and biomedical research. Although current genomic databases contain information on several million SNPs and are growing at a very fast rate, the true value of a SNP in this context is a function of the quality of the annotations that characterize it. Retrieving and analyzing such data for a large number of SNPs often represents a major bottleneck in the design of large-scale association studies.'),
(90102, 2004, 'bmc', 'Iterative Group Analysis (iGA): a simple tool to enhance sensitivity and facilitate interpretation of microarray experiments', 'Breitling, Rainer|Amtmann, Anna|Herzyk, Pawel', 'Plant Science Group, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom. r.breitling@bio.gla.ac.uk|Plant Science Group, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom. r.breitling@bio.gla.ac.uk|Plant Science Group, Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom. r.breitling@bio.gla.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 110, 'Animals|Arabidopsis|Computational Biology|Confidence Intervals|Gene Expression Profiling|Genes|Genes, Plant|Genome|Genome, Human|Genome, Plant|Humans|Mice|Oligonucleotide Array Sequence Analysis|Rats|Sensitivity and Specificity|Software|Software Validation', 'Comparative Study', '10.1186/1471-2105-5-34', '15050037', 'The biological interpretation of even a simple microarray experiment can be a challenging and highly complex task. Here we present a new method (Iterative Group Analysis) to facilitate, improve, and accelerate this process.'),
(90103, 2004, 'bmc', 'MiCoViTo: a tool for gene-centric comparison and visualization of yeast transcriptome states', 'Lelandais, Gaëlle|Marc, Philippe|Vincens, Pierre|Jacq, Claude|Vialette, Stéphane', 'Laboratoire de Génétique Moléculaire CNRS UMR8541, Ecole Normale Supérieure, Paris, 75230 Cedex 05, France. lelandais@biologie.ens.fr|Laboratoire de Génétique Moléculaire CNRS UMR8541, Ecole Normale Supérieure, Paris, 75230 Cedex 05, France. lelandais@biologie.ens.fr|Laboratoire de Génétique Moléculaire CNRS UMR8541, Ecole Normale Supérieure, Paris, 75230 Cedex 05, France. lelandais@biologie.ens.fr|Laboratoire de Génétique Moléculaire CNRS UMR8541, Ecole Normale Supérieure, Paris, 75230 Cedex 05, France. lelandais@biologie.ens.fr|Laboratoire de Génétique Moléculaire CNRS UMR8541, Ecole Normale Supérieure, Paris, 75230 Cedex 05, France. lelandais@biologie.ens.fr', 'France|France|France|France|France', 4, 'Cluster Analysis|Computational Biology|Computer Graphics|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Fungal|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Transcription, Genetic', 'Comparative Study', '10.1186/1471-2105-5-20', '15053844', 'Information obtained by DNA microarray technology gives a rough snapshot of the transcriptome state, i.e., the expression level of all the genes expressed in a cell population at any given time. One of the challenging questions raised by the tremendous amount of microarray data is to identify groups of co-regulated genes and to understand their role in cell functions.'),
(90104, 2004, 'bmc', 'Quantifying the relationship between co-expression, co-regulation and gene function', 'Allocco, Dominic J|Kohane, Isaac S|Butte, Atul J', 'Informatics Program, Childrens Hospital, Boston, MA, USA. allocco@chip.org|Informatics Program, Childrens Hospital, Boston, MA, USA. allocco@chip.org|Informatics Program, Childrens Hospital, Boston, MA, USA. allocco@chip.org', 'United States|United States|United States', 229, 'Gene Expression Profiling|Gene Expression Regulation|Genes|Genes, Regulator|Models, Genetic|Oligonucleotide Array Sequence Analysis|Predictive Value of Tests|Transcription Factors', 'Journal Article', '10.1186/1471-2105-5-18', '15053845', 'It is thought that genes with similar patterns of mRNA expression and genes with similar functions are likely to be regulated via the same mechanisms. It has been difficult to quantitatively test these hypotheses on a large scale because there has been no general way of determining whether genes share a common regulatory mechanism. Here we use data from a recent genome wide binding analysis in combination with mRNA expression data and existing functional annotations to quantify the likelihood that genes with varying degrees of similarity in mRNA expression profile or function will be bound by a common transcription factor.'),
(90105, 2004, 'bmc', 'Comparison of computational methods for identifying translation initiation sites in EST data', 'Nadershahi, Afshin|Fahrenkrug, Scott C|Ellis, Lynda B M', 'College of Biological Science, University of Minnesota, St. Paul, MN 55108, USA. nade0043@umn.edu|College of Biological Science, University of Minnesota, St. Paul, MN 55108, USA. nade0043@umn.edu|College of Biological Science, University of Minnesota, St. Paul, MN 55108, USA. nade0043@umn.edu', 'United States|United States|United States', 34, 'Codon, Initiator|Computational Biology|Expressed Sequence Tags|Methionine|Predictive Value of Tests|Protein Biosynthesis', 'Comparative Study', '10.1186/1471-2105-5-14', '15053846', 'Expressed Sequence Tag (EST) sequences are generally single-strand, single-pass sequences, only 200-600 nucleotides long, contain errors resulting in frame shifts, and represent different parts of their parent cDNA. If the cDNAs contain translation initiation sites, they may be suitable for functional genomics studies. We have compared five methods to predict translation initiation sites in EST data: first-ATG, ESTScan, Diogenes, Netstart, and ATGpr.'),
(90106, 2004, 'bmc', 'PASS2: an automated database of protein alignments organised as structural superfamilies', 'Bhaduri, Anirban|Pugalenthi, Ganesan|Sowdhamini, Ramanathan', 'National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India. anirban@ncbs.res.in|National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India. anirban@ncbs.res.in|National Centre for Biological Sciences, Tata Institute of Fundamental Research, UAS-GKVK campus, Bellary Road, Bangalore, Karnataka 560 065, India. anirban@ncbs.res.in', 'India|India|India', 30, 'Amino Acid Sequence|Automation|Cytochromes|Database Management Systems|Databases, Protein|Markov Chains|Molecular Sequence Data|Protein Folding|Proteins|Sequence Alignment|Software|Software Design', 'Journal Article', '10.1186/1471-2105-5-35', '15059245', 'The functional selection and three-dimensional structural constraints of proteins in nature often relates to the retention of significant sequence similarity between proteins of similar fold and function despite poor sequence identity. Organization of structure-based sequence alignments for distantly related proteins, provides a map of the conserved and critical regions of the protein universe that is useful for the analysis of folding principles, for the evolutionary unification of protein families and for maximizing the information return from experimental structure determination. The Protein Alignment organised as Structural Superfamily (PASS2) database represents continuously updated, structural alignments for evolutionary related, sequentially distant proteins.'),
(90107, 2004, 'bmc', 'Structural characterization of genomes by large scale sequence-structure threading', 'Cherkasov, Artem|Jones, Steven J M', 'Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, British Columbia, Canada. artc@interchange.ubc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, British Columbia, Canada. artc@interchange.ubc.ca', 'Canada|Canada', 0, 'Animals|Base Sequence|Computational Biology|Databases, Genetic|Genome|Genome, Archaeal|Genome, Bacterial|Genome, Fungal|Genome, Human|Genome, Protozoan|Humans|Mice|Nucleic Acid Conformation|Proteome|Software', 'Evaluation Studies', '10.1186/1471-2105-5-37', '15061866', 'Using sequence-structure threading we have conducted structural characterization of complete proteomes of 37 archaeal, bacterial and eukaryotic organisms (including worm, fly, mouse and human) totaling 167,888 genes.'),
(90108, 2004, 'bmc', 'Auto-validation of fluorescent primer extension genotyping assay using signal clustering and neural networks', 'Huang, Ching Yu Austin|Studebaker, Joel|Yuryev, Anton|Huang, Jianping|Scott, Kathryn E|Kuebler, Jennifer|Varde, Shobha|Alfisi, Steven|Gelfand, Craig A|Pohl, Mark|Boyce-Jacino, Michael T', 'Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu|Center for Pharmacogenomics and Complex Disease Research, Newark, NJ 07101, USA. austin.huang@umdnj.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 8, 'Artificial Intelligence|Automation|Cluster Analysis|DNA Primers|Fluorescent Dyes|Genotype|Humans|Polymerase Chain Reaction|Polymorphism, Single Nucleotide|Predictive Value of Tests|Quality Control|Reproducibility of Results|Software', 'Comparative Study', '10.1186/1471-2105-5-36', '15061867', 'SNP genotyping typically incorporates a review step to ensure that the genotype calls for a particular SNP are correct. For high-throughput genotyping, such as that provided by the GenomeLab SNPstream instrument from Beckman Coulter, Inc., the manual review used for low-volume genotyping becomes a major bottleneck. The work reported here describes the application of a neural network to automate the review of results.'),
(90109, 2004, 'bmc', 'A Hidden Markov Model method, capable of predicting and discriminating beta-barrel outer membrane proteins', 'Bagos, Pantelis G|Liakopoulos, Theodore D|Spyropoulos, Ioannis C|Hamodrakas, Stavros J', 'Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 15701, GREECE. pbagos@biol.uoa.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 15701, GREECE. pbagos@biol.uoa.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 15701, GREECE. pbagos@biol.uoa.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis, Athens 15701, GREECE. pbagos@biol.uoa.gr', '-|-|-|-', 136, 'Databases, Protein|Escherichia coli Proteins|Markov Chains|Membrane Proteins|Models, Statistical|Peptides|Predictive Value of Tests|Protein Structure, Tertiary', 'Comparative Study', '10.1186/1471-2105-5-29', '15070403', 'Integral membrane proteins constitute about 20-30% of all proteins in the fully sequenced genomes. They come in two structural classes, the alpha-helical and the beta-barrel membrane proteins, demonstrating different physicochemical characteristics, structure and localization. While transmembrane segment prediction for the alpha-helical integral membrane proteins appears to be an easy task nowadays, the same is much more difficult for the beta-barrel membrane proteins. We developed a method, based on a Hidden Markov Model, capable of predicting the transmembrane beta-strands of the outer membrane proteins of gram-negative bacteria, and discriminating those from water-soluble proteins in large datasets. The model is trained in a discriminative manner, aiming at maximizing the probability of correct predictions rather than the likelihood of the sequences.'),
(90110, 2004, 'bmc', 'Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models', 'Mahony, Shaun|McInerney, James O|Smith, Terry J|Golden, Aaron', 'National Centre for Biomedical Engineering Science, NUI, Galway, Galway, Ireland. shaun.mahony@nuigalway.ie|National Centre for Biomedical Engineering Science, NUI, Galway, Galway, Ireland. shaun.mahony@nuigalway.ie|National Centre for Biomedical Engineering Science, NUI, Galway, Galway, Ireland. shaun.mahony@nuigalway.ie|National Centre for Biomedical Engineering Science, NUI, Galway, Galway, Ireland. shaun.mahony@nuigalway.ie', 'Ireland|Ireland|Ireland|Ireland', 18, 'Chromosome Mapping|Codon|Computational Biology|Deinococcus|GC Rich Sequence|Genes, Archaeal|Genes, Bacterial|Genome, Archaeal|Genome, Bacterial|Gram-Negative Bacteria|Gram-Positive Endospore-Forming Bacteria|Markov Chains|Methanococcus|Models, Genetic|Multigene Family|Predictive Value of Tests|Reading Frames|Software', 'Comparative Study', '10.1186/1471-2105-5-23', '15070404', 'Many current gene prediction methods use only one model to represent protein-coding regions in a genome, and so are less likely to predict the location of genes that have an atypical sequence composition. It is likely that future improvements in gene finding will involve the development of methods that can adequately deal with intra-genomic compositional variation.'),
(90111, 2004, 'bmc', 'Cancer characterization and feature set extraction by discriminative margin clustering', 'Munagala, Kamesh|Tibshirani, Robert|Brown, Patrick O', 'Department of Biochemistry, Stanford University School of Medicine, 466 Gates Computer Science, Stanford, CA 94305, USA. kamesh@cmgm.stanford.edu|Department of Biochemistry, Stanford University School of Medicine, 466 Gates Computer Science, Stanford, CA 94305, USA. kamesh@cmgm.stanford.edu|Department of Biochemistry, Stanford University School of Medicine, 466 Gates Computer Science, Stanford, CA 94305, USA. kamesh@cmgm.stanford.edu', 'United States|United States|United States', 23, 'Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Humans|Molecular Diagnostic Techniques|Neoplasms|Oligonucleotide Array Sequence Analysis|Predictive Value of Tests', 'Journal Article', '10.1186/1471-2105-5-21', '15070405', 'A central challenge in the molecular diagnosis and treatment of cancer is to define a set of molecular features that, taken together, distinguish a given cancer, or type of cancer, from all normal cells and tissues.'),
(90112, 2004, 'bmc', 'Predicting co-complexed protein pairs using genomic and proteomic data integration', 'Zhang, Lan V|Wong, Sharyl L|King, Oliver D|Roth, Frederick P', 'Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. lan_zhang@student.hms.harvard.edu|Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. lan_zhang@student.hms.harvard.edu|Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. lan_zhang@student.hms.harvard.edu|Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. lan_zhang@student.hms.harvard.edu', 'United States|United States|United States|United States', 145, 'Computational Biology|Databases, Protein|Decision Trees|Gene Expression Regulation, Fungal|Genes, Fungal|Genomics|Mass Spectrometry|Predictive Value of Tests|Protein Interaction Mapping|Proteomics|RNA, Fungal|Saccharomyces cerevisiae Proteins|Two-Hybrid System Techniques', 'Journal Article', '10.1186/1471-2105-5-38', '15090078', 'Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same protein complex. High-throughput methods such as yeast two-hybrid (Y2H) and affinity purification coupled with mass spectrometry (APMS) have been used to detect interacting proteins on a genomic scale. However, both Y2H and APMS methods have substantial false-positive rates. Aside from high-throughput interaction screens, other gene- or protein-pair characteristics may also be informative of physical interaction. Therefore it is desirable to integrate multiple datasets and utilize their different predictive value for more accurate prediction of co-complexed relationship.'),
(90113, 2004, 'bmc', 'No statistical support for correlation between the positions of protein interaction sites and alternatively spliced regions', 'Offman, Marc N|Nurtdinov, Ramil N|Gelfand, Mikhail S|Frishman, Dmitrij', 'Department of Genome Oriented Bioinformatics, Technical University of Munich, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany. offman@in.tum.de|Department of Genome Oriented Bioinformatics, Technical University of Munich, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany. offman@in.tum.de|Department of Genome Oriented Bioinformatics, Technical University of Munich, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany. offman@in.tum.de|Department of Genome Oriented Bioinformatics, Technical University of Munich, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany. offman@in.tum.de', 'Germany|Germany|Germany|Germany', 6, 'Alternative Splicing|Amino Acid Sequence|CDC2-CDC28 Kinases|Cyclin-Dependent Kinase 2|Eye Proteins|GTP-Binding Protein Regulators|Humans|Models, Statistical|Molecular Sequence Data|Phosphoproteins|Protein Interaction Mapping|Protein Structure, Quaternary|Proteins|beta Karyopherins|rhoA GTP-Binding Protein', 'Journal Article', '10.1186/1471-2105-5-41', '15096275', 'Alternative splicing is an efficient mechanism for increasing the variety of functions fulfilled by proteins in a living cell. It has been previously demonstrated that alternatively spliced regions often comprise functionally important and conserved sequence motifs. The objective of this work was to test the hypothesis that alternative splicing is correlated with contact regions of protein-protein interactions.'),
(90114, 2004, 'bmc', 'Pegasys: software for executing and integrating analyses of biological sequences', 'Shah, Sohrab P|He, David Y M|Sawkins, Jessica N|Druce, Jeffrey C|Quon, Gerald|Lett, Drew|Zheng, Grace X Y|Xu, Tao|Ouellette, B F Francis', 'UBC Bioinformatics Centre, University of British Columbia, Vancouver, British Columbia, Canada. sohrab@bioinformatics.ubc.ca|UBC Bioinformatics Centre, University of British Columbia, Vancouver, British Columbia, Canada. sohrab@bioinformatics.ubc.ca|UBC Bioinformatics Centre, University of British Columbia, Vancouver, British Columbia, Canada. sohrab@bioinformatics.ubc.ca|UBC Bioinformatics Centre, University of British Columbia, Vancouver, British Columbia, Canada. sohrab@bioinformatics.ubc.ca|UBC Bioinformatics Centre, University of British Columbia, Vancouver, British Columbia, Canada. sohrab@bioinformatics.ubc.ca|UBC Bioinformatics Centre, University of British Columbia, Vancouver, British Columbia, Canada. sohrab@bioinformatics.ubc.ca|UBC Bioinformatics Centre, University of British Columbia, Vancouver, British Columbia, Canada. sohrab@bioinformatics.ubc.ca|UBC Bioinformatics Centre, University of British Columbia, Vancouver, British Columbia, Canada. sohrab@bioinformatics.ubc.ca|UBC Bioinformatics Centre, University of British Columbia, Vancouver, British Columbia, Canada. sohrab@bioinformatics.ubc.ca', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 67, 'Computational Biology|Computer Graphics|DNA|Databases, Genetic|Game Theory|Genetic Heterogeneity|Humans|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software|Software Design|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-5-40', '15096276', 'We present Pegasys--a flexible, modular and customizable software system that facilitates the execution and data integration from heterogeneous biological sequence analysis tools.'),
(90115, 2004, 'bmc', 'MolTalk--a programming library for protein structures and structure analysis', 'Diemand, Alexander V|Scheib, Holger', 'University of Lausanne and Swiss Institute of Bioinformatics, 155, chemin de Boveresses, 1066 Epalinges s/Lausanne, Switzerland. alexander.diemand@isb-sib.ch|University of Lausanne and Swiss Institute of Bioinformatics, 155, chemin de Boveresses, 1066 Epalinges s/Lausanne, Switzerland. alexander.diemand@isb-sib.ch', 'Switzerland|Switzerland', 11, 'Artificial Intelligence|Computational Biology|Database Management Systems|Internet|Programming Languages|Protein Conformation|Software|Software Design', 'Journal Article', '10.1186/1471-2105-5-39', '15096277', 'Two of the mostly unsolved but increasingly urgent problems for modern biologists are a) to quickly and easily analyse protein structures and b) to comprehensively mine the wealth of information, which is distributed along with the 3D co-ordinates by the Protein Data Bank (PDB). Tools which address this issue need to be highly flexible and powerful but at the same time must be freely available and easy to learn.'),
(90116, 2004, 'bmc', 'BioBuilder as a database development and functional annotation platform for proteins', 'Navarro, J Daniel|Talreja, Naveen|Peri, Suraj|Vrushabendra, B M|Rashmi, B P|Padma, N|Surendranath, Vineeth|Jonnalagadda, Chandra Kiran|Kousthub, P S|Deshpande, Nandan|Shanker, K|Pandey, Akhilesh', 'McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu|McKusick-Nathans Institute of Genetic Medicine and the Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. dnavarro@jhmi.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 5, 'Computational Biology|Database Management Systems|Databases, Protein|Humans|Internet|Proteins|Software|Software Design', 'Journal Article', '10.1186/1471-2105-5-43', '15099404', 'The explosion in biological information creates the need for databases that are easy to develop, easy to maintain and can be easily manipulated by annotators who are most likely to be biologists. However, deployment of scalable and extensible databases is not an easy task and generally requires substantial expertise in database development.'),
(90117, 2004, 'bmc', 'Leveraging two-way probe-level block design for identifying differential gene expression with high-density oligonucleotide arrays', 'Barrera, Leah|Benner, Chris|Tao, Yong-Chuan|Winzeler, Elizabeth|Zhou, Yingyao', 'Genomics Institute of the Novartis Research Foundation, 10675 John Jay Hopkins Drive, California 92121, USA. lbarrera@bioinf.ucsd.edu|Genomics Institute of the Novartis Research Foundation, 10675 John Jay Hopkins Drive, California 92121, USA. lbarrera@bioinf.ucsd.edu|Genomics Institute of the Novartis Research Foundation, 10675 John Jay Hopkins Drive, California 92121, USA. lbarrera@bioinf.ucsd.edu|Genomics Institute of the Novartis Research Foundation, 10675 John Jay Hopkins Drive, California 92121, USA. lbarrera@bioinf.ucsd.edu|Genomics Institute of the Novartis Research Foundation, 10675 John Jay Hopkins Drive, California 92121, USA. lbarrera@bioinf.ucsd.edu', 'United States|United States|United States|United States|United States', 19, 'Analysis of Variance|Benchmarking|Cell Line|Computational Biology|DNA Probes|Fibroblasts|Gene Expression Profiling|Genetic Variation|Humans|Nucleic Acid Conformation|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Research Design|Sample Size|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-5-42', '15099405', 'To identify differentially expressed genes across experimental conditions in oligonucleotide microarray experiments, existing statistical methods commonly use a summary of probe-level expression data for each probe set and compare replicates of these values across conditions using a form of the t-test or rank sum test. Here we propose the use of a statistical method that takes advantage of the built-in redundancy architecture of high-density oligonucleotide arrays.'),
(90118, 2004, 'bmc', 'Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data', 'Gao, Feng|Foat, Barrett C|Bussemaker, Harmen J', 'Department of Biological Sciences, Columbia University, New York, New York 10027, USA. fg2037@columbia.edu|Department of Biological Sciences, Columbia University, New York, New York 10027, USA. fg2037@columbia.edu|Department of Biological Sciences, Columbia University, New York, New York 10027, USA. fg2037@columbia.edu', 'United States|United States|United States', 194, 'Algorithms|Computational Biology|DNA, Fungal|Gene Expression Profiling|Gene Expression Regulation, Fungal|Genes, Fungal|Models, Genetic|Oligonucleotide Array Sequence Analysis|Promoter Regions, Genetic|RNA, Fungal|RNA, Messenger|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-5-31', '15113405', 'Functional genomics studies are yielding information about regulatory processes in the cell at an unprecedented scale. In the yeast S. cerevisiae, DNA microarrays have not only been used to measure the mRNA abundance for all genes under a variety of conditions but also to determine the occupancy of all promoter regions by a large number of transcription factors. The challenge is to extract useful information about the global regulatory network from these data.'),
(90119, 2004, 'bmc', 'Frequent occurrence of recognition site-like sequences in the restriction endonucleases', 'Biro, Jan C|Biro, Josephine M K', 'Karolinska Institute, Stockholm, Sweden. jan.biro@sbcglobal.net|Karolinska Institute, Stockholm, Sweden. jan.biro@sbcglobal.net', 'Sweden|Sweden', 10, 'Amino Acids|Base Composition|Base Sequence|Binding Sites|Codon|Conserved Sequence|DNA Restriction Enzymes|Databases, Genetic|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-5-30', '15113406', 'There are two different theories about the development of the genetic code. Woese suggested that it was developed in connection with the amino acid repertoire, while Crick argued that any connection between codons and amino acids is only the result of an accident. This question is fundamental to understand the nature of specific protein-nucleic acid interactions.'),
(90120, 2004, 'bmc', 'SUPFAM: a database of sequence superfamilies of protein domains', 'Pandit, Shashi B|Bhadra, Rana|Gowri, V S|Balaji, S|Anand, B|Srinivasan, N', 'Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560 012, India. shashi@mbu.iisc.ernet.in|Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560 012, India. shashi@mbu.iisc.ernet.in|Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560 012, India. shashi@mbu.iisc.ernet.in|Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560 012, India. shashi@mbu.iisc.ernet.in|Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560 012, India. shashi@mbu.iisc.ernet.in|Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560 012, India. shashi@mbu.iisc.ernet.in', 'India|India|India|India|India|India', 31, 'Amino Acid Sequence|Computational Biology|Databases, Protein|Peptides|Protein Structure, Tertiary|Proteins', 'Comparative Study', '10.1186/1471-2105-5-28', '15113407', 'SUPFAM database is a compilation of superfamily relationships between protein domain families of either known or unknown 3-D structure. In SUPFAM, sequence families from Pfam and structural families from SCOP are associated, using profile matching, to result in sequence superfamilies of known structure. Subsequently all-against-all family profile matches are made to deduce a list of new potential superfamilies of yet unknown structure.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90121, 2004, 'bmc', 'CisOrtho: a program pipeline for genome-wide identification of transcription factor target genes using phylogenetic footprinting', 'Bigelow, Henry R|Wenick, Adam S|Wong, Allan|Hobert, Oliver', 'Department of Biochemistry and Molecular Biophysics, Columbia University, College of Physicians and Surgeons, 701 West 168th Street, New York, NY 10032, USA. hrb46@columbia.edu|Department of Biochemistry and Molecular Biophysics, Columbia University, College of Physicians and Surgeons, 701 West 168th Street, New York, NY 10032, USA. hrb46@columbia.edu|Department of Biochemistry and Molecular Biophysics, Columbia University, College of Physicians and Surgeons, 701 West 168th Street, New York, NY 10032, USA. hrb46@columbia.edu|Department of Biochemistry and Molecular Biophysics, Columbia University, College of Physicians and Surgeons, 701 West 168th Street, New York, NY 10032, USA. hrb46@columbia.edu', 'United States|United States|United States|United States', 30, 'Animals|Caenorhabditis|Caenorhabditis elegans|Computational Biology|DNA Footprinting|DNA, Helminth|DNA, Intergenic|Databases, Genetic|Genes, Helminth|Genome|Internet|Phylogeny|Sequence Homology, Nucleic Acid|Software|Software Design|Software Validation|Transcription Factors', 'Journal Article', '10.1186/1471-2105-5-27', '15113408', 'All known genomes code for a large number of transcription factors. It is important to develop methods that will reveal how these transcription factors act on a genome wide level, that is, through what target genes they exert their function.'),
(90122, 2004, 'bmc', 'Computational protein biomarker prediction: a case study for prostate cancer', 'Wagner, Michael|Naik, Dayanand N|Pothen, Alex|Kasukurti, Srinivas|Devineni, Raghu Ram|Adam, Bao-Ling|Semmes, O John|Wright, George L', 'Cincinnati Childrens Hospital Research Foundation and Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45229, USA. mwagner@cchmc.org|Cincinnati Childrens Hospital Research Foundation and Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45229, USA. mwagner@cchmc.org|Cincinnati Childrens Hospital Research Foundation and Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45229, USA. mwagner@cchmc.org|Cincinnati Childrens Hospital Research Foundation and Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45229, USA. mwagner@cchmc.org|Cincinnati Childrens Hospital Research Foundation and Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45229, USA. mwagner@cchmc.org|Cincinnati Childrens Hospital Research Foundation and Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45229, USA. mwagner@cchmc.org|Cincinnati Childrens Hospital Research Foundation and Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45229, USA. mwagner@cchmc.org|Cincinnati Childrens Hospital Research Foundation and Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45229, USA. mwagner@cchmc.org', 'United States|United States|United States|United States|United States|United States|United States|United States', 84, 'Biomarkers, Tumor|Computational Biology|Humans|Male|Neoplasm Proteins|Predictive Value of Tests|Prostatic Neoplasms|Random Allocation|Reproducibility of Results|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Journal Article', '10.1186/1471-2105-5-26', '15113409', 'Recent technological advances in mass spectrometry pose challenges in computational mathematics and statistics to process the mass spectral data into predictive models with clinical and biological significance. We discuss several classification-based approaches to finding protein biomarker candidates using protein profiles obtained via mass spectrometry, and we assess their statistical significance. Our overall goal is to implicate peaks that have a high likelihood of being biologically linked to a given disease state, and thus to narrow the search for biomarker candidates.'),
(90123, 2004, 'bmc', 'A web services choreography scenario for interoperating bioinformatics applications', 'de Knikker, Remko|Guo, Youjun|Li, Jin-Long|Kwan, Albert K H|Yip, Kevin Y|Cheung, David W|Cheung, Kei-Hoi', 'Center for Medical Informatics, Department of Anesthesiology, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520, USA. remkodeknikker@hotmail.com|Center for Medical Informatics, Department of Anesthesiology, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520, USA. remkodeknikker@hotmail.com|Center for Medical Informatics, Department of Anesthesiology, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520, USA. remkodeknikker@hotmail.com|Center for Medical Informatics, Department of Anesthesiology, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520, USA. remkodeknikker@hotmail.com|Center for Medical Informatics, Department of Anesthesiology, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520, USA. remkodeknikker@hotmail.com|Center for Medical Informatics, Department of Anesthesiology, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520, USA. remkodeknikker@hotmail.com|Center for Medical Informatics, Department of Anesthesiology, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520, USA. remkodeknikker@hotmail.com', 'United States|United States|United States|United States|United States|United States|United States', 21, 'Computational Biology|Computer Graphics|Databases, Genetic|Gene Expression Profiling|Internet|Oligonucleotide Array Sequence Analysis|Software', 'Comparative Study', '10.1186/1471-2105-5-25', '15113410', 'Very often genome-wide data analysis requires the interoperation of multiple databases and analytic tools. A large number of genome databases and bioinformatics applications are available through the web, but it is difficult to automate interoperation because: 1) the platforms on which the applications run are heterogeneous, 2) their web interface is not machine-friendly, 3) they use a non-standard format for data input and output, 4) they do not exploit standards to define application interface and message exchange, and 5) existing protocols for remote messaging are often not firewall-friendly. To overcome these issues, web services have emerged as a standard XML-based model for message exchange between heterogeneous applications. Web services engines have been developed to manage the configuration and execution of a web services workflow.'),
(90124, 2004, 'bmc', 'Biochemical Network Stochastic Simulator (BioNetS): software for stochastic modeling of biochemical networks', 'Adalsteinsson, David|McMillen, David|Elston, Timothy C', 'Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3250, USA. david@amath.unc.edu|Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3250, USA. david@amath.unc.edu|Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3250, USA. david@amath.unc.edu', 'United States|United States|United States', 95, 'Algorithms|Cell Division|Computer Simulation|Gene Expression Regulation|Genes, Regulator|Models, Genetic|Neural Networks (Computer)|Software|Software Design|Stochastic Processes|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-5-24', '15113411', 'Intrinsic fluctuations due to the stochastic nature of biochemical reactions can have large effects on the response of biochemical networks. This is particularly true for pathways that involve transcriptional regulation, where generally there are two copies of each gene and the number of messenger RNA (mRNA) molecules can be small. Therefore, there is a need for computational tools for developing and investigating stochastic models of biochemical networks.'),
(90125, 2004, 'bmc', 'SIGI: score-based identification of genomic islands', 'Merkl, Rainer', 'Abteilung Molekulare Genetik und Präparative Molekularbiologie, Institut für Mikrobiologie und Genetik, Georg-August-Universität Göttingen and Göttingen Genomics Laboratory, Grisebachstr, 8, 37077 Göttingen, Germany. rmerkl@gwdg.de', 'Germany', 62, 'Algorithms|Base Composition|DNA, Archaeal|DNA, Bacterial|Genes, Archaeal|Genes, Bacterial|Genome, Archaeal|Genome, Bacterial|Genomic Islands|Interspersed Repetitive Sequences|Models, Genetic|Molecular Sequence Data|Software', 'Journal Article', '10.1186/1471-2105-5-22', '15113412', 'Genomic islands can be observed in many microbial genomes. These stretches of DNA have a conspicuous composition with regard to sequence or encoded functions. Genomic islands are assumed to be frequently acquired via horizontal gene transfer. For the analysis of genome structure and the study of horizontal gene transfer, it is necessary to reliably identify and characterize these islands.'),
(90126, 2004, 'bmc', 'Network analysis of metabolic enzyme evolution in Escherichia coli', 'Light, Sara|Kraulis, Per', 'Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm Center for Physics, Astronomy and Biotechnology, Stockholm University, Stockholm SE-10691, Sweden. sara@sbc.su.se|Stockholm Bioinformatics Center, Department of Biochemistry and Biophysics, Stockholm Center for Physics, Astronomy and Biotechnology, Stockholm University, Stockholm SE-10691, Sweden. sara@sbc.su.se', 'Sweden|Sweden', 46, 'Algorithms|Biotin|Computational Biology|Databases, Genetic|Escherichia coli|Escherichia coli Proteins|Evolution, Molecular|Genes, Bacterial|Models, Biological|Sequence Homology, Amino Acid|Substrate Specificity', 'Comparative Study', '10.1186/1471-2105-5-15', '15113413', 'The two most common models for the evolution of metabolism are the patchwork evolution model, where enzymes are thought to diverge from broad to narrow substrate specificity, and the retrograde evolution model, according to which enzymes evolve in response to substrate depletion. Analysis of the distribution of homologous enzyme pairs in the metabolic network can shed light on the respective importance of the two models. We here investigate the evolution of the metabolism in E. coli viewed as a single network using EcoCyc.'),
(90127, 2004, 'bmc', 'A hybrid clustering approach to recognition of protein families in 114 microbial genomes', 'Harlow, Timothy J|Gogarten, J Peter|Ragan, Mark A', 'Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld 4072, Australia. t.harlow@imb.uq.edu.au|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld 4072, Australia. t.harlow@imb.uq.edu.au|Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld 4072, Australia. t.harlow@imb.uq.edu.au', 'Australia|Australia|Australia', 37, 'Algorithms|Amino Acid Sequence|Bacterial Proteins|Cluster Analysis|Computational Biology|Databases, Protein|Genome, Bacterial|Mitochondrial Proton-Translocating ATPases|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-5-45', '15115543', 'Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function). Standard clustering methods such as single-linkage clustering capture a history of cluster topologies as a function of threshold, but in practice their usefulness is limited because unrelated sequences join clusters before biologically meaningful families are fully constituted, e.g. as the result of matches to so-called promiscuous domains. Use of the Markov Cluster algorithm avoids this non-specificity, but does not preserve topological or threshold information about protein families.'),
(90128, 2004, 'bmc', 'Identification of regions in multiple sequence alignments thermodynamically suitable for targeting by consensus oligonucleotides: application to HIV genome', 'Matveeva, Olga V|Foley, Brian T|Nemtsov, Vladimir A|Gesteland, Raymond F|Matsufuji, Senya|Atkins, John F|Ogurtsov, Alexei Y|Shabalina, Svetlana A', 'Department of Human Genetics, University of Utah, Salt Lake City 84112-5330, USA. olgam@howard.genetics.utah.edu|Department of Human Genetics, University of Utah, Salt Lake City 84112-5330, USA. olgam@howard.genetics.utah.edu|Department of Human Genetics, University of Utah, Salt Lake City 84112-5330, USA. olgam@howard.genetics.utah.edu|Department of Human Genetics, University of Utah, Salt Lake City 84112-5330, USA. olgam@howard.genetics.utah.edu|Department of Human Genetics, University of Utah, Salt Lake City 84112-5330, USA. olgam@howard.genetics.utah.edu|Department of Human Genetics, University of Utah, Salt Lake City 84112-5330, USA. olgam@howard.genetics.utah.edu|Department of Human Genetics, University of Utah, Salt Lake City 84112-5330, USA. olgam@howard.genetics.utah.edu|Department of Human Genetics, University of Utah, Salt Lake City 84112-5330, USA. olgam@howard.genetics.utah.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 4, 'Base Sequence|Computational Biology|Consensus Sequence|DNA, Viral|Databases, Genetic|Gene Products, gag|Genetic Variation|Genome, Viral|HIV-1|Internet|Molecular Sequence Data|Nucleic Acid Hybridization|Oligonucleotides|RNA, Viral|Sequence Alignment|Software|Thermodynamics', 'Journal Article', '10.1186/1471-2105-5-44', '15115544', 'Computer programs for the generation of multiple sequence alignments such as Clustal W allow detection of regions that are most conserved among many sequence variants. However, even for regions that are equally conserved, their potential utility as hybridization targets varies. Mismatches in sequence variants are more disruptive in some duplexes than in others. Additionally, the propensity for self-interactions amongst oligonucleotides targeting conserved regions differs and the structure of target regions themselves can also influence hybridization efficiency. There is a need to develop software that will employ thermodynamic selection criteria for finding optimal hybridization targets in related sequences.'),
(90129, 2004, 'bmc', 'Visualising very large phylogenetic trees in three dimensional hyperbolic space', 'Hughes, Timothy|Hyun, Young|Liberles, David A', 'Computational Biology Unit Bergen Centre for Computational Science University of Bergen, 5020 Bergen, Norway. tim@ii.uib.no|Computational Biology Unit Bergen Centre for Computational Science University of Bergen, 5020 Bergen, Norway. tim@ii.uib.no|Computational Biology Unit Bergen Centre for Computational Science University of Bergen, 5020 Bergen, Norway. tim@ii.uib.no', 'Norway|Norway|Norway', 0, 'Animals|Archaea|Bacteria|Classification|Computational Biology|Computer Graphics|Databases, Factual|Eukaryotic Cells|Phylogeny|Primates|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-5-48', '15117420', 'Common existing phylogenetic tree visualisation tools are not able to display readable trees with more than a few thousand nodes. These existing methodologies are based in two dimensional space.'),
(90130, 2004, 'bmc', 'Hybrid clustering for microarray image analysis combining intensity and shape features', 'Rahnenführer, Jörg|Bozinov, Daniel', 'Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de|Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de', 'Germany|Germany', 28, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Image Enhancement|Image Processing, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Software', 'Comparative Study', '10.1186/1471-2105-5-47', '15117421', 'Image analysis is the first crucial step to obtain reliable results from microarray experiments. First, areas in the image belonging to single spots have to be identified. Then, those target areas have to be partitioned into foreground and background. Finally, two scalar values for the intensities have to be extracted. These goals have been tackled either by spot shape methods or intensity histogram methods, but it would be desirable to have hybrid algorithms which combine the advantages of both approaches.'),
(90131, 2004, 'bmc', 'BEAR GeneInfo: a tool for identifying gene-related biomedical publications through user modifiable queries', 'Zhou, Guohui|Wen, Xinyu|Liu, Hang|Schlicht, Michael J|Hessner, Martin J|Tonellato, Peter J|Datta, Milton W', 'Department of Pathology and Bioinformatics Program, Medical College of Wisconsin, Milwaukee, WI, 53226, USA. guohui@rocketmail.com|Department of Pathology and Bioinformatics Program, Medical College of Wisconsin, Milwaukee, WI, 53226, USA. guohui@rocketmail.com|Department of Pathology and Bioinformatics Program, Medical College of Wisconsin, Milwaukee, WI, 53226, USA. guohui@rocketmail.com|Department of Pathology and Bioinformatics Program, Medical College of Wisconsin, Milwaukee, WI, 53226, USA. guohui@rocketmail.com|Department of Pathology and Bioinformatics Program, Medical College of Wisconsin, Milwaukee, WI, 53226, USA. guohui@rocketmail.com|Department of Pathology and Bioinformatics Program, Medical College of Wisconsin, Milwaukee, WI, 53226, USA. guohui@rocketmail.com|Department of Pathology and Bioinformatics Program, Medical College of Wisconsin, Milwaukee, WI, 53226, USA. guohui@rocketmail.com', 'United States|United States|United States|United States|United States|United States|United States', 8, 'Databases, Genetic|Genes, Neoplasm|Humans|Information Storage and Retrieval|Male|Prostatic Neoplasms|PubMed|Publications|Selenium|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-5-46', '15117422', 'Once specific genes are identified through high throughput genomics technologies there is a need to sort the final gene list to a manageable size for validation studies. The triaging and sorting of genes often relies on the use of supplemental information related to gene structure, metabolic pathways, and chromosomal location. Yet in disease states where the genes may not have identifiable structural elements, poorly defined metabolic pathways, or limited chromosomal data, flexible systems for obtaining additional data are necessary. In these situations having a tool for searching the biomedical literature using the list of identified genes while simultaneously defining additional search terms would be useful.'),
(90132, 2004, 'bmc', 'ASAView: database and tool for solvent accessibility representation in proteins', 'Ahmad, Shandar|Gromiha, Michael|Fawareh, Hamed|Sarai, Akinori', 'Department of Biochemical Engineering and Science, Kyushu Institute of Technology, Iizuka 820 8502, Fukuoka-ken, Japan. shandar@bse.kyutech.ac.jp|Department of Biochemical Engineering and Science, Kyushu Institute of Technology, Iizuka 820 8502, Fukuoka-ken, Japan. shandar@bse.kyutech.ac.jp|Department of Biochemical Engineering and Science, Kyushu Institute of Technology, Iizuka 820 8502, Fukuoka-ken, Japan. shandar@bse.kyutech.ac.jp|Department of Biochemical Engineering and Science, Kyushu Institute of Technology, Iizuka 820 8502, Fukuoka-ken, Japan. shandar@bse.kyutech.ac.jp', 'Japan|Japan|Japan|Japan', 219, 'Computer Graphics|Databases, Protein|Proteins|Software|Solvents', 'Journal Article', '10.1186/1471-2105-5-51', '15119964', 'Accessible surface area (ASA) or solvent accessibility of amino acids in a protein has important implications. Knowledge of surface residues helps in locating potential candidates of active sites. Therefore, a method to quickly see the surface residues in a two dimensional model would help to immediately understand the population of amino acid residues on the surface and in the inner core of the proteins.'),
(90133, 2004, 'bmc', 'A structural study for the optimisation of functional motifs encoded in protein sequences', 'Via, Allegra|Helmer-Citterich, Manuela', 'Centre for Molecular Bioinformatics, Dept, of Biology, University of Rome Tor Vergata, Rome, Italy. allegra@cbm.bio.uniroma2.it|Centre for Molecular Bioinformatics, Dept, of Biology, University of Rome Tor Vergata, Rome, Italy. allegra@cbm.bio.uniroma2.it', 'Italy|Italy', 0, 'Amino Acid Motifs|Amino Acid Sequence|Computational Biology|Conserved Sequence|Databases, Protein|False Negative Reactions|Proteins|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-5-50', '15119965', 'A large number of PROSITE patterns select false positives and/or miss known true positives. It is possible that--at least in some cases--the weak specificity and/or sensitivity of a pattern is due to the fact that one, or maybe more, functional and/or structural key residues are not represented in the pattern. Multiple sequence alignments are commonly used to build functional sequence patterns. If residues structurally conserved in proteins sharing a function cannot be aligned in a multiple sequence alignment, they are likely to be missed in a standard pattern construction procedure.'),
(90134, 2004, 'bmc', 'An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene interactions on risk of myocardial infarction: the importance of model validation', 'Coffey, Christopher S|Hebert, Patricia R|Ritchie, Marylyn D|Krumholz, Harlan M|Gaziano, J Michael|Ridker, Paul M|Brown, Nancy J|Vaughan, Douglas E|Moore, Jason H', 'Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. ccoffey@uab.edu|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. ccoffey@uab.edu|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. ccoffey@uab.edu|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. ccoffey@uab.edu|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. ccoffey@uab.edu|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. ccoffey@uab.edu|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. ccoffey@uab.edu|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. ccoffey@uab.edu|Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. ccoffey@uab.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Gene Expression Regulation|Genetic Predisposition to Disease|Genotype|Humans|Logistic Models|Myocardial Infarction|Risk Assessment', 'Comparative Study', '10.1186/1471-2105-5-49', '15119966', 'To examine interactions among the angiotensin converting enzyme (ACE) insertion/deletion, plasminogen activator inhibitor-1 (PAI-1) 4G/5G, and tissue plasminogen activator (t-PA) insertion/deletion gene polymorphisms on risk of myocardial infarction using data from 343 matched case-control pairs from the Physicians Health Study. We examined the data using both conditional logistic regression and the multifactor dimensionality reduction (MDR) method. One advantage of the MDR method is that it provides an internal prediction error for validation. We summarize our use of this internal prediction error for model validation.'),
(90135, 2004, 'bmc', 'Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels and spotted DNA microarrays', 'Townsend, Jeffrey P', 'Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. Townsend@Nature.Berkeley.edu', 'United States', 0, 'Algorithms|Bayes Theorem|Evaluation Studies as Topic|Gene Expression Profiling|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1186/1471-2105-5-54', '15128431', 'The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge requires careful examination of the performance of a range of statistical models, as well as empirical examination of the effect of replication on the power to resolve these differences.'),
(90136, 2004, 'bmc', 'Statistical monitoring of weak spots for improvement of normalization and ratio estimates in microarrays', 'Dozmorov, Igor|Knowlton, Nicholas|Tang, Yuhong|Centola, Michael', 'Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA. dozmorovi@omrf.ouhsc.edu|Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA. dozmorovi@omrf.ouhsc.edu|Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA. dozmorovi@omrf.ouhsc.edu|Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA. dozmorovi@omrf.ouhsc.edu', 'United States|United States|United States|United States', 0, 'Animals|DNA, Complementary|Gene Expression Profiling|Genes|Humans|Leukocytes, Mononuclear|Mice|Models, Statistical|Normal Distribution|Oligonucleotide Array Sequence Analysis|Quality Control', 'Journal Article', '10.1186/1471-2105-5-53', '15128432', 'Several aspects of microarray data analysis are dependent on identification of genes expressed at or near the limits of detection. For example, regression-based normalization methods rely on the premise that most genes in compared samples are expressed at similar levels and therefore require accurate identification of nonexpressed genes (additive noise) so that they can be excluded from the normalization procedure. Moreover, key regulatory genes can maintain stringent control of a given response at low expression levels. If arbitrary cutoffs are used for distinguishing expressed from nonexpressed genes, some of these key regulatory genes may be unnecessarily excluded from the analysis. Unfortunately, no accurate method for differentiating additive noise from genes expressed at low levels is currently available.'),
(90137, 2004, 'bmc', 'GeneOrder30: software for comparing the order of genes in pairs of small bacterial genomes', 'Celamkoti, Srikanth|Kundeti, Sashidhara|Purkayastha, Anjan|Mazumder, Raja|Buck, Charles|Seto, Donald', 'Bioinformatics and Computational Biology, School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 5B3, Manassas, VA 20110, USA. scelamko@gmu.edu|Bioinformatics and Computational Biology, School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 5B3, Manassas, VA 20110, USA. scelamko@gmu.edu|Bioinformatics and Computational Biology, School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 5B3, Manassas, VA 20110, USA. scelamko@gmu.edu|Bioinformatics and Computational Biology, School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 5B3, Manassas, VA 20110, USA. scelamko@gmu.edu|Bioinformatics and Computational Biology, School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 5B3, Manassas, VA 20110, USA. scelamko@gmu.edu|Bioinformatics and Computational Biology, School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 5B3, Manassas, VA 20110, USA. scelamko@gmu.edu', 'United States|United States|United States|United States|United States|United States', 16, 'Chromosome Mapping|Chromosomes, Bacterial|Gene Order|Genes, Bacterial|Genome, Bacterial|Haemophilus ducreyi|Haemophilus influenzae|Molecular Sequence Data|Mycoplasma|Mycoplasma gallisepticum|Mycoplasma genitalium|Mycoplasma penetrans|Mycoplasma pneumoniae|Mycoplasma pulmonis|Programming Languages|Software|Software Validation|Ureaplasma', 'Comparative Study', '10.1186/1471-2105-5-52', '15128433', 'An increasing number of whole viral and bacterial genomes are being sequenced and deposited in public databases. In parallel to the mounting interest in whole genomes, the number of whole genome analyses software tools is also increasing. GeneOrder was originally developed to provide an analysis of genes between two genomes, allowing visualization of gene order and synteny comparisons of any small genomes. It was originally developed for comparing virus, mitochondrion and chloroplast genomes. This is now extended to small bacterial genomes of sizes less than 2 Mb.'),
(90138, 2004, 'bmc', 'eL-DASionator: an LDAS upload file generator', 'Negre, Vincent|Grunau, Christoph', 'Institut de Génétique Humaine, CNRS UPR 1142, 141 rue de la Cardonille, 34396 Montpellier, France. developer@methdb.net|Institut de Génétique Humaine, CNRS UPR 1142, 141 rue de la Cardonille, 34396 Montpellier, France. developer@methdb.net', 'France|France', 0, 'Base Sequence|DNA|Database Management Systems|Databases, Genetic|Software', 'Journal Article', '10.1186/1471-2105-5-55', '15132760', 'The Distributed Annotation System (DAS) allows merging of DNA sequence annotations from multiple sources and provides a single annotation view. A straightforward way to establish a DAS annotation server is to use the Lightweight DAS server (LDAS). Onto this type of server, annotations can be uploaded as flat text files in a defined format. The popular Ensembl ContigView uses the same format for the transient upload and display of user data.'),
(90139, 2004, 'bmc', 'Computational identification of transcription factor binding sites by functional analysis of sets of genes sharing overrepresented upstream motifs', 'Corà, Davide|Di Cunto, Ferdinando|Provero, Paolo|Silengo, Lorenzo|Caselle, Michele', 'Dipartimento di Fisica Teorica, Università di Torino, and INFN, sezione di Torino, Italy. cora@to.infn.it|Dipartimento di Fisica Teorica, Università di Torino, and INFN, sezione di Torino, Italy. cora@to.infn.it|Dipartimento di Fisica Teorica, Università di Torino, and INFN, sezione di Torino, Italy. cora@to.infn.it|Dipartimento di Fisica Teorica, Università di Torino, and INFN, sezione di Torino, Italy. cora@to.infn.it|Dipartimento di Fisica Teorica, Università di Torino, and INFN, sezione di Torino, Italy. cora@to.infn.it', 'Italy|Italy|Italy|Italy|Italy', 0, '5 Flanking Region|Base Composition|Binding Sites|Computational Biology|Consensus Sequence|DNA, Fungal|Gene Expression Regulation, Fungal|Genes, Fungal|Saccharomyces cerevisiae|Transcription Factors|Transcription Initiation Site', 'Journal Article', '10.1186/1471-2105-5-57', '15137914', 'Transcriptional regulation is a key mechanism in the functioning of the cell, and is mostly effected through transcription factors binding to specific recognition motifs located upstream of the coding region of the regulated gene. The computational identification of such motifs is made easier by the fact that they often appear several times in the upstream region of the regulated genes, so that the number of occurrences of relevant motifs is often significantly larger than expected by pure chance.'),
(90140, 2004, 'bmc', 'Enhanced protein domain discovery using taxonomy', 'Coin, Lachlan|Bateman, Alex|Durbin, Richard', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. lc1@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. lc1@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. lc1@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Databases, Protein|Models, Statistical|Protein Structure, Tertiary|Proteins|Species Specificity', 'Journal Article', '10.1186/1471-2105-5-56', '15137915', 'It is well known that different species have different protein domain repertoires, and indeed that some protein domains are kingdom specific. This information has not yet been incorporated into statistical methods for finding domains in sequences of amino acids.'),
(90141, 2004, 'bmc', 'Use of a structural alphabet for analysis of short loops connecting repetitive structures', 'Fourrier, Laurent|Benros, Cristina|de Brevern, Alexandre G', 'Equipe de Bioinformatique Génomique et Moléculaire, INSERM E0346, Université Denis DIDEROT-Paris 7, case 7113, 2, place Jussieu, 75251 Paris Cedex 05, France. laurent.fourrier@ebgm.jussieu.fr|Equipe de Bioinformatique Génomique et Moléculaire, INSERM E0346, Université Denis DIDEROT-Paris 7, case 7113, 2, place Jussieu, 75251 Paris Cedex 05, France. laurent.fourrier@ebgm.jussieu.fr|Equipe de Bioinformatique Génomique et Moléculaire, INSERM E0346, Université Denis DIDEROT-Paris 7, case 7113, 2, place Jussieu, 75251 Paris Cedex 05, France. laurent.fourrier@ebgm.jussieu.fr', 'France|France|France', 52, 'Computational Biology|Molecular Sequence Data|Peptides|Predictive Value of Tests|Protein Conformation|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Repetitive Sequences, Amino Acid|Software', 'Journal Article', '10.1186/1471-2105-5-58', '15140270', 'Because loops connect regular secondary structures, analysis of the former depends directly on the definition of the latter. The numerous assignment methods, however, can offer different definitions. In a previous study, we defined a structural alphabet composed of 16 average protein fragments, which we called Protein Blocks (PBs). They allow an accurate description of every region of 3D protein backbones and have been used in local structure prediction. In the present study, we use this structural alphabet to analyze and predict the loops connecting two repetitive structures.'),
(90142, 2004, 'bmc', 'Gene finding in novel genomes', 'Korf, Ian', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. ik1@sanger.ac.uk', 'United Kingdom', 0, 'Animals|Arabidopsis|Caenorhabditis elegans|Computational Biology|Databases, Genetic|Drosophila melanogaster|Genes|Genes, Helminth|Genes, Insect|Genes, Plant|Genetic Variation|Genome|Genome, Plant|Predictive Value of Tests|Software', 'Journal Article', '10.1186/1471-2105-5-59', '15144565', 'Computational gene prediction continues to be an important problem, especially for genomes with little experimental data.'),
(90143, 2004, 'bmc', 'An approach to large scale identification of non-obvious structural similarities between proteins', 'Cherkasov, Artem|Jones, Steven J M', 'Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada. artc@interchange.ubc.ca|Department of Medicine, Faculty of Medicine, University of British Columbia, Vancouver, Canada. artc@interchange.ubc.ca', 'Canada|Canada', 0, 'Bacterial Proteins|Chlamydia trachomatis|Computational Biology|Genome, Bacterial|Genome, Human|Humans|Models, Biological|Protein Structure, Quaternary|Proteins|Sequence Alignment|Sequence Homology, Amino Acid|Virulence Factors', 'Comparative Study', '10.1186/1471-2105-5-61', '15147578', 'A new sequence independent bioinformatics approach allowing genome-wide search for proteins with similar three dimensional structures has been developed. By utilizing the numerical output of the sequence threading it establishes putative non-obvious structural similarities between proteins. When applied to the testing set of proteins with known three dimensional structures the developed approach was able to recognize structurally similar proteins with high accuracy.'),
(90144, 2004, 'bmc', 'Graphical technique for identifying a monotonic variance stabilizing transformation for absolute gene intensity signals', 'Archer, Kellie J|Dumur, Catherine I|Ramakrishnan, Viswanathan', 'Department of Biostatistics, Virginia Commonwealth University, Richmond, VA 23298, USA. kjarcher@vcu.edu|Department of Biostatistics, Virginia Commonwealth University, Richmond, VA 23298, USA. kjarcher@vcu.edu|Department of Biostatistics, Virginia Commonwealth University, Richmond, VA 23298, USA. kjarcher@vcu.edu', 'United States|United States|United States', 4, 'Computational Biology|Computer Graphics|DNA, Complementary|Gene Expression Profiling|Gene Expression Regulation|Genes|Humans|Image Processing, Computer-Assisted|Oligonucleotide Array Sequence Analysis|RNA, Complementary', 'Journal Article', '10.1186/1471-2105-5-60', '15147579', 'The usefulness of log2 transformation for cDNA microarray data has led to its widespread application to Affymetrix data. For Affymetrix data, where absolute intensities are indicative of number of transcripts, there is a systematic relationship between variance and magnitude of measurements. Application of the log2 transformation expands the scale of genes with low intensities while compressing the scale of genes with higher intensities thus reversing the mean by variance relationship. The usefulness of these transformations needs to be examined.'),
(90145, 2004, 'bmc', 'A fast algorithm for determining the best combination of local alignments to a query sequence', 'Conant, Gavin C|Wagner, Andreas', 'Department of Biology, The University of New Mexico, Albuquerque, NM, USA. gconant@unm.edu|Department of Biology, The University of New Mexico, Albuquerque, NM, USA. gconant@unm.edu', 'Mexico|Mexico', 0, 'Algorithms|Animals|Caenorhabditis elegans|Computational Biology|Computer Graphics|DNA, Helminth|DNA, Mitochondrial|Drosophila melanogaster|Genome|Genome, Human|Hagfishes|Humans|Mitochondria|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-5-62', '15149555', 'Existing sequence alignment algorithms assume that similarities between DNA or amino acid sequences are linearly ordered. That is, stretches of similar nucleotides or amino acids are in the same order in both sequences. Recombination perturbs this order. An algorithm that can reconstruct sequence similarity despite rearrangement would be helpful for reconstructing the evolutionary history of recombined sequences.'),
(90146, 2004, 'bmc', 'Spotting effect in microarray experiments', 'Mary-Huard, Tristan|Daudin, Jean-Jacques|Robin, Stéphane|Bitton, Frédérique|Cabannes, Eric|Hilson, Pierre', 'Institut National Agronomique Paris-Grignon, 75231 Paris, France. maryhuar@inapg.fr|Institut National Agronomique Paris-Grignon, 75231 Paris, France. maryhuar@inapg.fr|Institut National Agronomique Paris-Grignon, 75231 Paris, France. maryhuar@inapg.fr|Institut National Agronomique Paris-Grignon, 75231 Paris, France. maryhuar@inapg.fr|Institut National Agronomique Paris-Grignon, 75231 Paris, France. maryhuar@inapg.fr|Institut National Agronomique Paris-Grignon, 75231 Paris, France. maryhuar@inapg.fr', 'France|France|France|France|France|France', 0, 'Animals|Arabidopsis|DNA, Complementary|DNA, Plant|DNA, Protozoan|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Plant|Normal Distribution|Oligonucleotide Array Sequence Analysis|Plasmodium falciparum|Research Design', 'Comparative Study', '10.1186/1471-2105-5-63', '15151695', 'Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects data obtained with Cy3/Cy5 spotted glass arrays. It yields a periodic pattern altering both signal (Cy3/Cy5 ratio) and intensity across the array.'),
(90147, 2004, 'bmc', 'Feature selection for splice site prediction: a new method using EDA-based feature ranking', 'Saeys, Yvan|Degroeve, Sven|Aeyels, Dirk|Rouzé, Pierre|Van de Peer, Yves', 'Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Ghent, Belgium. yvan.saeys@psb.ugent.be|Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Ghent, Belgium. yvan.saeys@psb.ugent.be|Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Ghent, Belgium. yvan.saeys@psb.ugent.be|Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Ghent, Belgium. yvan.saeys@psb.ugent.be|Department of Plant Systems Biology, Ghent University, Flanders Interuniversity Institute for Biotechnology (VIB), Technologiepark 927, B-9052 Ghent, Belgium. yvan.saeys@psb.ugent.be', 'Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Adenosine|Algorithms|Arabidopsis|Base Composition|Chromosomes, Plant|Computational Biology|Databases, Genetic|Guanine|Predictive Value of Tests|RNA Splice Sites|RNA, Plant|Software|Software Validation', 'Comparative Study', '10.1186/1471-2105-5-64', '15154966', 'The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data.'),
(90148, 2004, 'bmc', 'Bioinformatics analysis of SARS coronavirus genome polymorphism', 'Pavlovic-Lazetic, Gordana M|Mitic, Nenad S|Beljanski, Milos V', 'Faculty of Mathematics, University of Belgrade, 11001 Belgrade, Serbia and Montenegro. gordana@matf.bg.ac.yu|Faculty of Mathematics, University of Belgrade, 11001 Belgrade, Serbia and Montenegro. gordana@matf.bg.ac.yu|Faculty of Mathematics, University of Belgrade, 11001 Belgrade, Serbia and Montenegro. gordana@matf.bg.ac.yu', 'Montenegro|Montenegro|Montenegro', 0, 'Amino Acid Sequence|Computational Biology|DNA, Viral|Genome, Viral|Mutagenesis, Insertional|Phylogeny|Polymorphism, Genetic|Polymorphism, Single Nucleotide|SARS Virus|Sequence Deletion|Viral Proteins', 'Comparative Study', '10.1186/1471-2105-5-65', '15161495', 'We have compared 38 isolates of the SARS-CoV complete genome. The main goal was twofold: first, to analyze and compare nucleotide sequences and to identify positions of single nucleotide polymorphism (SNP), insertions and deletions, and second, to group them according to sequence similarity, eventually pointing to phylogeny of SARS-CoV isolates. The comparison is based on genome polymorphism such as insertions or deletions and the number and positions of SNPs.'),
(90149, 2004, 'bmc', 'Esub8: a novel tool to predict protein subcellular localizations in eukaryotic organisms', 'Cui, Qinghua|Jiang, Tianzi|Liu, Bing|Ma, Songde', 'National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, P R China. qhcui@nlpr.ia.ac.cn|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, P R China. qhcui@nlpr.ia.ac.cn|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, P R China. qhcui@nlpr.ia.ac.cn|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, P R China. qhcui@nlpr.ia.ac.cn', 'China|China|China|China', 36, 'Computational Biology|Eukaryotic Cells|Predictive Value of Tests|Proteins|Software|Subcellular Fractions', 'Comparative Study', '10.1186/1471-2105-5-66', '15163352', 'Subcellular localization of a new protein sequence is very important and fruitful for understanding its function. As the number of new genomes has dramatically increased over recent years, a reliable and efficient system to predict protein subcellular location is urgently needed.'),
(90150, 2004, 'bmc', 'Genome SEGE: a database for intronless genes in eukaryotic genomes', 'Sakharkar, Meena Kishore|Kangueane, Pandjassarame', 'Nanyang Centre for Supercomputing and Visualization, School of Mechanical and Production Engineering, Nanyang Technological University, Singapore 639798. mmeena@ntu.edu.sg|Nanyang Centre for Supercomputing and Visualization, School of Mechanical and Production Engineering, Nanyang Technological University, Singapore 639798. mmeena@ntu.edu.sg', 'Singapore|Singapore', 0, 'Databases, Genetic|Eukaryotic Cells|Genes|Genome|Internet|Introns', 'Journal Article', '10.1186/1471-2105-5-67', '15175116', 'A number of completely sequenced eukaryotic genome data are available in the public domain. Eukaryotic genes are either intron containing or intronless. Eukaryotic intronless genes are interesting datasets for comparative genomics and evolutionary studies. The SEGE database containing a collection of eukaryotic single exon genes is available. However, SEGE is derived using GenBank. The redundant, incomplete and heterogeneous qualities of GenBank data are a bottleneck for biological investigation in comparative genomics and evolutionary studies. Such studies often require representative gene sets from each genome and this is possible only by deriving specific datasets from completely sequenced genome data. Thus Genome SEGE, a database for intronless genes in completely sequenced eukaryotic genomes, has been constructed.'),
(90151, 2004, 'bmc', 'Detection of chromosomal regions showing differential gene expression in human skeletal muscle and in alveolar rhabdomyosarcoma', 'Bisognin, Andrea|Bortoluzzi, Stefania|Danieli, Gian Antonio', 'Department of Biology, University of Padua, 35131, Padova, Italy. bisio@medgen.univr.it|Department of Biology, University of Padua, 35131, Padova, Italy. bisio@medgen.univr.it|Department of Biology, University of Padua, 35131, Padova, Italy. bisio@medgen.univr.it', 'Italy|Italy|Italy', 5, 'Chromosome Mapping|Chromosomes, Human, X|Down-Regulation|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Genome, Human|Humans|Muscle, Skeletal|Oligonucleotide Array Sequence Analysis|Rhabdomyosarcoma, Alveolar|Software', 'Comparative Study', '10.1186/1471-2105-5-68', '15176974', 'Rhabdomyosarcoma is a relatively common tumour of the soft tissue, probably due to regulatory disruption of growth and differentiation of skeletal muscle stem cells. Identification of genes differentially expressed in normal skeletal muscle and in rhabdomyosarcoma may help in understanding mechanisms of tumour development, in discovering diagnostic and prognostic markers and in identifying novel targets for drug therapy.'),
(90152, 2004, 'bmc', 'Coronavirus 3CLpro proteinase cleavage sites: possible relevance to SARS virus pathology', 'Kiemer, Lars|Lund, Ole|Brunak, Søren|Blom, Nikolaj', 'Center for Biological Sequence Analysis BioCentrum-DTU, Technical University of Denmark DK-2800 Lyngby. lars@cbs.dtu.dk|Center for Biological Sequence Analysis BioCentrum-DTU, Technical University of Denmark DK-2800 Lyngby. lars@cbs.dtu.dk|Center for Biological Sequence Analysis BioCentrum-DTU, Technical University of Denmark DK-2800 Lyngby. lars@cbs.dtu.dk|Center for Biological Sequence Analysis BioCentrum-DTU, Technical University of Denmark DK-2800 Lyngby. lars@cbs.dtu.dk', 'Denmark|Denmark|Denmark|Denmark', 34, 'Artificial Intelligence|Binding Sites|Coronavirus 229E, Human|Cysteine Endopeptidases|Humans|Neural Networks (Computer)|Proteins|SARS Virus|Sequence Analysis, DNA|Severe Acute Respiratory Syndrome', 'Journal Article', '10.1186/1471-2105-5-72', '15180906', 'Despite the passing of more than a year since the first outbreak of Severe Acute Respiratory Syndrome (SARS), efficient counter-measures are still few and many believe that reappearance of SARS, or a similar disease caused by a coronavirus, is not unlikely. For other virus families like the picornaviruses it is known that pathology is related to proteolytic cleavage of host proteins by viral proteinases. Furthermore, several studies indicate that virus proliferation can be arrested using specific proteinase inhibitors supporting the belief that proteinases are indeed important during infection. Prompted by this, we set out to analyse and predict cleavage by the coronavirus main proteinase using computational methods.'),
(90153, 2004, 'bmc', 'Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction', 'Dowell, Robin D|Eddy, Sean R', 'Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, St, Louis, MO 63108 USA. robin@genetics.wustl.edu|Howard Hughes Medical Institute and Department of Genetics, Washington University School of Medicine, St, Louis, MO 63108 USA. robin@genetics.wustl.edu', 'United States|United States', 0, 'Computational Biology|Models, Statistical|Nucleic Acid Conformation|Predictive Value of Tests|RNA|Stochastic Processes', 'Evaluation Studies', '10.1186/1471-2105-5-71', '15180907', 'RNA secondary structure prediction methods based on probabilistic modeling can be developed using stochastic context-free grammars (SCFGs). Such methods can readily combine different sources of information that can be expressed probabilistically, such as an evolutionary model of comparative RNA sequence analysis and a biophysical model of structure plausibility. However, the number of free parameters in an integrated model for consensus RNA structure prediction can become untenable if the underlying SCFG design is too complex. Thus a key question is, what small, simple SCFG designs perform best for RNA secondary structure prediction?');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90154, 2004, 'bmc', 'Multiclass discovery in array data', 'Liu, Yingchun|Ringnér, Markus', 'Department of Theoretical Physics, Lund University, Sölvegatan 14A, SE-223 62 Lund, Sweden. spring@thep.lu.se|Department of Theoretical Physics, Lund University, Sölvegatan 14A, SE-223 62 Lund, Sweden. spring@thep.lu.se', 'Sweden|Sweden', 10, 'Breast Neoplasms|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Humans|Oligonucleotide Array Sequence Analysis|Software|Software Validation', 'Journal Article', '10.1186/1471-2105-5-70', '15180908', 'A routine goal in the analysis of microarray data is to identify genes with expression levels that correlate with known classes of experiments. In a growing number of array data sets, it has been shown that there is an over-abundance of genes that discriminate between known classes as compared to expectations for random classes. Therefore, one can search for novel classes in array data by looking for partitions of experiments for which there are an over-abundance of discriminatory genes. We have previously used such an approach in a breast cancer study.'),
(90155, 2004, 'bmc', 'pdb-care (PDB carbohydrate residue check): a program to support annotation of complex carbohydrate structures in PDB files', 'Lütteke, Thomas|von der Lieth, Claus-W', 'German Cancer Research Center, Central Spectroscopic Department, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. t.luetteke@dkfz-heidelberg.de|German Cancer Research Center, Central Spectroscopic Department, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. t.luetteke@dkfz-heidelberg.de', 'Germany|Germany', 116, 'Carbohydrate Conformation|Carbohydrate Sequence|Carbohydrates|Software', 'Journal Article', '10.1186/1471-2105-5-69', '15180909', 'Carbohydrates are involved in a variety of fundamental biological processes and pathological situations. They therefore have a large pharmaceutical and diagnostic potential. Knowledge of the 3D structure of glycans is a prerequisite for a complete understanding of their biological functions. The largest source of biomolecular 3D structures is the Protein Data Bank. However, about 30% of all 1663 PDB entries (version September 2003) containing carbohydrates comprise errors in glycan description. Unfortunately, no software is currently available which aligns the 3D information with the reported assignments. It is the aim of this work to fill this gap.'),
(90156, 2004, 'bmc', 'Correction: Benchmarking tools for the alignment of functional noncoding DNA', 'Pollard, D A|Bergman, C M|Stoye, J|Celniker, S E|Eisen, M B', 'University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu|University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu|University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu|University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu|University of California, Berkeley, CA 94720, USA. dpollard@socrates.berkeley.edu', 'United States|United States|United States|United States|United States', 3, 'Benchmarking', 'Journal Article', '10.1186/1471-2105-5-73', '15186509', '-'),
(90157, 2004, 'bmc', 'A Bayesian method for identifying missing enzymes in predicted metabolic pathway databases', 'Green, Michelle L|Karp, Peter D', 'Bioinformatics Research Group, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA. green@ai.sri.com|Bioinformatics Research Group, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, USA. green@ai.sri.com', 'United States|United States', 0, 'Amino Acid Oxidoreductases|Bacterial Proteins|Bayes Theorem|Carbon-Nitrogen Ligases with Glutamine as Amide-N-Donor|Caulobacter crescentus|Computational Biology|Databases, Factual|Escherichia coli Proteins|Models, Statistical|Multienzyme Complexes|Mycobacterium tuberculosis|Nicotinamide-Nucleotide Adenylyltransferase|Predictive Value of Tests|Pyridines|Software|Software Validation|Vibrio cholerae', 'Journal Article', '10.1186/1471-2105-5-76', '15189570', 'The PathoLogic program constructs Pathway/Genome databases by using a genomes annotation to predict the set of metabolic pathways present in an organism. PathoLogic determines the set of reactions composing those pathways from the enzymes annotated in the organisms genome. Most annotation efforts fail to assign function to 40-60% of sequences. In addition, large numbers of sequences may have non-specific annotations (e.g., thiolase family protein). Pathway holes occur when a genome appears to lack the enzymes needed to catalyze reactions in a pathway. If a protein has not been assigned a specific function during the annotation process, any reaction catalyzed by that protein will appear as a missing enzyme or pathway hole in a Pathway/Genome database.'),
(90158, 2004, 'bmc', 'Interaction profile-based protein classification of death domain', 'Lett, Drew|Hsing, Michael|Pio, Frederic', 'Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, B,C, Canada, V5A 1S6. dclett@sfu.ca|Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, B,C, Canada, V5A 1S6. dclett@sfu.ca|Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, B,C, Canada, V5A 1S6. dclett@sfu.ca', 'Canada|Canada|Canada', 0, 'Humans|Peptides|Predictive Value of Tests|Protein Interaction Mapping|Protein Structure, Quaternary|Proteins|Proteomics|Software', 'Journal Article', '10.1186/1471-2105-5-75', '15189571', 'The increasing number of protein sequences and 3D structure obtained from genomic initiatives is leading many of us to focus on proteomics, and to dedicate our experimental and computational efforts on the creation and analysis of information derived from 3D structure. In particular, the high-throughput generation of protein-protein interaction data from a few organisms makes such an approach very important towards understanding the molecular recognition that make-up the entire protein-protein interaction network. Since the generation of sequences, and experimental protein-protein interactions increases faster than the 3D structure determination of protein complexes, there is tremendous interest in developing in silico methods that generate such structure for prediction and classification purposes. In this study we focused on classifying protein family members based on their protein-protein interaction distinctiveness. Structure-based classification of protein-protein interfaces has been described initially by Ponstingl et al. 1 and more recently by Valdar et al. 2 and Mintseris et al. 3, from complex structures that have been solved experimentally. However, little has been done on protein classification based on the prediction of protein-protein complexes obtained from homology modeling and docking simulation.'),
(90159, 2004, 'bmc', 'M-CGH: analysing microarray-based CGH experiments', 'Wang, Junbai|Meza-Zepeda, Leonardo A|Kresse, Stine H|Myklebost, Ola', 'Department of Tumor Biology, The Norwegian Radium Hospital, Montebello, N-0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, The Norwegian Radium Hospital, Montebello, N-0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, The Norwegian Radium Hospital, Montebello, N-0310 Oslo, Norway. junbaiw@radium.uio.no|Department of Tumor Biology, The Norwegian Radium Hospital, Montebello, N-0310 Oslo, Norway. junbaiw@radium.uio.no', 'Norway|Norway|Norway|Norway', 0, 'Chromosomes, Artificial, Bacterial|Chromosomes, Artificial, P1 Bacteriophage|Chromosomes, Human, Pair 1|Computer Graphics|DNA, Neoplasm|Fuzzy Logic|Genes, Neoplasm|Genes, Tumor Suppressor|Genome, Human|Humans|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Oncogenes|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-5-74', '15189572', 'Microarray-based comparative genomic hybridisation (array CGH) is a technique by which variation in relative copy numbers between two genomes can be analysed by competitive hybridisation to DNA microarrays. This technology has most commonly been used to detect chromosomal amplifications and deletions in cancer. Dedicated tools are needed to analyse the results of such experiments, which include appropriate visualisation, and to take into consideration the physical relation in the genome between the probes on the array.'),
(90160, 2004, 'bmc', 'Comparing transformation methods for DNA microarray data', 'Thygesen, Helene H|Zwinderman, Aeilko H', 'Clinical Epidemiology and Biostatistics, Academisch Medisch Centrum, University of Amsterdam, 1100 DD, Netherlands. h.h.thygesen@amc.uva.nl|Clinical Epidemiology and Biostatistics, Academisch Medisch Centrum, University of Amsterdam, 1100 DD, Netherlands. h.h.thygesen@amc.uva.nl', 'Netherlands|Netherlands', 0, 'Animals|Confidence Intervals|Data Interpretation, Statistical|Kidney|Liver|Male|Mice|Oligonucleotide Array Sequence Analysis|Organ Specificity|Reference Values|Reproducibility of Results|Testis', 'Comparative Study', '10.1186/1471-2105-5-77', '15202953', 'When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer.'),
(90161, 2004, 'bmc', 'Boosting accuracy of automated classification of fluorescence microscope images for location proteomics', 'Huang, Kai|Murphy, Robert F', 'Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213 USA. khuang@andrew.cmu.edu|Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213 USA. khuang@andrew.cmu.edu', 'United States|United States', 110, 'Cell Line, Tumor|Computational Biology|HeLa Cells|Humans|Imaging, Three-Dimensional|Intracellular Space|Microscopy, Fluorescence|Proteomics|Sensitivity and Specificity', 'Comparative Study', '10.1186/1471-2105-5-78', '15207009', 'Detailed knowledge of the subcellular location of each expressed protein is critical to a full understanding of its function. Fluorescence microscopy, in combination with methods for fluorescent tagging, is the most suitable current method for proteome-wide determination of subcellular location. Previous work has shown that neural network classifiers can distinguish all major protein subcellular location patterns in both 2D and 3D fluorescence microscope images. Building on these results, we evaluate here new classifiers and features to improve the recognition of protein subcellular location patterns in both 2D and 3D fluorescence microscope images.'),
(90162, 2004, 'bmc', 'PhosphoELM: a database of experimentally verified phosphorylation sites in eukaryotic proteins', 'Diella, Francesca|Cameron, Scott|Gemünd, Christine|Linding, Rune|Via, Allegra|Kuster, Bernhard|Sicheritz-Pontén, Thomas|Blom, Nikolaj|Gibson, Toby J', 'Cellzome AG, Heidelberg, Germany. diella@embl.de|Cellzome AG, Heidelberg, Germany. diella@embl.de|Cellzome AG, Heidelberg, Germany. diella@embl.de|Cellzome AG, Heidelberg, Germany. diella@embl.de|Cellzome AG, Heidelberg, Germany. diella@embl.de|Cellzome AG, Heidelberg, Germany. diella@embl.de|Cellzome AG, Heidelberg, Germany. diella@embl.de|Cellzome AG, Heidelberg, Germany. diella@embl.de|Cellzome AG, Heidelberg, Germany. diella@embl.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Animals|Binding Sites|Databases, Protein|Humans|Mice|Phosphorylation|Protein Processing, Post-Translational|Proteins|Rats|Research Design|Software', 'Journal Article', '10.1186/1471-2105-5-79', '15212693', 'Post-translational phosphorylation is one of the most common protein modifications. Phosphoserine, threonine and tyrosine residues play critical roles in the regulation of many cellular processes. The fast growing number of research reports on protein phosphorylation points to a general need for an accurate database dedicated to phosphorylation to provide easily retrievable information on phosphoproteins.'),
(90163, 2004, 'bmc', 'Mistaken identifiers: gene name errors can be introduced inadvertently when using Excel in bioinformatics', 'Zeeberg, Barry R|Riss, Joseph|Kane, David W|Bussey, Kimberly J|Uchio, Edward|Linehan, W Marston|Barrett, J Carl|Weinstein, John N', 'Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892 USA. barry@discover.nci.nih.gov|Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892 USA. barry@discover.nci.nih.gov|Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892 USA. barry@discover.nci.nih.gov|Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892 USA. barry@discover.nci.nih.gov|Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892 USA. barry@discover.nci.nih.gov|Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892 USA. barry@discover.nci.nih.gov|Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892 USA. barry@discover.nci.nih.gov|Genomics & Bioinformatics Group, Laboratory of Molecular Pharmacology, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, MD 20892 USA. barry@discover.nci.nih.gov', 'United States|United States|United States|United States|United States|United States|United States|United States', 52, 'Animals|Computational Biology|Genes|Humans|Mice|Oligonucleotide Array Sequence Analysis|Research Design|Software', 'Journal Article', '10.1186/1471-2105-5-80', '15214961', 'When processing microarray data sets, we recently noticed that some gene names were being changed inadvertently to non-gene names.'),
(90164, 2004, 'bmc', 'Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes', 'Jiang, Hongying|Deng, Youping|Chen, Huann-Sheng|Tao, Lin|Sha, Qiuying|Chen, Jun|Tsai, Chung-Jui|Zhang, Shuanglin', 'Department of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA. hojiang@mtu.edu|Department of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA. hojiang@mtu.edu|Department of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA. hojiang@mtu.edu|Department of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA. hojiang@mtu.edu|Department of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA. hojiang@mtu.edu|Department of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA. hojiang@mtu.edu|Department of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA. hojiang@mtu.edu|Department of Mathematical Sciences, Michigan Technological University, Houghton, MI 49931, USA. hojiang@mtu.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 190, 'Adenocarcinoma|Age Distribution|Biomarkers, Tumor|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Humans|Lung Neoplasms|Male|Oligonucleotide Array Sequence Analysis|Predictive Value of Tests|Reproducibility of Results|Sex Distribution', 'Comparative Study', '10.1186/1471-2105-5-81', '15217521', 'Due to the high cost and low reproducibility of many microarray experiments, it is not surprising to find a limited number of patient samples in each study, and very few common identified marker genes among different studies involving patients with the same disease. Therefore, it is of great interest and challenge to merge data sets from multiple studies to increase the sample size, which may in turn increase the power of statistical inferences. In this study, we combined two lung cancer studies using microarray GeneChip, employed two gene shaving methods and a two-step survival test to identify genes with expression patterns that can distinguish diseased from normal samples, and to indicate patient survival, respectively.'),
(90165, 2004, 'bmc', 'Asynchronous adaptive time step in quantitative cellular automata modeling', 'Zhu, Hao|Pang, Peter Y H|Sun, Yan|Dhar, Pawan', 'Bioinformatics Institute, National University of Singapore, 138671. zhuhao@bii.a-star.edu.sg|Bioinformatics Institute, National University of Singapore, 138671. zhuhao@bii.a-star.edu.sg|Bioinformatics Institute, National University of Singapore, 138671. zhuhao@bii.a-star.edu.sg|Bioinformatics Institute, National University of Singapore, 138671. zhuhao@bii.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore', 3, 'Animals|Computational Biology|Computer Simulation|Electrophysiology|Models, Biological|Myocardium|Time', 'Journal Article', '10.1186/1471-2105-5-85', '15222901', 'The behaviors of cells in metazoans are context dependent, thus large-scale multi-cellular modeling is often necessary, for which cellular automata are natural candidates. Two related issues are involved in cellular automata based multi-cellular modeling: how to introduce differential equation based quantitative computing to precisely describe cellular activity, and upon it, how to solve the heavy time consumption issue in simulation.'),
(90166, 2004, 'bmc', 'Visualization and analysis of microarray and gene ontology data with treemaps', 'Baehrecke, Eric H|Dang, Niem|Babaria, Ketan|Shneiderman, Ben', 'University of Maryland Biotechnology Institute, College Park, Maryland 20742, USA. baehreck@umbi.umd.edu|University of Maryland Biotechnology Institute, College Park, Maryland 20742, USA. baehreck@umbi.umd.edu|University of Maryland Biotechnology Institute, College Park, Maryland 20742, USA. baehreck@umbi.umd.edu|University of Maryland Biotechnology Institute, College Park, Maryland 20742, USA. baehreck@umbi.umd.edu', 'United States|United States|United States|United States', 60, 'Animals|Computational Biology|Computer Graphics|Databases, Genetic|Drosophila melanogaster|Gene Expression Profiling|Genes, Insect|Genome|Internet|Oligonucleotide Array Sequence Analysis|RNA|Salivary Glands|Software', 'Journal Article', '10.1186/1471-2105-5-84', '15222902', 'The increasing complexity of genomic data presents several challenges for biologists. Limited computer monitor views of data complexity and the dynamic nature of data in the midst of discovery increase the challenge of integrating experimental results with information resources. The use of Gene Ontology enables researchers to summarize results of quantitative analyses in this framework, but the limitations of typical browser presentation restrict data access.'),
(90167, 2004, 'bmc', 'The MB2 gene family of Plasmodium species has a unique combination of S1 and GTP-binding domains', 'Romero, Lisa C|Nguyen, Thanh V|Deville, Benoit|Ogunjumo, Oluwasanmi|James, Anthony A', 'Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697-3900, USA. lopie@uci.edu|Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697-3900, USA. lopie@uci.edu|Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697-3900, USA. lopie@uci.edu|Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697-3900, USA. lopie@uci.edu|Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697-3900, USA. lopie@uci.edu', 'United States|United States|United States|United States|United States', 6, 'Amino Acid Sequence|Animals|Conserved Sequence|DNA, Protozoan|GTP-Binding Proteins|Genome, Protozoan|Molecular Sequence Data|Multigene Family|Open Reading Frames|Peptides|Plasmodium|Plasmodium berghei|Plasmodium falciparum|Plasmodium gallinaceum|Plasmodium knowlesi|Plasmodium yoelii|Protein Sorting Signals|Protein Structure, Tertiary|Protozoan Proteins|Repetitive Sequences, Amino Acid', 'Journal Article', '10.1186/1471-2105-5-83', '15222903', 'Identification and characterization of novel Plasmodium gene families is necessary for developing new anti-malarial therapeutics. The products of the Plasmodium falciparum gene, MB2, were shown previously to have a stage-specific pattern of subcellular localization and proteolytic processing.'),
(90168, 2004, 'bmc', 'mlstdbNet - distributed multi-locus sequence typing (MLST) databases', 'Jolley, Keith A|Chan, Man-Suen|Maiden, Martin C J', 'The Peter Medawar Building for Pathogen Research and Department of Zoology, University of Oxford, OX1 3SY, UK. keith.jolley@medawar.ox.ac.uk|The Peter Medawar Building for Pathogen Research and Department of Zoology, University of Oxford, OX1 3SY, UK. keith.jolley@medawar.ox.ac.uk|The Peter Medawar Building for Pathogen Research and Department of Zoology, University of Oxford, OX1 3SY, UK. keith.jolley@medawar.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 406, 'Bacterial Typing Techniques|Base Sequence|DNA, Bacterial|Databases, Nucleic Acid|Software|Species Specificity', 'Comparative Study', '10.1186/1471-2105-5-86', '15230973', 'Multi-locus sequence typing (MLST) is a method of typing that facilitates the discrimination of microbial isolates by comparing the sequences of housekeeping gene fragments. The mlstdbNet software enables the implementation of distributed web-accessible MLST databases that can be linked widely over the Internet.'),
(90169, 2004, 'bmc', 'galaxieEST: addressing EST identity through automated phylogenetic analysis', 'Nilsson, R Henrik|Rajashekar, Balaji|Larsson, Karl-Henrik|Ursing, Björn M', 'Götenborg University, Botanical Institute, SE-405 30, Sweden. henrik.nilsson@botany.gu.se|Götenborg University, Botanical Institute, SE-405 30, Sweden. henrik.nilsson@botany.gu.se|Götenborg University, Botanical Institute, SE-405 30, Sweden. henrik.nilsson@botany.gu.se|Götenborg University, Botanical Institute, SE-405 30, Sweden. henrik.nilsson@botany.gu.se', 'Sweden|Sweden|Sweden|Sweden', 0, 'Computational Biology|Expressed Sequence Tags|Phylogeny|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-5-87', '15236648', 'Research involving expressed sequence tags (ESTs) is intricately coupled to the existence of large, well-annotated sequence repositories. Comparatively complete and satisfactory annotated public sequence libraries are, however, available only for a limited range of organisms, rendering the absence of sequences and gene structure information a tangible problem for those working with taxa lacking an EST or genome sequencing project. Paralogous genes belonging to the same gene family but distinguished by derived characteristics are particularly prone to misidentification and erroneous annotation, high but incomplete levels of sequence similarity are typically difficult to interpret and have formed the basis of many unsubstantiated assumptions of orthology. In these cases, a phylogenetic study of the query sequence together with the most similar sequences in the database may be of great value to the identification process. In order to facilitate this laborious procedure, a project to employ automated phylogenetic analysis in the identification of ESTs was initiated.'),
(90170, 2004, 'bmc', 'A double classification tree search algorithm for index SNP selection', 'Zhang, Peisen|Sheng, Huitao|Uehara, Ryuhei', 'Laboratory of Population Genetics, National Cancer Institute, NIH, Bethesda, MD 20892, USA. zhangpeis@mail.nih.gov|Laboratory of Population Genetics, National Cancer Institute, NIH, Bethesda, MD 20892, USA. zhangpeis@mail.nih.gov|Laboratory of Population Genetics, National Cancer Institute, NIH, Bethesda, MD 20892, USA. zhangpeis@mail.nih.gov', 'United States|United States|United States', 18, 'Algorithms|Computational Biology|Haplotypes|Polymorphism, Single Nucleotide|Selection, Genetic|Software|Software Design', 'Journal Article', '10.1186/1471-2105-5-89', '15238162', 'In population-based studies, it is generally recognized that single nucleotide polymorphism (SNP) markers are not independent. Rather, they are carried by haplotypes, groups of SNPs that tend to be coinherited. It is thus possible to choose a much smaller number of SNPs to use as indices for identifying haplotypes or haplotype blocks in genetic association studies. We refer to these characteristic SNPs as index SNPs. In order to reduce costs and work, a minimum number of index SNPs that can distinguish all SNP and haplotype patterns should be chosen. Unfortunately, this is an NP-complete problem, requiring brute force algorithms that are not feasible for large data sets.'),
(90171, 2004, 'bmc', 'RAG: RNA-As-Graphs web resource', 'Fera, Daniela|Kim, Namhee|Shiffeldrim, Nahum|Zorn, Julie|Laserson, Uri|Gan, Hin Hark|Schlick, Tamar', 'Department of Chemistry, New York University, New York, NY 10003, USA. df448@nyu.edu|Department of Chemistry, New York University, New York, NY 10003, USA. df448@nyu.edu|Department of Chemistry, New York University, New York, NY 10003, USA. df448@nyu.edu|Department of Chemistry, New York University, New York, NY 10003, USA. df448@nyu.edu|Department of Chemistry, New York University, New York, NY 10003, USA. df448@nyu.edu|Department of Chemistry, New York University, New York, NY 10003, USA. df448@nyu.edu|Department of Chemistry, New York University, New York, NY 10003, USA. df448@nyu.edu', 'United States|United States|United States|United States|United States|United States|United States', 45, 'Computational Biology|Computer Graphics|Databases, Nucleic Acid|Internet|RNA|Software|Software Design', 'Journal Article', '10.1186/1471-2105-5-88', '15238163', 'The proliferation of structural and functional studies of RNA has revealed an increasing range of RNAs structural repertoire. Toward the objective of systematic cataloguing of RNAs structural repertoire, we have recently described the basis of a graphical approach for organizing RNA secondary structures, including existing and hypothetical motifs.'),
(90172, 2004, 'bmc', 'SPOC: a widely distributed domain associated with cancer, apoptosis and transcription', 'Sánchez-Pulido, Luis|Rojas, Ana M|van Wely, Karel H|Martinez-A, Carlos|Valencia, Alfonso', 'Protein Design Group, Centro Nacional de Biotecnología (CNB-CSIC), Cantoblanco, E-28049 Madrid, Spain. sanchez@cnb.uam.es|Protein Design Group, Centro Nacional de Biotecnología (CNB-CSIC), Cantoblanco, E-28049 Madrid, Spain. sanchez@cnb.uam.es|Protein Design Group, Centro Nacional de Biotecnología (CNB-CSIC), Cantoblanco, E-28049 Madrid, Spain. sanchez@cnb.uam.es|Protein Design Group, Centro Nacional de Biotecnología (CNB-CSIC), Cantoblanco, E-28049 Madrid, Spain. sanchez@cnb.uam.es|Protein Design Group, Centro Nacional de Biotecnología (CNB-CSIC), Cantoblanco, E-28049 Madrid, Spain. sanchez@cnb.uam.es', 'Spain|Spain|Spain|Spain|Spain', 0, 'Amino Acid Sequence|Animals|Apoptosis|Arabidopsis Proteins|Caenorhabditis elegans Proteins|Conserved Sequence|Drosophila Proteins|Humans|Molecular Sequence Data|Neoplasms|Peptides|Plasmodium|Protein Structure, Tertiary|Proteins|Protozoan Proteins|Saccharomyces cerevisiae Proteins|Sequence Homology, Amino Acid|Signal Recognition Particle|Transcription, Genetic|Xenopus Proteins', 'Comparative Study', '10.1186/1471-2105-5-91', '15239844', 'The Split ends (Spen) family are large proteins characterised by N-terminal RNA recognition motifs (RRMs) and a conserved SPOC (Spen paralog and ortholog C-terminal) domain. The aim of this study is to characterize the family at the sequence level.'),
(90173, 2004, 'bmc', 'Global features of sequences of bacterial chromosomes, plasmids and phages revealed by analysis of oligonucleotide usage patterns', 'Reva, Oleg N|Tümmler, Burkhard', 'Klinische Forschergruppe, OE6711, Medizinische Hochschule Hannover, Carl-Neuberg-Strasse 1, D-30625 Hanover, Germany. reva.oleg@mh-hannover.de|Klinische Forschergruppe, OE6711, Medizinische Hochschule Hannover, Carl-Neuberg-Strasse 1, D-30625 Hanover, Germany. reva.oleg@mh-hannover.de', 'Germany|Germany', 42, 'Bacteriophages|Base Composition|Chromosomes, Bacterial|Cyanobacteria|DNA, Bacterial|DNA, Viral|Genetic Variation|Genome, Bacterial|Nucleic Acid Conformation|Oligonucleotides|Plasmids|Xylella', 'Comparative Study', '10.1186/1471-2105-5-90', '15239845', 'Oligonucleotide frequencies were shown to be conserved signatures for bacterial genomes, however, the underlying constraints have yet not been resolved in detail. In this paper we analyzed oligonucleotide usage (OU) biases in a comprehensive collection of 155 completely sequenced bacterial chromosomes, 316 plasmids and 104 phages.'),
(90174, 2004, 'bmc', 'Delayed impact: ISIs citation tracking choices are keeping scientists in the dark', 'Cockerill, Matthew J', 'BioMed Central Ltd, 34-42, Middlesex House, London, W1T 4LB, UK. matt@biomedcentral.com', 'United Kingdom', 9, 'Databases, Bibliographic|Humans|Periodicals as Topic|Quality Control|Reference Standards|Science', 'Journal Article', '10.1186/1471-2105-5-93', '15248902', '-'),
(90175, 2004, 'bmc', 'Target SNP selection in complex disease association studies', 'Wjst, Matthias', 'Gruppe Molekulare Epidemiologie, Institut für Epidemiologie, GSF - Forschungszentrum für Umwelt und Gesundheit, Ingolstädter Landstrasse 1, D-85758 Neuherberg/Munich, Germany. wjst@gsf.de', 'Germany', 0, 'Amino Acid Substitution|Chromosome Mapping|Chromosomes, Human, Pair 6|Computational Biology|Databases, Genetic|Exons|Genes|Genetic Linkage|Genetic Variation|Genome, Human|Humans|Introns|Mutation, Missense|Polymorphism, Single Nucleotide', 'Comparative Study', '10.1186/1471-2105-5-92', '15248903', 'The massive amount of SNP data stored at public internet sites provides unprecedented access to human genetic variation. Selecting target SNP for disease-gene association studies is currently done more or less randomly as decision rules for the selection of functional relevant SNPs are not available.'),
(90176, 2004, 'bmc', 'Clustering proteins from interaction networks for the prediction of cellular functions', 'Brun, Christine|Herrmann, Carl|Guénoche, Alain', 'Laboratoire de Génétique et Physiologie du Développement, IBDM, CNRS/INSERM/Université de la Méditerranée. herrmann@ibdm.univ-mrs.fr|Laboratoire de Génétique et Physiologie du Développement, IBDM, CNRS/INSERM/Université de la Méditerranée. herrmann@ibdm.univ-mrs.fr|Laboratoire de Génétique et Physiologie du Développement, IBDM, CNRS/INSERM/Université de la Méditerranée. herrmann@ibdm.univ-mrs.fr', '-|-|-', 0, 'Cluster Analysis|Computational Biology|Computer Graphics|Predictive Value of Tests|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Comparative Study', '10.1186/1471-2105-5-95', '15251039', 'Developing reliable and efficient strategies allowing to infer a function to yet uncharacterized proteins based on interaction networks is of crucial interest in the current context of high-throughput data generation. In this paper, we develop a new algorithm for clustering vertices of a protein-protein interaction network using a density function, providing disjoint classes.'),
(90177, 2004, 'bmc', 'Detection of transposable elements by their compositional bias', 'Andrieu, Olivier|Fiston, Anna-Sophie|Anxolabéhère, Dominique|Quesneville, Hadi', 'Laboratoire Dynamique du Génome et Evolution, Institut Jacques Monod, Tour 42-32, 5 place Jussieu, 75251 Paris, France. andrieu@ijm.jussieu.fr|Laboratoire Dynamique du Génome et Evolution, Institut Jacques Monod, Tour 42-32, 5 place Jussieu, 75251 Paris, France. andrieu@ijm.jussieu.fr|Laboratoire Dynamique du Génome et Evolution, Institut Jacques Monod, Tour 42-32, 5 place Jussieu, 75251 Paris, France. andrieu@ijm.jussieu.fr|Laboratoire Dynamique du Génome et Evolution, Institut Jacques Monod, Tour 42-32, 5 place Jussieu, 75251 Paris, France. andrieu@ijm.jussieu.fr', 'France|France|France|France', 18, 'Animals|Arabidopsis|Base Composition|Caenorhabditis elegans|DNA|DNA Transposable Elements|DNA, Helminth|DNA, Plant|Dinucleotide Repeats|Drosophila melanogaster|Gene Amplification|Models, Genetic|Models, Statistical|Predictive Value of Tests', 'Comparative Study', '10.1186/1471-2105-5-94', '15251040', 'Transposable elements (TE) are mobile genetic entities present in nearly all genomes. Previous work has shown that TEs tend to have a different nucleotide composition than the host genes, either considering codon usage bias or dinucleotide frequencies. We show here how these compositional differences can be used as a tool for detection and analysis of TE sequences.'),
(90178, 2004, 'bmc', 'Base-By-Base: single nucleotide-level analysis of whole viral genome alignments', 'Brodie, Ryan|Smith, Alex J|Roper, Rachel L|Tcherepanov, Vasily|Upton, Chris', 'Biochemistry and Microbiology, University of Victoria, B,C, V8W 3P6 Canada. ryan@ryanbrodie.com|Biochemistry and Microbiology, University of Victoria, B,C, V8W 3P6 Canada. ryan@ryanbrodie.com|Biochemistry and Microbiology, University of Victoria, B,C, V8W 3P6 Canada. ryan@ryanbrodie.com|Biochemistry and Microbiology, University of Victoria, B,C, V8W 3P6 Canada. ryan@ryanbrodie.com|Biochemistry and Microbiology, University of Victoria, B,C, V8W 3P6 Canada. ryan@ryanbrodie.com', 'Canada|Canada|Canada|Canada|Canada', 0, 'Base Composition|Computational Biology|Computer Graphics|Computer Systems|DNA, Viral|Databases, Genetic|Fuzzy Logic|Genome, Viral|Mutation|Nucleotides|Programming Languages|Regulatory Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Software|Variola virus', 'Comparative Study', '10.1186/1471-2105-5-96', '15253776', 'With ever increasing numbers of closely related virus genomes being sequenced, it has become desirable to be able to compare two genomes at a level more detailed than gene content because two strains of an organism may share the same set of predicted genes but still differ in their pathogenicity profiles. For example, detailed comparison of multiple isolates of the smallpox virus genome (each approximately 200 kb, with 200 genes) is not feasible without new bioinformatics tools.'),
(90179, 2004, 'bmc', 'Two-stage normalization using background intensities in cDNA microarray data', 'Yoon, Dankyu|Yi, Sung-Gon|Kim, Ju-Han|Park, Taesung', 'Seoul National University, San56-l, Shin Lim-Dong, Kwan Ak-Ku, Seoul 151-747, Republic of Korea. avanti@chollian.net|Seoul National University, San56-l, Shin Lim-Dong, Kwan Ak-Ku, Seoul 151-747, Republic of Korea. avanti@chollian.net|Seoul National University, San56-l, Shin Lim-Dong, Kwan Ak-Ku, Seoul 151-747, Republic of Korea. avanti@chollian.net|Seoul National University, San56-l, Shin Lim-Dong, Kwan Ak-Ku, Seoul 151-747, Republic of Korea. avanti@chollian.net', '-|-|-|-', 11, 'Cell Line, Tumor|DNA, Complementary|DNA, Neoplasm|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Variation|Humans|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1186/1471-2105-5-97', '15268767', 'In the microarray experiment, many undesirable systematic variations are commonly observed. Normalization is the process of removing such variation that affects the measured gene expression levels. Normalization plays an important role in the earlier stage of microarray data analysis. The subsequent analysis results are highly dependent on normalization. One major source of variation is the background intensities. Recently, some methods have been employed for correcting the background intensities. However, all these methods focus on defining signal intensities appropriately from foreground and background intensities in the image analysis. Although a number of normalization methods have been proposed, no systematic methods have been proposed using the background intensities in the normalization process.'),
(90180, 2004, 'bmc', 'Integrated web service for improving alignment quality based on segments comparison', 'Plewczynski, Dariusz|Rychlewski, Leszek|Ye, Yuzhen|Jaroszewski, Lukasz|Godzik, Adam', 'Bioinformatics Laboratory, BioInfoBank Institute, Poznan, Poland. darman@bioinfo.pl|Bioinformatics Laboratory, BioInfoBank Institute, Poznan, Poland. darman@bioinfo.pl|Bioinformatics Laboratory, BioInfoBank Institute, Poznan, Poland. darman@bioinfo.pl|Bioinformatics Laboratory, BioInfoBank Institute, Poznan, Poland. darman@bioinfo.pl|Bioinformatics Laboratory, BioInfoBank Institute, Poznan, Poland. darman@bioinfo.pl', 'Poland|Poland|Poland|Poland|Poland', 11, 'Computational Biology|Databases, Protein|Internet|Online Systems|Peptide Fragments|Predictive Value of Tests|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-5-98', '15271224', 'Defining blocks forming the global protein structure on the basis of local structural regularity is a very fruitful idea, extensively used in description, and prediction of structure from only sequence information. Over many years the secondary structure elements were used as available building blocks with great success. Specially prepared sets of possible structural motifs can be used to describe similarity between very distant, non-homologous proteins. The reason for utilizing the structural information in the description of proteins is straightforward. Structural comparison is able to detect approximately twice as many distant relationships as sequence comparison at the same error rate.'),
(90181, 2004, 'bmc', 'Accuracy of cDNA microarray methods to detect small gene expression changes induced by neuregulin on breast epithelial cells', 'Yao, Bin|Rakhade, Sanjay N|Li, Qunfang|Ahmed, Sharlin|Krauss, Raul|Draghici, Sorin|Loeb, Jeffrey A', 'Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan, USA. binyao@genetics.wayne.edu|Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan, USA. binyao@genetics.wayne.edu|Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan, USA. binyao@genetics.wayne.edu|Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan, USA. binyao@genetics.wayne.edu|Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan, USA. binyao@genetics.wayne.edu|Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan, USA. binyao@genetics.wayne.edu|Center for Molecular Medicine and Genetics, Wayne State University, Detroit, Michigan, USA. binyao@genetics.wayne.edu', 'United States|United States|United States|United States|United States|United States|United States', 42, 'Blotting, Northern|Breast Neoplasms|Cell Division|Cell Line, Tumor|Computational Biology|DNA, Complementary|Epithelial Cells|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Models, Genetic|Neuregulin-1|Oligonucleotide Array Sequence Analysis|RNA, Neoplasm|Recombinant Proteins|Research Design', 'Comparative Study', '10.1186/1471-2105-5-99', '15272935', 'cDNA microarrays are a powerful means to screen for biologically relevant gene expression changes, but are often limited by their ability to detect small changes accurately due to noise from random and systematic errors. While experimental designs and statistical analysis methods have been proposed to reduce these errors, few studies have tested their accuracy and ability to identify small, but biologically important, changes. Here, we have compared two cDNA microarray experimental design methods with northern blot confirmation to reveal changes in gene expression that could contribute to the early antiproliferative effects of neuregulin on MCF10AT human breast epithelial cells.'),
(90182, 2004, 'bmc', 'Graph-based iterative Group Analysis enhances microarray interpretation', 'Breitling, Rainer|Amtmann, Anna|Herzyk, Pawel', 'Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom. r.breitling@bio.gla.ac.uk|Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom. r.breitling@bio.gla.ac.uk|Institute of Biomedical and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom. r.breitling@bio.gla.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 75, 'Algorithms|Computational Biology|Computer Graphics|Gene Expression Profiling|Gene Expression Regulation, Fungal|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae', 'Comparative Study', '10.1186/1471-2105-5-100', '15272936', 'One of the most time-consuming tasks after performing a gene expression experiment is the biological interpretation of the results by identifying physiologically important associations between the differentially expressed genes. A large part of the relevant functional evidence can be represented in the form of graphs, e.g. metabolic and signaling pathways, protein interaction maps, shared GeneOntology annotations, or literature co-citation relations. Such graphs are easily constructed from available genome annotation data. The problem of biological interpretation can then be described as identifying the subgraphs showing the most significant patterns of gene expression. We applied a graph-based extension of our iterative Group Analysis (iGA) approach to obtain a statistically rigorous identification of the subgraphs of interest in any evidence graph.'),
(90183, 2004, 'bmc', 'Structural characterization of genomes by large scale sequence-structure threading: application of reliability analysis in structural genomics', 'Cherkasov, Artem|Ho Sui, Shannan J|Brunham, Robert C|Jones, Steven J M', 'Division of Infectious Diseases, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. artc@interchange.ubc.ca|Division of Infectious Diseases, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. artc@interchange.ubc.ca|Division of Infectious Diseases, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. artc@interchange.ubc.ca|Division of Infectious Diseases, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. artc@interchange.ubc.ca', 'Canada|Canada|Canada|Canada', 8, 'Computational Biology|Databases, Genetic|Genome|Genomics|Likelihood Functions|Models, Statistical|Protein Folding', 'Comparative Study', '10.1186/1471-2105-5-101', '15274750', 'We establish that the occurrence of protein folds among genomes can be accurately described with a Weibull function. Systems which exhibit Weibull character can be interpreted with reliability theory commonly used in engineering analysis. For instance, Weibull distributions are widely used in reliability, maintainability and safety work to model time-to-failure of mechanical devices, mechanisms, building constructions and equipment.'),
(90184, 2004, 'bmc', 'A computer simulation analysis of the accuracy of partial genome sequencing and restriction fragment analysis in estimating genetic relationships: an application to papillomavirus DNA sequences', 'Qiao, Baozhen|Weigel, Ronald M', 'Department of Veterinary Pathobiology, University of Illinois, Urbana, IL 61801 USA. qbaozhen@hotmail.com|Department of Veterinary Pathobiology, University of Illinois, Urbana, IL 61801 USA. qbaozhen@hotmail.com', 'United States|United States', 0, 'Animals|Bovine papillomavirus 1|Computer Simulation|DNA, Viral|Databases, Genetic|Dogs|Genome, Viral|Genotype|Humans|Pan troglodytes|Papillomaviridae|Phylogeny|Restriction Mapping|Sequence Analysis, DNA|Species Specificity', 'Comparative Study', '10.1186/1471-2105-5-102', '15279682', 'Determination of genetic relatedness among microorganisms provides information necessary for making inferences regarding phylogeny. However, there is little information available on how well the genetic relationships inferred from different genotyping methods agree with true genetic relationships. In this report, two genotyping methods - restriction fragment analysis (RFA) and partial genome DNA sequencing - were each compared to complete DNA sequencing as the definitive standard for classification.'),
(90185, 2004, 'bmc', 'Improving the scaling normalization for high-density oligonucleotide GeneChip expression microarrays', 'Lu, Chao', 'Microarray Facility, The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario M5G 1X8, Canada. chao.lu@utoronto.ca', 'Canada', 16, 'Animals|Gene Expression Profiling|Gene Expression Regulation|Genome|Normal Distribution|Oligonucleotide Array Sequence Analysis|Rats', 'Comparative Study', '10.1186/1471-2105-5-103', '15283861', 'Normalization is an important step for microarray data analysis to minimize biological and technical variations. Choosing a suitable approach can be critical. The default method in GeneChip expression microarray uses a constant factor, the scaling factor (SF), for every gene on an array. The SF is obtained from a trimmed average signal of the array after excluding the 2% of the probe sets with the highest and the lowest values.'),
(90186, 2004, 'bmc', 'Design, implementation and evaluation of a practical pseudoknot folding algorithm based on thermodynamics', 'Reeder, Jens|Giegerich, Robert', 'Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany. jreeder@techfak.uni-bielefeld.de|Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany. jreeder@techfak.uni-bielefeld.de', 'Germany|Germany', 221, 'Algorithms|Computational Biology|Hepatitis Delta Virus|Models, Genetic|Nucleic Acid Conformation|Predictive Value of Tests|RNA|RNA, Viral|Thermodynamics', 'Evaluation Studies', '10.1186/1471-2105-5-104', '15294028', 'The general problem of RNA secondary structure prediction under the widely used thermodynamic model is known to be NP-complete when the structures considered include arbitrary pseudoknots. For restricted classes of pseudoknots, several polynomial time algorithms have been designed, where the O(n6)time and O(n4) space algorithm by Rivas and Eddy is currently the best available program.'),
(90187, 2004, 'bmc', 'Estimates of statistical significance for comparison of individual positions in multiple sequence alignments', 'Sadreyev, Ruslan I|Grishin, Nick V', 'Howard Hughes Medical Institute, Department of Biochemistry, University of Texas Southwestern Medical Center, 5323, Harry Hines Blvd, Dallas, TX 75390-9050, USA. sadreyev@chop.swmed.edu|Howard Hughes Medical Institute, Department of Biochemistry, University of Texas Southwestern Medical Center, 5323, Harry Hines Blvd, Dallas, TX 75390-9050, USA. sadreyev@chop.swmed.edu', 'United States|United States', 9, 'Amino Acid Sequence|Amino Acids|Computational Biology|Evolution, Molecular|Models, Genetic|Models, Statistical|Predictive Value of Tests|Proteins|Sequence Alignment|Sequence Homology, Amino Acid', 'Comparative Study', '10.1186/1471-2105-5-106', '15296518', 'Profile-based analysis of multiple sequence alignments (MSA) allows for accurate comparison of protein families. Here, we address the problems of detecting statistically confident dissimilarities between (1) MSA position and a set of predicted residue frequencies, and (2) between two MSA positions. These problems are important for (i) evaluation and optimization of methods predicting residue occurrence at protein positions, (ii) detection of potentially misaligned regions in automatically produced alignments and their further refinement, and (iii) detection of sites that determine functional or structural specificity in two related families.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90188, 2004, 'bmc', 'Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction', 'Doshi, Kishore J|Cannone, Jamie J|Cobaugh, Christian W|Gutell, Robin R', 'The Institute for Cellular and Molecular Biology, The University of Texas at Austin, TX 78712-0159, USA. kjdoshi@mail.utexas.edu|The Institute for Cellular and Molecular Biology, The University of Texas at Austin, TX 78712-0159, USA. kjdoshi@mail.utexas.edu|The Institute for Cellular and Molecular Biology, The University of Texas at Austin, TX 78712-0159, USA. kjdoshi@mail.utexas.edu|The Institute for Cellular and Molecular Biology, The University of Texas at Austin, TX 78712-0159, USA. kjdoshi@mail.utexas.edu', 'United States|United States|United States|United States', 159, 'Base Sequence|Computational Biology|Entropy|Models, Genetic|Nucleic Acid Conformation|Phylogeny|Predictive Value of Tests|RNA|RNA, Archaeal|RNA, Bacterial|RNA, Chloroplast|RNA, Mitochondrial|RNA, Ribosomal, 16S|RNA, Ribosomal, 23S|RNA, Ribosomal, 5S|Thermodynamics', 'Comparative Study', '10.1186/1471-2105-5-105', '15296519', 'A detailed understanding of an RNAs correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNAs secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1.'),
(90189, 2004, 'bmc', 'STING Millennium Suite: integrated software for extensive analyses of 3d structures of proteins and their complexes', 'Higa, Roberto H|Togawa, Roberto C|Montagner, Arnaldo J|Palandrani, Juliana C F|Okimoto, Igor K S|Kuser, Paula R|Yamagishi, Michel E B|Mancini, Adauto L|Neshich, Goran', 'Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil. roberto@cnptia.embrapa.br|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil. roberto@cnptia.embrapa.br|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil. roberto@cnptia.embrapa.br|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil. roberto@cnptia.embrapa.br|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil. roberto@cnptia.embrapa.br|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil. roberto@cnptia.embrapa.br|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil. roberto@cnptia.embrapa.br|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil. roberto@cnptia.embrapa.br|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil. roberto@cnptia.embrapa.br', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 21, 'Algorithms|Computational Biology|Computer Graphics|Protein Structure, Quaternary|Proteins|Software', 'Comparative Study', '10.1186/1471-2105-5-107', '15301693', 'The integration of many aspects of protein/DNA structure analysis is an important requirement for software products in general area of structural bioinformatics. In fact, there are too few software packages on the internet which can be described as successful in this respect. We might say that what is still missing is publicly available, web based software for interactive analysis of the sequence/structure/function of proteins and their complexes with DNA and ligands. Some of existing software packages do have certain level of integration and do offer analysis of several structure related parameters, however not to the extent generally demanded by a user.'),
(90190, 2004, 'bmc', 'Linear fuzzy gene network models obtained from microarray data by exhaustive search', 'Sokhansanj, Bahrad A|Fitch, J Patrick|Quong, Judy N|Quong, Andrew A', 'Computational Systems Biology Group, University of California, Lawrence Livermore National Laboratory, L-235, 7000 East Ave, Livermore, CA 94551, USA. sokhansanj@gmail.com|Computational Systems Biology Group, University of California, Lawrence Livermore National Laboratory, L-235, 7000 East Ave, Livermore, CA 94551, USA. sokhansanj@gmail.com|Computational Systems Biology Group, University of California, Lawrence Livermore National Laboratory, L-235, 7000 East Ave, Livermore, CA 94551, USA. sokhansanj@gmail.com|Computational Systems Biology Group, University of California, Lawrence Livermore National Laboratory, L-235, 7000 East Ave, Livermore, CA 94551, USA. sokhansanj@gmail.com', 'United States|United States|United States|United States', 35, 'Artificial Intelligence|Cell Cycle|Computational Biology|Fuzzy Logic|Linear Models|Models, Genetic|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-5-108', '15304201', 'Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are needed to interpret the resulting large and complex data sets. Rationally designed perturbations (e.g., gene knock-outs) can be used to iteratively refine hypothetical models, suggesting an approach for high-throughput biological system analysis. We introduce an approach to gene network modeling based on a scalable linear variant of fuzzy logic: a framework with greater resolution than Boolean logic models, but which, while still semi-quantitative, does not require the precise parameter measurement needed for chemical kinetics-based modeling.'),
(90191, 2004, 'bmc', 'Tests for finding complex patterns of differential expression in cancers: towards individualized medicine', 'Lyons-Weiler, James|Patel, Satish|Becich, Michael J|Godfrey, Tony E', 'Department of Pathology, Center for Biomedical Informatics, and Interdisciplinary Biomedical Graduate Program, University of Pittsburgh, PA 15232 USA. lyonsweilerj@upmc.edu|Department of Pathology, Center for Biomedical Informatics, and Interdisciplinary Biomedical Graduate Program, University of Pittsburgh, PA 15232 USA. lyonsweilerj@upmc.edu|Department of Pathology, Center for Biomedical Informatics, and Interdisciplinary Biomedical Graduate Program, University of Pittsburgh, PA 15232 USA. lyonsweilerj@upmc.edu|Department of Pathology, Center for Biomedical Informatics, and Interdisciplinary Biomedical Graduate Program, University of Pittsburgh, PA 15232 USA. lyonsweilerj@upmc.edu', 'United States|United States|United States|United States', 36, 'Delivery of Health Care|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Humans|Neoplasms|Patient-Centered Care', 'Comparative Study', '10.1186/1471-2105-5-110', '15307894', 'Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g., comparison of sample means) to identify differentially expressed genes. This leads to the discovery of population-level markers, i.e., genes with the expression patterns A > B and B > A. We introduce the PPST test that identifies genes where a significantly large subset of cases exhibit expression values beyond upper and lower thresholds observed in the control samples.'),
(90192, 2004, 'bmc', 'The Hotdog fold: wrapping up a superfamily of thioesterases and dehydratases', 'Dillon, Shane C|Bateman, Alex', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. scd@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK. scd@sanger.ac.uk', 'United Kingdom|United Kingdom', 124, 'Amino Acid Motifs|Amino Acid Sequence|Arabidopsis Proteins|Archaeal Proteins|Bacterial Proteins|Fungal Proteins|Humans|Hydro-Lyases|Molecular Sequence Data|Peptides|Protein Folding|Protein Structure, Quaternary|Protein Structure, Tertiary|Sequence Alignment|Thiolester Hydrolases', 'Journal Article', '10.1186/1471-2105-5-109', '15307895', 'The Hotdog fold was initially identified in the structure of Escherichia coli FabA and subsequently in 4-hydroxybenzoyl-CoA thioesterase from Pseudomonas sp. strain CBS. Since that time structural determinations have shown a number of other apparently unrelated proteins also share the Hotdog fold.'),
(90193, 2004, 'bmc', 'Alternative mapping of probes to genes for Affymetrix chips', 'Gautier, Laurent|Møller, Morten|Friis-Hansen, Lennart|Knudsen, Steen', 'Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark. laurent@cbs.dtu.dk|Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark. laurent@cbs.dtu.dk|Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark. laurent@cbs.dtu.dk|Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark. laurent@cbs.dtu.dk', 'Denmark|Denmark|Denmark|Denmark', 94, 'Base Sequence|DNA Probes|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Genes|Humans|Oligonucleotide Array Sequence Analysis|Reference Standards|Software', 'Journal Article', '10.1186/1471-2105-5-111', '15310390', 'Short oligonucleotide arrays have several probes measuring the expression level of each target transcript. Therefore the selection of probes is a key component for the quality of measurements. However, once probes have been selected and synthesized on an array, it is still possible to re-evaluate the results using an updated mapping of probes to genes, taking into account the latest biological knowledge available.'),
(90194, 2004, 'bmc', 'IdentiCS--identification of coding sequence and in silico reconstruction of the metabolic network directly from unannotated low-coverage bacterial genome sequence', 'Sun, Jibin|Zeng, An-Ping', 'Department of Genome Analysis, GBF-German Research Center for Biotechnology, Mascheroder Weg 1, Braunschweig, 38124, Germany. jsu@gbf.de|Department of Genome Analysis, GBF-German Research Center for Biotechnology, Mascheroder Weg 1, Braunschweig, 38124, Germany. jsu@gbf.de', 'Germany|Germany', 39, 'Base Sequence|Computational Biology|DNA, Bacterial|Genome, Bacterial|Klebsiella pneumoniae|Open Reading Frames|Salmonella typhimurium', 'Comparative Study', '10.1186/1471-2105-5-112', '15312235', 'A necessary step for a genome level analysis of the cellular metabolism is the in silico reconstruction of the metabolic network from genome sequences. The available methods are mainly based on the annotation of genome sequences including two successive steps, the prediction of coding sequences (CDS) and their function assignment. The annotation process takes time. The available methods often encounter difficulties when dealing with unfinished error-containing genomic sequence.'),
(90195, 2004, 'bmc', 'MUSCLE: a multiple sequence alignment method with reduced time and space complexity', 'Edgar, Robert C', 'Department of Plant and Microbial Biology, 461 Koshland Hall, University of California, Berkeley, CA 94720-3102, USA. bob@drive5.com', 'United States', 4504, 'Cluster Analysis|Computational Biology|Phylogeny|Sequence Alignment|Software|Software Design|Time Factors', 'Comparative Study', '10.1186/1471-2105-5-113', '15318951', 'In a previous paper, we introduced MUSCLE, a new program for creating multiple alignments of protein sequences, giving a brief summary of the algorithm and showing MUSCLE to achieve the highest scores reported to date on four alignment accuracy benchmarks. Here we present a more complete discussion of the algorithm, describing several previously unpublished techniques that improve biological accuracy and / or computational complexity. We introduce a new option, MUSCLE-fast, designed for high-throughput applications. We also describe a new protocol for evaluating objective functions that align two profiles.'),
(90196, 2004, 'bmc', 'Influence of microarrays experiments missing values on the stability of gene groups by hierarchical clustering', 'de Brevern, Alexandre G|Hazout, Serge|Malpertuy, Alain', 'Equipe de Bioinformatique Génomique et Moléculaire (EBGM), INSERM E0346, Université Denis DIDEROT-Paris 7, case 7113, 2, place Jussieu, 75251 Paris, France. alexandre.debrevern@ebgm.jussieu.fr|Equipe de Bioinformatique Génomique et Moléculaire (EBGM), INSERM E0346, Université Denis DIDEROT-Paris 7, case 7113, 2, place Jussieu, 75251 Paris, France. alexandre.debrevern@ebgm.jussieu.fr|Equipe de Bioinformatique Génomique et Moléculaire (EBGM), INSERM E0346, Université Denis DIDEROT-Paris 7, case 7113, 2, place Jussieu, 75251 Paris, France. alexandre.debrevern@ebgm.jussieu.fr', 'France|France|France', 69, 'Cluster Analysis|Computational Biology|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Fungal|Genes, Fungal|Oligonucleotide Array Sequence Analysis|Reference Values|Research Design|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-5-114', '15324460', 'Microarray technologies produced large amount of data. The hierarchical clustering is commonly used to identify clusters of co-expressed genes. However, microarray datasets often contain missing values (MVs) representing a major drawback for the use of the clustering methods. Usually the MVs are not treated, or replaced by zero or estimated by the k-Nearest Neighbor (kNN) approach. The topic of the paper is to study the stability of gene clusters, defined by various hierarchical clustering algorithms, of microarrays experiments including or not MVs.'),
(90197, 2004, 'bmc', 'An imaging system for standardized quantitative analysis of C elegans behavior', 'Feng, Zhaoyang|Cronin, Christopher J|Wittig, John H|Sternberg, Paul W|Schafer, William R', 'Division of Biological Sciences, University of California, San Diego, CA USA. zhaoyang@UCSD.Edu|Division of Biological Sciences, University of California, San Diego, CA USA. zhaoyang@UCSD.Edu|Division of Biological Sciences, University of California, San Diego, CA USA. zhaoyang@UCSD.Edu|Division of Biological Sciences, University of California, San Diego, CA USA. zhaoyang@UCSD.Edu|Division of Biological Sciences, University of California, San Diego, CA USA. zhaoyang@UCSD.Edu', 'United States|United States|United States|United States|United States', 0, 'Animals|Behavior, Animal|Caenorhabditis elegans|Microscopy, Video|Motor Activity|Multimedia|Mutation|Phenotype|Software', 'Journal Article', '10.1186/1471-2105-5-115', '15331023', 'The nematode Caenorhabditis elegans is widely used for the genetic analysis of neuronal cell biology, development, and behavior. Because traditional methods for evaluating behavioral phenotypes are qualitative and imprecise, there is a need for tools that allow quantitation and standardization of C. elegans behavioral assays.'),
(90198, 2004, 'bmc', 'XHM: a system for detection of potential cross hybridizations in DNA microarrays', 'Flikka, Kristian|Yadetie, Fekadu|Laegreid, Astrid|Jonassen, Inge', 'Computational Biology Unit, Bergen Center for Computational Science, UNIFOB/UiB, Thormoehlensgt,55, N-5008 Bergen, Norway. flikka@ii.uib.no|Computational Biology Unit, Bergen Center for Computational Science, UNIFOB/UiB, Thormoehlensgt,55, N-5008 Bergen, Norway. flikka@ii.uib.no|Computational Biology Unit, Bergen Center for Computational Science, UNIFOB/UiB, Thormoehlensgt,55, N-5008 Bergen, Norway. flikka@ii.uib.no|Computational Biology Unit, Bergen Center for Computational Science, UNIFOB/UiB, Thormoehlensgt,55, N-5008 Bergen, Norway. flikka@ii.uib.no', 'Norway|Norway|Norway|Norway', 0, 'Animals|Computational Biology|DNA Probes|DNA, Complementary|Databases, Genetic|Gene Expression Profiling|Humans|Internet|Mice|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Rats|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-5-117', '15333145', 'Microarrays have emerged as the preferred platform for high throughput gene expression analysis. Cross-hybridization among genes with high sequence similarities can be a source of error reducing the reliability of DNA microarray results.'),
(90199, 2004, 'bmc', 'Applying Support Vector Machines for Gene Ontology based gene function prediction', 'Vinayagam, Arunachalam|König, Rainer|Moormann, Jutta|Schubert, Falk|Eils, Roland|Glatting, Karl-Heinz|Suhai, Sándor', 'Department of Molecular Biophysics, Deutsches Krebsforschungszentrum (DKFZ), TP3, Im Neuenheimer Feld 580, Heidelberg, D-69120, Germany. A.Vinayagam@dkfz-heidelberg.de|Department of Molecular Biophysics, Deutsches Krebsforschungszentrum (DKFZ), TP3, Im Neuenheimer Feld 580, Heidelberg, D-69120, Germany. A.Vinayagam@dkfz-heidelberg.de|Department of Molecular Biophysics, Deutsches Krebsforschungszentrum (DKFZ), TP3, Im Neuenheimer Feld 580, Heidelberg, D-69120, Germany. A.Vinayagam@dkfz-heidelberg.de|Department of Molecular Biophysics, Deutsches Krebsforschungszentrum (DKFZ), TP3, Im Neuenheimer Feld 580, Heidelberg, D-69120, Germany. A.Vinayagam@dkfz-heidelberg.de|Department of Molecular Biophysics, Deutsches Krebsforschungszentrum (DKFZ), TP3, Im Neuenheimer Feld 580, Heidelberg, D-69120, Germany. A.Vinayagam@dkfz-heidelberg.de|Department of Molecular Biophysics, Deutsches Krebsforschungszentrum (DKFZ), TP3, Im Neuenheimer Feld 580, Heidelberg, D-69120, Germany. A.Vinayagam@dkfz-heidelberg.de|Department of Molecular Biophysics, Deutsches Krebsforschungszentrum (DKFZ), TP3, Im Neuenheimer Feld 580, Heidelberg, D-69120, Germany. A.Vinayagam@dkfz-heidelberg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Animals|Artificial Intelligence|Computational Biology|Databases, Genetic|Genes|Genes, Bacterial|Genes, Fungal|Genes, Helminth|Genes, Insect|Genes, Plant|Genes, Protozoan|Mice|Neural Networks (Computer)|Predictive Value of Tests|Rats|Xenopus laevis', 'Comparative Study', '10.1186/1471-2105-5-116', '15333146', 'The current progress in sequencing projects calls for rapid, reliable and accurate function assignments of gene products. A variety of methods has been designed to annotate sequences on a large scale. However, these methods can either only be applied for specific subsets, or their results are not formalised, or they do not provide precise confidence estimates for their predictions.'),
(90200, 2004, 'bmc', 'Artificial neural network approach for selection of susceptible single nucleotide polymorphisms and construction of prediction model on childhood allergic asthma', 'Tomita, Yasuyuki|Tomida, Shuta|Hasegawa, Yuko|Suzuki, Yoichi|Shirakawa, Taro|Kobayashi, Takeshi|Honda, Hiroyuki', 'Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. h031411m@mbox.nagoya-u.ac.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. h031411m@mbox.nagoya-u.ac.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. h031411m@mbox.nagoya-u.ac.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. h031411m@mbox.nagoya-u.ac.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. h031411m@mbox.nagoya-u.ac.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. h031411m@mbox.nagoya-u.ac.jp|Department of Biotechnology, School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan. h031411m@mbox.nagoya-u.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 53, 'Alleles|Artificial Intelligence|Asian Continental Ancestry Group|Asthma|Child|Child, Preschool|Genes|Genetic Predisposition to Disease|Genotype|Humans|Infant|Infant, Newborn|Japan|Models, Genetic|Neural Networks (Computer)|Polymorphism, Single Nucleotide|Predictive Value of Tests|Selection, Genetic', 'Journal Article', '10.1186/1471-2105-5-120', '15339344', 'Screening of various gene markers such as single nucleotide polymorphism (SNP) and correlation between these markers and development of multifactorial disease have previously been studied. Here, we propose a susceptible marker-selectable artificial neural network (ANN) for predicting development of allergic disease.'),
(90201, 2004, 'bmc', 'Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)', 'Vêncio, Ricardo Z N|Brentani, Helena|Patrão, Diogo F C|Pereira, Carlos A B', 'Statistics Department, Instituto de Matemática e Estatística - Universidade de São Paulo, Rua do Matão 1010, 05508-090 São Paulo, Brazil. rvencio@vision.ime.usp.br|Statistics Department, Instituto de Matemática e Estatística - Universidade de São Paulo, Rua do Matão 1010, 05508-090 São Paulo, Brazil. rvencio@vision.ime.usp.br|Statistics Department, Instituto de Matemática e Estatística - Universidade de São Paulo, Rua do Matão 1010, 05508-090 São Paulo, Brazil. rvencio@vision.ime.usp.br|Statistics Department, Instituto de Matemática e Estatística - Universidade de São Paulo, Rua do Matão 1010, 05508-090 São Paulo, Brazil. rvencio@vision.ime.usp.br', 'Brazil|Brazil|Brazil|Brazil', 0, 'Astrocytoma|Bayes Theorem|Brain Chemistry|Brain Neoplasms|Computational Biology|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Variation|Humans|Models, Genetic|Oligonucleotide Array Sequence Analysis|Research Design', 'Comparative Study', '10.1186/1471-2105-5-119', '15339345', 'An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), Digital Northern or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error.'),
(90202, 2004, 'bmc', 'Estimating mutual information using B-spline functions--an improved similarity measure for analysing gene expression data', 'Daub, Carsten O|Steuer, Ralf|Selbig, Joachim|Kloska, Sebastian', 'Max Planck Institute of Molecular Plant Physiology, Potsdam, 14424, Germany. carsten.daub@cgb.ki.se|Max Planck Institute of Molecular Plant Physiology, Potsdam, 14424, Germany. carsten.daub@cgb.ki.se|Max Planck Institute of Molecular Plant Physiology, Potsdam, 14424, Germany. carsten.daub@cgb.ki.se|Max Planck Institute of Molecular Plant Physiology, Potsdam, 14424, Germany. carsten.daub@cgb.ki.se', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Computational Biology|Fuzzy Logic|Gene Expression Profiling|Information Science|Models, Theoretical|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1186/1471-2105-5-118', '15339346', 'The information theoretic concept of mutual information provides a general framework to evaluate dependencies between variables. In the context of the clustering of genes with similar patterns of expression it has been suggested as a general quantity of similarity to extend commonly used linear measures. Since mutual information is defined in terms of discrete variables, its application to continuous data requires the use of binning procedures, which can lead to significant numerical errors for datasets of small or moderate size.'),
(90203, 2004, 'bmc', 'Automatic annotation of protein motif function with Gene Ontology terms', 'Lu, Xinghua|Zhai, Chengxiang|Gopalakrishnan, Vanathi|Buchanan, Bruce G', 'Dept. of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, 135 Cannon St, Suite 303, Charleston, SC 29425, USA. lux@musc.edu|Dept. of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, 135 Cannon St, Suite 303, Charleston, SC 29425, USA. lux@musc.edu|Dept. of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, 135 Cannon St, Suite 303, Charleston, SC 29425, USA. lux@musc.edu|Dept. of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, 135 Cannon St, Suite 303, Charleston, SC 29425, USA. lux@musc.edu', 'United States|United States|United States|United States', 25, 'Amino Acid Motifs|Computational Biology|Conserved Sequence|Databases, Protein|Genes|Logistic Models|Predictive Value of Tests|Proteins|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-5-122', '15345032', 'Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, a much needed and important task is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO) project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base.'),
(90204, 2004, 'bmc', 'SED, a normalization free method for DNA microarray data analysis', 'Wang, Huajun|Huang, Hui', 'Oscient Pharmaceuticals Corporation, 100 Beaver St, Waltham, Massachusetts 02453, USA. hw14@columbia.edu|Oscient Pharmaceuticals Corporation, 100 Beaver St, Waltham, Massachusetts 02453, USA. hw14@columbia.edu', 'United States|United States', 2, 'Central Nervous System Neoplasms|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, Neoplasm|Humans|Leukemia|Lymphoma|Male|Neoplasms|Normal Distribution|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Prostatic Neoplasms', 'Journal Article', '10.1186/1471-2105-5-121', '15345033', 'Analysis of DNA microarray data usually begins with a normalization step where intensities of different arrays are adjusted to the same scale so that the intensity levels from different arrays can be compared with one other. Both simple total array intensity-based as well as more complex local intensity level dependent normalization methods have been developed, some of which are widely used. Much less developed methods for microarray data analysis include those that bypass the normalization step and therefore yield results that are not confounded by potential normalization errors.'),
(90205, 2004, 'bmc', 'Determination of the differentially expressed genes in microarray experiments using local FDR', 'Aubert, J|Bar-Hen, A|Daudin, J J|Robin, S', 'UMR INAPG/INRA/ENGREF 518, 16, rue C, Bernard, 75231 Paris, France. aubert@inapg.fr|UMR INAPG/INRA/ENGREF 518, 16, rue C, Bernard, 75231 Paris, France. aubert@inapg.fr|UMR INAPG/INRA/ENGREF 518, 16, rue C, Bernard, 75231 Paris, France. aubert@inapg.fr|UMR INAPG/INRA/ENGREF 518, 16, rue C, Bernard, 75231 Paris, France. aubert@inapg.fr', 'France|France|France|France', 58, 'Acute Disease|Animals|Apolipoprotein A-I|Breast Neoplasms|Cholesterol, HDL|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Neoplastic|Humans|Leukemia, Myeloid|Mice|Mice, Knockout|Oligonucleotide Array Sequence Analysis|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Research Design', 'Journal Article', '10.1186/1471-2105-5-125', '15350197', 'Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR), has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5%) is arbitrary and a specific measure associated with each gene would be worthwhile.'),
(90206, 2004, 'bmc', 'Handling multiple testing while interpreting microarrays with the Gene Ontology Database', 'Osier, Michael V|Zhao, Hongyu|Cheung, Kei-Hoi', 'Department of Biological Sciences, Rochester Institute of Technology, 85 Lomb Memorial Drive, Rochester, NY 14623, USA. michael@bioinformatics.rit.edu|Department of Biological Sciences, Rochester Institute of Technology, 85 Lomb Memorial Drive, Rochester, NY 14623, USA. michael@bioinformatics.rit.edu|Department of Biological Sciences, Rochester Institute of Technology, 85 Lomb Memorial Drive, Rochester, NY 14623, USA. michael@bioinformatics.rit.edu', 'United States|United States|United States', 26, 'Animals|Computational Biology|Data Interpretation, Statistical|Databases, Genetic|Drosophila|Gene Expression Profiling|Helminths|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1186/1471-2105-5-124', '15350198', 'The development of software tools that analyze microarray data in the context of genetic knowledgebases is being pursued by multiple research groups using different methods. A common problem for many of these tools is how to correct for multiple statistical testing since simple corrections are overly conservative and more sophisticated corrections are currently impractical. A careful study of the nature of the distribution one would expect by chance, such as by a simulation study, may be able to guide the development of an appropriate correction that is not overly time consuming computationally.'),
(90207, 2004, 'bmc', 'GASP: Gapped Ancestral Sequence Prediction for proteins', 'Edwards, Richard J|Shields, Denis C', 'Bioinformatics Core, Clinical Pharmacology, Royal College of Surgeons in Ireland, 123 St Stephens Green, Dublin 2, Ireland. redwards@rcsi.ie|Bioinformatics Core, Clinical Pharmacology, Royal College of Surgeons in Ireland, 123 St Stephens Green, Dublin 2, Ireland. redwards@rcsi.ie', 'Ireland|Ireland', 31, 'Amino Acid Sequence|Animals|Avian Proteins|Cattle|Chickens|Computer Simulation|DNA|Evolution, Molecular|Humans|Mice|Molecular Sequence Data|Predictive Value of Tests|Proteins|Rats|Software', 'Journal Article', '10.1186/1471-2105-5-123', '15350199', 'The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments.'),
(90208, 2004, 'bmc', 'Iterative class discovery and feature selection using Minimal Spanning Trees', 'Varma, Sudhir|Simon, Richard', 'Biometric Research Branch, National Cancer Institute, Rockville, USA. varmas@mail.nih.gov|Biometric Research Branch, National Cancer Institute, Rockville, USA. varmas@mail.nih.gov', 'United States|United States', 27, 'Acute Disease|Algorithms|Breast Neoplasms|Cluster Analysis|Computational Biology|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genes, BRCA2|Humans|Leukemia, Myeloid|Lymphoma, B-Cell|Lymphoma, Large B-Cell, Diffuse|Mutation|Oligonucleotide Array Sequence Analysis|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Principal Component Analysis', 'Journal Article', '10.1186/1471-2105-5-126', '15355552', 'Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples are based on distance metrics utilizing all genes. This has the effect of obscuring clustering in samples that may be evident only when looking at a subset of genes, because noise from irrelevant genes dominates the signal from the relevant genes in the distance calculation.'),
(90209, 2004, 'bmc', 'GDR (Genome Database for Rosaceae): integrated web resources for Rosaceae genomics and genetics research', 'Jung, Sook|Jesudurai, Christopher|Staton, Margaret|Du, Zhidian|Ficklin, Stephen|Cho, Ilhyung|Abbott, Albert|Tomkins, Jeffrey|Main, Dorrie', 'Department of Genetics and Biochemistry, Clemson University, Clemson, SC, 29634, USA. sook@genome.clemson.edu|Department of Genetics and Biochemistry, Clemson University, Clemson, SC, 29634, USA. sook@genome.clemson.edu|Department of Genetics and Biochemistry, Clemson University, Clemson, SC, 29634, USA. sook@genome.clemson.edu|Department of Genetics and Biochemistry, Clemson University, Clemson, SC, 29634, USA. sook@genome.clemson.edu|Department of Genetics and Biochemistry, Clemson University, Clemson, SC, 29634, USA. sook@genome.clemson.edu|Department of Genetics and Biochemistry, Clemson University, Clemson, SC, 29634, USA. sook@genome.clemson.edu|Department of Genetics and Biochemistry, Clemson University, Clemson, SC, 29634, USA. sook@genome.clemson.edu|Department of Genetics and Biochemistry, Clemson University, Clemson, SC, 29634, USA. sook@genome.clemson.edu|Department of Genetics and Biochemistry, Clemson University, Clemson, SC, 29634, USA. sook@genome.clemson.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 72, 'Computer Graphics|Databases, Genetic|Genetics|Genome, Plant|Genomics|Internet|Research|Rosaceae|Sequence Alignment|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-5-130', '15357877', 'Peach is being developed as a model organism for Rosaceae, an economically important family that includes fruits and ornamental plants such as apple, pear, strawberry, cherry, almond and rose. The genomics and genetics data of peach can play a significant role in the gene discovery and the genetic understanding of related species. The effective utilization of these peach resources, however, requires the development of an integrated and centralized database with associated analysis tools.'),
(90210, 2004, 'bmc', 'Cross-species comparison significantly improves genome-wide prediction of cis-regulatory modules in Drosophila', 'Sinha, Saurabh|Schroeder, Mark D|Unnerstall, Ulrich|Gaul, Ulrike|Siggia, Eric D', 'Center for Studies in Physics and Biology, Rockefeller University, 1230 York Ave, New York, NY10021, USA. saurabh@lonnrot.rockefeller.edu.|Center for Studies in Physics and Biology, Rockefeller University, 1230 York Ave, New York, NY10021, USA. saurabh@lonnrot.rockefeller.edu.|Center for Studies in Physics and Biology, Rockefeller University, 1230 York Ave, New York, NY10021, USA. saurabh@lonnrot.rockefeller.edu.|Center for Studies in Physics and Biology, Rockefeller University, 1230 York Ave, New York, NY10021, USA. saurabh@lonnrot.rockefeller.edu.|Center for Studies in Physics and Biology, Rockefeller University, 1230 York Ave, New York, NY10021, USA. saurabh@lonnrot.rockefeller.edu.', 'United States|United States|United States|United States|United States', 77, 'Algorithms|Animals|Conserved Sequence|Drosophila|Drosophila melanogaster|Evolution, Molecular|Gene Expression Regulation|Genes, Insect|Genome|Predictive Value of Tests|Species Specificity|Transcription, Genetic', 'Comparative Study', '10.1186/1471-2105-5-129', '15357878', 'The discovery of cis-regulatory modules in metazoan genomes is crucial for understanding the connection between genes and organism diversity. It is important to quantify how comparative genomics can improve computational detection of such modules.'),
(90211, 2004, 'bmc', 'DIALIGN P: fast pair-wise and multiple sequence alignment using parallel processors', 'Schmollinger, Martin|Nieselt, Kay|Kaufmann, Michael|Morgenstern, Burkhard', 'Wilhelm-Schickard-Institut fur Informatik, Sand 14, 72076 Tübingen, Germany. Martin.Schmollinger@fh-furtwangen.de|Wilhelm-Schickard-Institut fur Informatik, Sand 14, 72076 Tübingen, Germany. Martin.Schmollinger@fh-furtwangen.de|Wilhelm-Schickard-Institut fur Informatik, Sand 14, 72076 Tübingen, Germany. Martin.Schmollinger@fh-furtwangen.de|Wilhelm-Schickard-Institut fur Informatik, Sand 14, 72076 Tübingen, Germany. Martin.Schmollinger@fh-furtwangen.de', 'Germany|Germany|Germany|Germany', 31, 'Computational Biology|Genome|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-5-128', '15357879', 'Parallel computing is frequently used to speed up computationally expensive tasks in Bioinformatics.'),
(90212, 2004, 'bmc', 'Functionally specified protein signatures distinctive for each of the different blue copper proteins', 'Giri, Anuradha Vivekanandan|Anishetty, Sharmila|Gautam, Pennathur', 'Centre for Biotechnology, Anna University, Chennai 600 025, India. anuvivek15@yahoo.com|Centre for Biotechnology, Anna University, Chennai 600 025, India. anuvivek15@yahoo.com|Centre for Biotechnology, Anna University, Chennai 600 025, India. anuvivek15@yahoo.com', 'India|India|India', 17, 'Amino Acid Sequence|Azurin|Bacterial Proteins|Carrier Proteins|Copper|Databases, Protein|Metalloproteins|Molecular Sequence Data|Peptide Mapping|Plant Proteins|Plastocyanin', 'Journal Article', '10.1186/1471-2105-5-127', '15357880', 'Proteins having similar functions from different sources can be identified by the occurrence in their sequences, a conserved cluster of amino acids referred to as pattern, motif, signature or fingerprint. The wide usage of protein sequence analysis in par with the growth of databases signifies the importance of using patterns or signatures to retrieve out related sequences. Blue copper proteins are found in the electron transport chain of prokaryotes and eukaryotes. The signatures already existing in the databases like the type 1 copper blue, multiple copper oxidase, cyt b/b6, photosystem 1 psaA&B, psaG&K, and reiske iron sulphur protein are not specified signatures for blue copper proteins as the name itself suggests. Most profile and motif databases strive to classify protein sequences into a broad spectrum of protein families. This work describes the signatures designed based on the copper metal binding motifs in blue copper proteins. The common feature in all blue copper proteins is a trigonal planar arrangement of two nitrogen ligands [each from histidine] and one sulphur containing thiolate ligand [from cysteine], with strong interactions between the copper center and these ligands.'),
(90213, 2004, 'bmc', 'What can we learn from noncoding regions of similarity between genomes?', 'Down, Thomas A|Hubbard, Tim J P', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. td2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. td2@sanger.ac.uk', 'United Kingdom|United Kingdom', 6, 'Animals|Artificial Intelligence|Base Composition|Chromosomes, Human, Pair 6|Computational Biology|CpG Islands|DNA, Intergenic|Genome|Genome, Human|Humans|Mice|Models, Genetic|Predictive Value of Tests|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-5-131', '15369604', 'In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to assume that these conserved regions are more likely to contain functional elements than less-conserved portions of the genome.'),
(90214, 2004, 'bmc', 'Allermatch, a webtool for the prediction of potential allergenicity according to current FAO/WHO Codex alimentarius guidelines', 'Fiers, Mark W E J|Kleter, Gijs A|Nijland, Herman|Peijnenburg, Ad A C M|Nap, Jan Peter|van Ham, Roeland C H J', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. td2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. td2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. td2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. td2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. td2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK. td2@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 89, 'Allergens|Amino Acid Sequence|Databases, Factual|Databases, Protein|Guidelines as Topic|Humans|Internet|Plant Proteins|Predictive Value of Tests|Sequence Alignment|United Nations|World Health Organization', 'Journal Article', '10.1186/1471-2105-5-133', '15373946', 'Novel proteins entering the food chain, for example by genetic modification of plants, have to be tested for allergenicity. Allermatch http://allermatch.org is a webtool for the efficient and standardized prediction of potential allergenicity of proteins and peptides according to the current recommendations of the FAO/WHO Expert Consultation, as outlined in the Codex alimentarius.'),
(90215, 2004, 'bmc', 'Simple statistical models predict C-to-U edited sites in plant mitochondrial RNA', 'Cummings, Michael P|Myers, Daniel S', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742-3360, USA. mike@umiacs.umd.edu.|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742-3360, USA. mike@umiacs.umd.edu.', 'United States|United States', 36, 'Arabidopsis|Brassica napus|Cytidine|Models, Genetic|Models, Statistical|Oryza|Plants|Predictive Value of Tests|RNA|RNA Editing|RNA, Messenger|RNA, Mitochondrial|Reproducibility of Results|Sensitivity and Specificity|Uridine', 'Journal Article', '10.1186/1471-2105-5-132', '15373947', 'RNA editing is the process whereby an RNA sequence is modified from the sequence of the corresponding DNA template. In the mitochondria of land plants, some cytidines are converted to uridines before translation. Despite substantial study, the molecular biological mechanism by which C-to-U RNA editing proceeds remains relatively obscure, although several experimental studies have implicated a role for cis-recognition. A highly non-random distribution of nucleotides is observed in the immediate vicinity of edited sites (within 20 nucleotides 5 and 3), but no precise consensus motif has been identified.'),
(90216, 2004, 'bmc', 'PATTERNFINDER: combined analysis of DNA regulatory sequences and double-helix stability', 'Huang, Yanlin|Kowalski, David', 'Cancer Genetics Department, Roswell Park Cancer Institute, Buffalo, NY 14263, USA. yanlinh@microsoft.com|Cancer Genetics Department, Roswell Park Cancer Institute, Buffalo, NY 14263, USA. yanlinh@microsoft.com', 'United States|United States', 3, 'Computational Biology|DNA|Genes, myc|Humans|Internet|Regulatory Sequences, Nucleic Acid|Sequence Analysis, DNA|Software|Thermodynamics|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-5-134', '15383143', 'Regulatory regions that function in DNA replication and gene transcription contain specific sequences that bind proteins as well as less-specific sequences in which the double helix is often easy to unwind. Progress towards predicting and characterizing regulatory regions could be accelerated by computer programs that perform a combined analysis of specific sequences and DNA unwinding properties.'),
(90217, 2004, 'bmc', 'Profiled support vector machines for antisense oligonucleotide efficacy prediction', 'Camps-Valls, Gustavo|Chalk, Alistair M|Serrano-López, Antonio J|Martín-Guerrero, José D|Sonnhammer, Erik L L', 'Grup de Processament Digital de Senyals, Universitat de València, Spain, C/ Dr, Moliner, 50, 46100 Burjassot, València, Spain. gustavo.camps@uv.es|Grup de Processament Digital de Senyals, Universitat de València, Spain, C/ Dr, Moliner, 50, 46100 Burjassot, València, Spain. gustavo.camps@uv.es|Grup de Processament Digital de Senyals, Universitat de València, Spain, C/ Dr, Moliner, 50, 46100 Burjassot, València, Spain. gustavo.camps@uv.es|Grup de Processament Digital de Senyals, Universitat de València, Spain, C/ Dr, Moliner, 50, 46100 Burjassot, València, Spain. gustavo.camps@uv.es|Grup de Processament Digital de Senyals, Universitat de València, Spain, C/ Dr, Moliner, 50, 46100 Burjassot, València, Spain. gustavo.camps@uv.es', 'Spain|Spain|Spain|Spain|Spain', 25, 'Databases, Genetic|Gene Expression|Models, Genetic|Oligonucleotides, Antisense|Predictive Value of Tests|Proteins|RNA|Software|Software Validation', 'Comparative Study', '10.1186/1471-2105-5-135', '15383156', 'This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality. We propose a two-stage strategy to develop an optimal model: (1) feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE), and (2) AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to different parts of the training data to focus the training on the most important regions.'),
(90218, 2004, 'bmc', 'A combinational feature selection and ensemble neural network method for classification of gene expression data', 'Liu, Bing|Cui, Qinghua|Jiang, Tianzi|Ma, Songde', 'National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, P. R. China. bliu@nlpr.ia.ac.cn|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, P. R. China. bliu@nlpr.ia.ac.cn|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, P. R. China. bliu@nlpr.ia.ac.cn|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, P. R. China. bliu@nlpr.ia.ac.cn', 'China|China|China|China', 114, 'Acute Disease|Artificial Intelligence|Colonic Neoplasms|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Leukemia, Myeloid|Lung Neoplasms|Lymphoma, B-Cell|Lymphoma, Large B-Cell, Diffuse|Male|Neural Networks (Computer)|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Predictive Value of Tests|Prostatic Neoplasms', 'Comparative Study', '10.1186/1471-2105-5-136', '15450124', 'Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for a particular disease. To date, this problem has received most attention in the context of cancer research, especially in tumor classification. Various feature selection methods and classifier design strategies also have been generally used and compared. However, most published articles on tumor classification have applied a certain technique to a certain dataset, and recently several researchers compared these techniques based on several public datasets. But, it has been verified that differently selected features reflect different aspects of the dataset and some selected features can obtain better solutions on some certain problems. At the same time, faced with a large amount of microarray data with little knowledge, it is difficult to find the intrinsic characteristics using traditional methods. In this paper, we attempt to introduce a combinational feature selection method in conjunction with ensemble neural networks to generally improve the accuracy and robustness of sample classification.'),
(90219, 2004, 'bmc', 'A population-based statistical approach identifies parameters characteristic of human microRNA-mRNA interactions', 'Smalheiser, Neil R|Torvik, Vetle I', 'University of Illinois at Chicago, UIC Psychiatric Institute, MC 912, 1601 W, Taylor Street, room 285 Chicago, IL 60612, USA. smalheiser@psych.uic.edu|University of Illinois at Chicago, UIC Psychiatric Institute, MC 912, 1601 W, Taylor Street, room 285 Chicago, IL 60612, USA. smalheiser@psych.uic.edu', 'United States|United States', 0, 'Computational Biology|Genetics, Population|Humans|MicroRNAs|RNA, Messenger', 'Comparative Study', '10.1186/1471-2105-5-139', '15453917', 'MicroRNAs are approximately 17-24 nt. noncoding RNAs found in all eukaryotes that degrade messenger RNAs via RNA interference (if they bind in a perfect or near-perfect complementarity to the target mRNA), or arrest translation (if the binding is imperfect). Several microRNA targets have been identified in lower organisms, but only one mammalian microRNA target has yet been validated experimentally.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(90220, 2004, 'bmc', 'cuticleDB: a relational database of Arthropod cuticular proteins', 'Magkrioti, Christiana K|Spyropoulos, Ioannis C|Iconomidou, Vassiliki A|Willis, Judith H|Hamodrakas, Stavros J', 'Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Athens 15701, Greece. chmagkrioti@yahoo.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Athens 15701, Greece. chmagkrioti@yahoo.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Athens 15701, Greece. chmagkrioti@yahoo.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Athens 15701, Greece. chmagkrioti@yahoo.gr|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Athens 15701, Greece. chmagkrioti@yahoo.gr', 'Greece|Greece|Greece|Greece|Greece', 47, 'Amino Acid Motifs|Animals|Anopheles|Arthropods|Classification|Databases, Protein|Drosophila Proteins|Drosophila melanogaster|Information Storage and Retrieval|Insect Proteins|Internet', 'Journal Article', '10.1186/1471-2105-5-138', '15453918', 'The insect exoskeleton or cuticle is a bi-partite composite of proteins and chitin that provides protective, skeletal and structural functions. Little information is available about the molecular structure of this important complex that exhibits a helicoidal architecture. Scores of sequences of cuticular proteins have been obtained from direct protein sequencing, from cDNAs, and from genomic analyses. Most of these cuticular protein sequences contain motifs found only in arthropod proteins.'),
(90221, 2004, 'bmc', 'Few amino acid positions in rpoB are associated with most of the rifampin resistance in Mycobacterium tuberculosis', 'Cummings, Michael P|Segal, Mark R', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742-3360, USA. mike@umiacs.umd.edu.|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742-3360, USA. mike@umiacs.umd.edu.', 'United States|United States', 0, 'Amino Acids|Bacterial Proteins|Classification|DNA-Directed RNA Polymerases|Drug Resistance, Microbial|Genotype|Models, Biological|Models, Statistical|Mycobacterium tuberculosis|Phenotype|Predictive Value of Tests|Regression Analysis|Rifampin', 'Journal Article', '10.1186/1471-2105-5-137', '15453919', 'Mutations in rpoB, the gene encoding the beta subunit of DNA-dependent RNA polymerase, are associated with rifampin resistance in Mycobacterium tuberculosis. Several studies have been conducted where minimum inhibitory concentration (MIC, which is defined as the minimum concentration of the antibiotic in a given culture medium below which bacterial growth is not inhibited) of rifampin has been measured and partial DNA sequences have been determined for rpoB in different isolates of M. tuberculosis. However, no model has been constructed to predict rifampin resistance based on sequence information alone. Such a model might provide the basis for quantifying rifampin resistance status based exclusively on DNA sequence data and thus eliminate the requirements for time consuming culturing and antibiotic testing of clinical isolates.'),
(90222, 2004, 'bmc', 'GeneXplorer: an interactive web application for microarray data visualization and analysis', 'Rees, Christian A|Demeter, Janos|Matese, John C|Botstein, David|Sherlock, Gavin', 'Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. rees@genome.stanford.edu <rees@genome.stanford.edu>|Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. rees@genome.stanford.edu <rees@genome.stanford.edu>|Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. rees@genome.stanford.edu <rees@genome.stanford.edu>|Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. rees@genome.stanford.edu <rees@genome.stanford.edu>|Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. rees@genome.stanford.edu <rees@genome.stanford.edu>', 'United States|United States|United States|United States|United States', 0, 'Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Internet|Oligonucleotide Array Sequence Analysis|Software|Software Design', 'Journal Article', '10.1186/1471-2105-5-141', '15458579', 'When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data.'),
(90223, 2004, 'bmc', 'A comprehensive comparison of comparative RNA structure prediction approaches', 'Gardner, Paul P|Giegerich, Robert', 'Department of Evolutionary Biology, University of Copenhagen, Universitetsparken 15, 2100 Copenhagen Ø, Denmark. PPGardner@bi.ku.dk|Department of Evolutionary Biology, University of Copenhagen, Universitetsparken 15, 2100 Copenhagen Ø, Denmark. PPGardner@bi.ku.dk', 'Denmark|Denmark', 253, 'Algorithms|Benchmarking|Consensus Sequence|Escherichia coli K12|Nucleic Acid Conformation|Predictive Value of Tests|RNA|RNA, Bacterial|RNA, Fungal|Saccharomyces cerevisiae|Sequence Alignment|Software|Software Design', 'Comparative Study', '10.1186/1471-2105-5-140', '15458580', 'An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, independent benchmarking of these algorithms is rarely performed as is now common practice for protein-folding, gene-finding and multiple-sequence-alignment algorithms.'),
(90224, 2004, 'bmc', 'ArrayD: a general purpose software for microarray design', 'Sharma, Anu|Srivastava, Gyan Prakash|Sharma, Vineet K|Ramachandran, Srinivasan', 'Institute of Genomics and Integrative Biology (CSIR), Mall Road, Delhi 110 007, India. anusha77in@yahoo.com.|Institute of Genomics and Integrative Biology (CSIR), Mall Road, Delhi 110 007, India. anusha77in@yahoo.com.|Institute of Genomics and Integrative Biology (CSIR), Mall Road, Delhi 110 007, India. anusha77in@yahoo.com.|Institute of Genomics and Integrative Biology (CSIR), Mall Road, Delhi 110 007, India. anusha77in@yahoo.com.', 'India|India|India|India', 0, 'Computational Biology|DNA Probes|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Research Design|Software|Software Design', 'Journal Article', '10.1186/1471-2105-5-142', '15461789', 'Microarray is a high-throughput technology to study expression of thousands of genes in parallel. A critical aspect of microarray production is the design aimed at space optimization while maximizing the number of gene probes and their replicates to be spotted.'),
(90225, 2004, 'bmc', 'Identitag, a relational database for SAGE tag identification and interspecies comparison of SAGE libraries', 'Keime, Céline|Damiola, Francesca|Mouchiroud, Dominique|Duret, Laurent|Gandrillon, Olivier', 'Equipe Signalisation et identités cellulaires, Centre de Génétique Moléculaire et Cellulaire CNRS UMR 5534, Université Claude Bernard Lyon 1, bâtiment Gregor Mendel, 16 rue Raphaël Dubois 69622 Villeurbanne cedex France. keime@cgmc.univ-lyon1.fr|Equipe Signalisation et identités cellulaires, Centre de Génétique Moléculaire et Cellulaire CNRS UMR 5534, Université Claude Bernard Lyon 1, bâtiment Gregor Mendel, 16 rue Raphaël Dubois 69622 Villeurbanne cedex France. keime@cgmc.univ-lyon1.fr|Equipe Signalisation et identités cellulaires, Centre de Génétique Moléculaire et Cellulaire CNRS UMR 5534, Université Claude Bernard Lyon 1, bâtiment Gregor Mendel, 16 rue Raphaël Dubois 69622 Villeurbanne cedex France. keime@cgmc.univ-lyon1.fr|Equipe Signalisation et identités cellulaires, Centre de Génétique Moléculaire et Cellulaire CNRS UMR 5534, Université Claude Bernard Lyon 1, bâtiment Gregor Mendel, 16 rue Raphaël Dubois 69622 Villeurbanne cedex France. keime@cgmc.univ-lyon1.fr|Equipe Signalisation et identités cellulaires, Centre de Génétique Moléculaire et Cellulaire CNRS UMR 5534, Université Claude Bernard Lyon 1, bâtiment Gregor Mendel, 16 rue Raphaël Dubois 69622 Villeurbanne cedex France. keime@cgmc.univ-lyon1.fr', 'France|France|France|France|France', 17, 'Animals|Chickens|DNA, Complementary|Databases, Genetic|Expressed Sequence Tags|Gene Expression Profiling|Humans|Poly A|Sequence Homology, Nucleic Acid|Software|Software Design|Species Specificity', 'Comparative Study', '10.1186/1471-2105-5-143', '15469608', 'Serial Analysis of Gene Expression (SAGE) is a method of large-scale gene expression analysis that has the potential to generate the full list of mRNAs present within a cell population at a given time and their frequency. An essential step in SAGE library analysis is the unambiguous assignment of each 14 bp tag to the transcript from which it was derived. This process, called tag-to-gene mapping, represents a step that has to be improved in the analysis of SAGE libraries. Indeed, the existing web sites providing correspondence between tags and transcripts do not concern all species for which numerous EST and cDNA have already been sequenced.'),
(90226, 2004, 'bmc', 'Overdispersed logistic regression for SAGE: modelling multiple groups and covariates', 'Baggerly, Keith A|Deng, Li|Morris, Jeffrey S|Aldaz, C Marcelo', 'Department of Biostatistics and Applied Mathematics, UT M. D. Anderson Cancer Center, Houston, TX, USA. kabagg@mdanderson.org|Department of Biostatistics and Applied Mathematics, UT M. D. Anderson Cancer Center, Houston, TX, USA. kabagg@mdanderson.org|Department of Biostatistics and Applied Mathematics, UT M. D. Anderson Cancer Center, Houston, TX, USA. kabagg@mdanderson.org|Department of Biostatistics and Applied Mathematics, UT M. D. Anderson Cancer Center, Houston, TX, USA. kabagg@mdanderson.org', 'United States|United States|United States|United States', 35, 'Analysis of Variance|Cell Line, Tumor|Colon|Colonic Neoplasms|DNA|DNA, Neoplasm|Gene Expression Profiling|Gene Expression Regulation|Gene Library|Humans|Logistic Models|Mathematical Computing|Multivariate Analysis|Rectal Neoplasms', 'Comparative Study', '10.1186/1471-2105-5-144', '15469612', 'Two major identifiable sources of variation in data derived from the Serial Analysis of Gene Expression (SAGE) are within-library sampling variability and between-library heterogeneity within a group. Most published methods for identifying differential expression focus on just the sampling variability. In recent work, the problem of assessing differential expression between two groups of SAGE libraries has been addressed by introducing a beta-binomial hierarchical model that explicitly deals with both of the above sources of variation. This model leads to a test statistic analogous to a weighted two-sample t-test. When the number of groups involved is more than two, however, a more general approach is needed.'),
(90227, 2004, 'bmc', 'Tools for loading MEDLINE into a local relational database', 'Oliver, Diane E|Bhalotia, Gaurav|Schwartz, Ariel S|Altman, Russ B|Hearst, Marti A', 'Department of Genetics, Stanford University, Stanford, CA, USA. oliver@SMI.Stanford.EDU <oliver@SMI.Stanford.EDU>|Department of Genetics, Stanford University, Stanford, CA, USA. oliver@SMI.Stanford.EDU <oliver@SMI.Stanford.EDU>|Department of Genetics, Stanford University, Stanford, CA, USA. oliver@SMI.Stanford.EDU <oliver@SMI.Stanford.EDU>|Department of Genetics, Stanford University, Stanford, CA, USA. oliver@SMI.Stanford.EDU <oliver@SMI.Stanford.EDU>|Department of Genetics, Stanford University, Stanford, CA, USA. oliver@SMI.Stanford.EDU <oliver@SMI.Stanford.EDU>', 'United States|United States|United States|United States|United States', 0, 'Database Management Systems|Databases, Bibliographic|MEDLINE|Software|Software Design|Software Validation|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-5-146', '15471541', 'Researchers who use MEDLINE for text mining, information extraction, or natural language processing may benefit from having a copy of MEDLINE that they can manage locally. The National Library of Medicine (NLM) distributes MEDLINE in eXtensible Markup Language (XML)-formatted text files, but it is difficult to query MEDLINE in that format. We have developed software tools to parse the MEDLINE data files and load their contents into a relational database. Although the task is conceptually straightforward, the size and scope of MEDLINE make the task nontrivial. Given the increasing importance of text analysis in biology and medicine, we believe a local installation of MEDLINE will provide helpful computing infrastructure for researchers.'),
(90228, 2004, 'bmc', 'Extending the mutual information measure to rank inferred literature relationships', 'Wren, Jonathan D', 'Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 101 David L, Boren Blvd, Rm 2025, Norman 73019, USA. Jonathan.Wren@OU.edu', 'United States', 72, 'Humans|Peer Review, Research', 'Journal Article', '10.1186/1471-2105-5-145', '15471547', 'Within the peer-reviewed literature, associations between two things are not always recognized until commonalities between them become apparent. These commonalities can provide justification for the inference of a new relationship where none was previously known, and are the basis of most observation-based hypothesis formation. It has been shown that the crux of the problem is not finding inferable associations, which are extraordinarily abundant given the scale-free networks that arise from literature-based associations, but determining which ones are informative. The Mutual Information Measure (MIM) is a well-established method to measure how informative an association is, but is limited to direct (i.e. observable) associations.'),
(90229, 2004, 'bmc', 'Content-rich biological network constructed by mining PubMed abstracts', 'Chen, Hao|Sharp, Burt M', 'Department of Pharmacology, University of Tennessee Health Science Center, Room 115 Crowe Research Building, 874 Union Avenue, Memphis, Tennessee 38163, USA. hchen@utmem.edu|Department of Pharmacology, University of Tennessee Health Science Center, Room 115 Crowe Research Building, 874 Union Avenue, Memphis, Tennessee 38163, USA. hchen@utmem.edu', 'United States|United States', 237, 'Biology|Computer Graphics|Databases, Protein|Information Services|Information Storage and Retrieval|Internet|Natural Language Processing|Protein Binding|PubMed|Software|Software Design|User-Computer Interface', 'Evaluation Studies', '10.1186/1471-2105-5-147', '15473905', 'The integration of the rapidly expanding corpus of information about the genome, transcriptome, and proteome, engendered by powerful technological advances, such as microarrays, and the availability of genomic sequence from multiple species, challenges the grasp and comprehension of the scientific community. Despite the existence of text-mining methods that identify biological relationships based on the textual co-occurrence of gene/protein terms or similarities in abstract texts, knowledge of the underlying molecular connections on a large scale, which is prerequisite to understanding novel biological processes, lags far behind the accumulation of data. While computationally efficient, the co-occurrence-based approaches fail to characterize (e.g., inhibition or stimulation, directionality) biological interactions. Programs with natural language processing (NLP) capability have been created to address these limitations, however, they are in general not readily accessible to the public.'),
(90230, 2004, 'bmc', 'Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data', 'Martin, Dietmar E|Demougin, Philippe|Hall, Michael N|Bellis, Michel', 'Biozentrum, University of Basel, CH-4056 Basel, Switzerland. dietmar.martin@unibas.ch <dietmar.martin@unibas.ch>|Biozentrum, University of Basel, CH-4056 Basel, Switzerland. dietmar.martin@unibas.ch <dietmar.martin@unibas.ch>|Biozentrum, University of Basel, CH-4056 Basel, Switzerland. dietmar.martin@unibas.ch <dietmar.martin@unibas.ch>|Biozentrum, University of Basel, CH-4056 Basel, Switzerland. dietmar.martin@unibas.ch <dietmar.martin@unibas.ch>', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Comparative Study', '10.1186/1471-2105-5-148', '15476558', 'A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals between two biological conditions.'),
(90231, 2004, 'bmc', 'Improved hit criteria for DNA local alignment', 'Noé, Laurent|Kucherov, Gregory', 'LORIA/INRIA-Lorraine, Villers-lès-Nancy France. Laurent.Noe@loria.fr|LORIA/INRIA-Lorraine, Villers-lès-Nancy France. Laurent.Noe@loria.fr', 'France|France', 44, 'Algorithms|Animals|Chromosomes, Human, X|DNA|DNA, Bacterial|DNA, Fungal|Drosophila|Humans|Markov Chains|Models, Statistical|Neisseria meningitidis|Saccharomyces cerevisiae|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-5-149', '15485572', 'The hit criterion is a key component of heuristic local alignment algorithms. It specifies a class of patterns assumed to witness a potential similarity, and this choice is decisive for the selectivity and sensitivity of the whole method.'),
(90232, 2004, 'bmc', 'PCOGR: phylogenetic COG ranking as an online tool to judge the specificity of COGs with respect to freely definable groups of organisms', 'Meereis, Florian|Kaufmann, Michael', 'The Protein Chemistry Group, Institute of Neurobiochemistry, Witten/Herdecke University, Stockumer Str. 10, 58448 Witten, Germany. fmeereis@uni-wh.de <fmeereis@uni-wh.de>|The Protein Chemistry Group, Institute of Neurobiochemistry, Witten/Herdecke University, Stockumer Str. 10, 58448 Witten, Germany. fmeereis@uni-wh.de <fmeereis@uni-wh.de>', 'Germany|Germany', 6, 'Escherichia coli|Phylogeny|Saccharomyces cerevisiae|Software|Species Specificity', 'Comparative Study', '10.1186/1471-2105-5-150', '15488147', 'The rapidly increasing number of completely sequenced genomes led to the establishment of the COG-database which, based on sequence homologies, assigns similar proteins from different organisms to clusters of orthologous groups (COGs). There are several bioinformatic studies that made use of this database to determine (hyper)thermophile-specific proteins by searching for COGs containing (almost) exclusively proteins from (hyper)thermophilic genomes. However, public software to perform individually definable group-specific searches is not available.'),
(90233, 2004, 'bmc', 'Caryoscope: an Open Source Java application for viewing microarray data in a genomic context', 'Awad, Ihab A B|Rees, Christian A|Hernandez-Boussard, Tina|Ball, Catherine A|Sherlock, Gavin', 'Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. ihab@stanford.edu <ihab@stanford.edu>|Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. ihab@stanford.edu <ihab@stanford.edu>|Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. ihab@stanford.edu <ihab@stanford.edu>|Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. ihab@stanford.edu <ihab@stanford.edu>|Dept. of Genetics, 300 Pasteur Drive, Stanford University Medical School, Stanford, CA 94305-5120, USA. ihab@stanford.edu <ihab@stanford.edu>', 'United States|United States|United States|United States|United States', 26, 'Chromosome Mapping|Computational Biology|Computer Graphics|Genome|Microarray Analysis|Nucleic Acid Hybridization|Programming Languages|Software|Software Design', 'Comparative Study', '10.1186/1471-2105-5-151', '15488149', 'Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented graphically in a genomic context.'),
(90234, 2004, 'bmc', 'Incidence of quasi-ditags in catalogs generated by Serial Analysis of Gene Expression (SAGE)', 'Anisimov, Sergey V|Sharov, Alexei A', 'Section for Neuronal Survival, Wallenberg Neuroscience Center, Lund University, 221 84 Lund, Sweden. Sergey.Anisimov@mphy.lu.se|Section for Neuronal Survival, Wallenberg Neuroscience Center, Lund University, 221 84 Lund, Sweden. Sergey.Anisimov@mphy.lu.se', 'Sweden|Sweden', 0, 'Animals|DNA Primers|DNA, Bacterial|DNA, Concatenated|DNA, Fungal|Escherichia coli K12|Gene Expression Profiling|Gene Expression Regulation|Gene Library|Genome, Bacterial|Genome, Fungal|Genomics|Mice|Saccharomyces cerevisiae|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-5-152', '15491492', 'Serial Analysis of Gene Expression (SAGE) is a functional genomic technique that quantitatively analyzes the cellular transcriptome. The analysis of SAGE libraries relies on the identification of ditags from sequencing files, however, the software used to examine SAGE libraries cannot distinguish between authentic versus false ditags (quasi-ditags).'),
(90235, 2004, 'bmc', 'Inter-residue distances derived from fold contact propensities correlate with evolutionary substitution costs', 'Williams, Gareth|Doherty, Patrick', 'Wolfson Centre for Age-Related Diseases, The Wolfson Wing, Hodgkin Building, Kings College London, London SE1 1UL, UK. gareth.2.williams@kcl.ac.uk|Wolfson Centre for Age-Related Diseases, The Wolfson Wing, Hodgkin Building, Kings College London, London SE1 1UL, UK. gareth.2.williams@kcl.ac.uk', 'United Kingdom|United Kingdom', 6, 'Amino Acid Substitution|Amino Acids|Evolution, Molecular|Protein Folding|Proteins', 'Journal Article', '10.1186/1471-2105-5-153', '15491497', 'The wealth of information on protein structure has led to a variety of statistical analyses of the role played by individual amino acid types in the protein fold. In particular, the contact propensities between the various amino acids can be converted into folding energies that have proved useful in structure prediction. The present study addresses the relationship of protein folding propensities to the evolutionary relationship between residues.'),
(90236, 2004, 'bmc', 'Information assessment on predicting protein-protein interactions', 'Lin, Nan|Wu, Baolin|Jansen, Ronald|Gerstein, Mark|Zhao, Hongyu', 'Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63130, USA. nlin@math.wustl.edu <nlin@math.wustl.edu>|Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63130, USA. nlin@math.wustl.edu <nlin@math.wustl.edu>|Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63130, USA. nlin@math.wustl.edu <nlin@math.wustl.edu>|Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63130, USA. nlin@math.wustl.edu <nlin@math.wustl.edu>|Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63130, USA. nlin@math.wustl.edu <nlin@math.wustl.edu>', 'United States|United States|United States|United States|United States', 131, 'Artificial Intelligence|Databases, Protein|Fungal Proteins|Genome, Fungal|Genomics|Logistic Models|Models, Genetic|Predictive Value of Tests|Protein Interaction Mapping|Proteome', 'Comparative Study', '10.1186/1471-2105-5-154', '15491499', 'Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions are of significant value, but the high-throughput experimental technologies suffer from high rates of both false positive and false negative predictions. In addition to high-throughput experimental data, many diverse types of genomic data can help predict protein-protein interactions, such as mRNA expression, localization, essentiality, and functional annotation. Evaluations of the information contributions from different evidences help to establish more parsimonious models with comparable or better prediction accuracy, and to obtain biological insights of the relationships between protein-protein interactions and other genomic information.'),
(90237, 2004, 'bmc', 'Modeling of cell signaling pathways in macrophages by semantic networks', 'Hsing, Michael|Bellenson, Joel L|Shankey, Conor|Cherkasov, Artem', 'CIHR/MSFHR Strategic Training Program in Bioinformatics, Genetics Graduate Program, Faculty of Graduate Studies, University of British Columbia, Vancouver, British Columbia, V5Z 3J5, Canada. mhsing@interchange.ubc.ca <mhsing@interchange.ubc.ca>|CIHR/MSFHR Strategic Training Program in Bioinformatics, Genetics Graduate Program, Faculty of Graduate Studies, University of British Columbia, Vancouver, British Columbia, V5Z 3J5, Canada. mhsing@interchange.ubc.ca <mhsing@interchange.ubc.ca>|CIHR/MSFHR Strategic Training Program in Bioinformatics, Genetics Graduate Program, Faculty of Graduate Studies, University of British Columbia, Vancouver, British Columbia, V5Z 3J5, Canada. mhsing@interchange.ubc.ca <mhsing@interchange.ubc.ca>|CIHR/MSFHR Strategic Training Program in Bioinformatics, Genetics Graduate Program, Faculty of Graduate Studies, University of British Columbia, Vancouver, British Columbia, V5Z 3J5, Canada. mhsing@interchange.ubc.ca <mhsing@interchange.ubc.ca>', 'Canada|Canada|Canada|Canada', 0, 'Computer Simulation|Humans|Intracellular Space|Macrophages|Models, Genetic|Multiprotein Complexes|Mycobacterium tuberculosis|Peptides|Protein Structure, Tertiary|Signal Transduction|Tuberculosis', 'Journal Article', '10.1186/1471-2105-5-156', '15494071', 'Substantial amounts of data on cell signaling, metabolic, gene regulatory and other biological pathways have been accumulated in literature and electronic databases. Conventionally, this information is stored in the form of pathway diagrams and can be characterized as highly compartmental (i.e. individual pathways are not connected into more general networks). Current approaches for representing pathways are limited in their capacity to model molecular interactions in their spatial and temporal context. Moreover, the critical knowledge of cause-effect relationships among signaling events is not reflected by most conventional approaches for manipulating pathways.'),
(90238, 2004, 'bmc', 'PASBio: predicate-argument structures for event extraction in molecular biology', 'Wattarujeekrit, Tuangthong|Shah, Parantu K|Collier, Nigel', 'National Institute of Informatics, National Center of Sciences, Hitotsubashi 2-1-2, Chiyoda-ku, Tokyo 101-8430, Japan. tuangthong@grad.nii.ac.jp <tuangthong@grad.nii.ac.jp>|National Institute of Informatics, National Center of Sciences, Hitotsubashi 2-1-2, Chiyoda-ku, Tokyo 101-8430, Japan. tuangthong@grad.nii.ac.jp <tuangthong@grad.nii.ac.jp>|National Institute of Informatics, National Center of Sciences, Hitotsubashi 2-1-2, Chiyoda-ku, Tokyo 101-8430, Japan. tuangthong@grad.nii.ac.jp <tuangthong@grad.nii.ac.jp>', 'Japan|Japan|Japan', 62, 'Cybernetics|Database Management Systems|Databases, Genetic|Humans|Linguistics|Molecular Biology|Software', 'Journal Article', '10.1186/1471-2105-5-155', '15494078', 'The exploitation of information extraction (IE), a technology aiming to provide instances of structured representations from free-form text, has been rapidly growing within the molecular biology (MB) research community to keep track of the latest results reported in literature. IE systems have traditionally used shallow syntactic patterns for matching facts in sentences but such approaches appear inadequate to achieve high accuracy in MB event extraction due to complex sentence structure. A consensus in the IE community is emerging on the necessity for exploiting deeper knowledge structures such as through the relations between a verb and its arguments shown by predicate-argument structure (PAS). PAS is of interest as structures typically correspond to events of interest and their participating entities. For this to be realized within IE a key knowledge component is the definition of PAS frames. PAS frames for non-technical domains such as newswire are already being constructed in several projects such as PropBank, VerbNet, and FrameNet. Knowledge from PAS should enable more accurate applications in several areas where sentence understanding is required like machine translation and text summarization. In this article, we explore the need to adapt PAS for the MB domain and specify PAS frames to support IE, as well as outlining the major issues that require consideration in their construction.'),
(90239, 2004, 'bmc', 'Gapped alignment of protein sequence motifs through Monte Carlo optimization of a hidden Markov model', 'Neuwald, Andrew F|Liu, Jun S', 'Cold Spring Harbor Laboratory, 1 Bungtown Road, P,O, Box 100, Cold Spring Harbor, NY 11724, USA. neuwald@cshl.org|Cold Spring Harbor Laboratory, 1 Bungtown Road, P,O, Box 100, Cold Spring Harbor, NY 11724, USA. neuwald@cshl.org', 'United States|United States', 30, 'Amino Acid Motifs|Amino Acid Sequence|Animals|Archaeal Proteins|Bacterial Proteins|Conserved Sequence|GTP Phosphohydrolases|Helminth Proteins|Hydrolases|Markov Chains|Molecular Sequence Data|Monte Carlo Method|Protein Folding|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Serine Endopeptidases|Software', 'Journal Article', '10.1186/1471-2105-5-157', '15504234', 'Certain protein families are highly conserved across distantly related organisms and belong to large and functionally diverse superfamilies. The patterns of conservation present in these protein sequences presumably are due to selective constraints maintaining important but unknown structural mechanisms with some constraints specific to each family and others shared by a larger subset or by the entire superfamily. To exploit these patterns as a source of functional information, we recently devised a statistically based approach called contrast hierarchical alignment and interaction network (CHAIN) analysis, which infers the strengths of various categories of selective constraints from co-conserved patterns in a multiple alignment. The power of this approach strongly depends on the quality of the multiple alignments, which thus motivated development of theoretical concepts and strategies to improve alignment of conserved motifs within large sets of distantly related sequences.'),
(90240, 2004, 'bmc', 'A computational approach for ordering signal transduction pathway components from genomics and proteomics Data', 'Liu, Yin|Zhao, Hongyu', 'Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA. yin.liu@yale.edu <yin.liu@yale.edu>|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA. yin.liu@yale.edu <yin.liu@yale.edu>', 'United States|United States', 0, 'Computational Biology|Databases, Protein|Gene Expression Profiling|Genomics|Mitogen-Activated Protein Kinases|Oligonucleotide Array Sequence Analysis|Predictive Value of Tests|Protein Interaction Mapping|Proteome|Proteomics|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Comparative Study', '10.1186/1471-2105-5-158', '15504238', 'Signal transduction is one of the most important biological processes by which cells convert an external signal into a response. Novel computational approaches to mapping proteins onto signaling pathways are needed to fully take advantage of the rapid accumulation of genomic and proteomics information. However, despite their importance, research on signaling pathways reconstruction utilizing large-scale genomics and proteomics information has been limited.'),
(90241, 2004, 'bmc', 'Combining gene expression data from different generations of oligonucleotide arrays', 'Hwang, Kyu-Baek|Kong, Sek Won|Greenberg, Steve A|Park, Peter J', 'School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea. kbhwang@bi.snu.ac.kr <kbhwang@bi.snu.ac.kr>|School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea. kbhwang@bi.snu.ac.kr <kbhwang@bi.snu.ac.kr>|School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea. kbhwang@bi.snu.ac.kr <kbhwang@bi.snu.ac.kr>|School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea. kbhwang@bi.snu.ac.kr <kbhwang@bi.snu.ac.kr>', '-|-|-|-', 49, 'Biopsy|Cluster Analysis|DNA Probes|Databases, Genetic|Dermatomyositis|Gene Expression Profiling|Gene Expression Regulation|Genetic Variation|Humans|Myositis|Oligonucleotide Array Sequence Analysis|Polymyositis|Reproducibility of Results', 'Comparative Study', '10.1186/1471-2105-5-159', '15504239', 'One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from ones own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform.'),
(90242, 2004, 'bmc', 'Reuse of imputed data in microarray analysis increases imputation efficiency', 'Kim, Ki-Yeol|Kim, Byoung-Jin|Yi, Gwan-Su', 'School of engineering, Information and Communications University, 103-6 Munji-dong, Yusung-gu, Daejon 305-714, South Korea. kky1004@icu.ac.kr <kky1004@icu.ac.kr>|School of engineering, Information and Communications University, 103-6 Munji-dong, Yusung-gu, Daejon 305-714, South Korea. kky1004@icu.ac.kr <kky1004@icu.ac.kr>|School of engineering, Information and Communications University, 103-6 Munji-dong, Yusung-gu, Daejon 305-714, South Korea. kky1004@icu.ac.kr <kky1004@icu.ac.kr>', '-|-|-', 100, 'Efficiency, Organizational|Microarray Analysis', 'Evaluation Studies', '10.1186/1471-2105-5-160', '15504240', 'The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked.'),
(90243, 2004, 'bmc', 'Implications for domain fusion protein-protein interactions based on structural information', 'Chia, Jer-Ming|Kolatkar, Prasanna R', 'The Genome Institute of Singapore, Singapore. g04030676@nus.edu.sg <g04030676@nus.edu.sg>|The Genome Institute of Singapore, Singapore. g04030676@nus.edu.sg <g04030676@nus.edu.sg>', 'Singapore|Singapore', 0, 'Amino Acids|Conserved Sequence|Databases, Protein|Peptides|Predictive Value of Tests|Protein Interaction Mapping|Protein Structure, Tertiary|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-5-161', '15504241', 'Several in silico methods exist that were developed to predict protein interactions from the copious amount of genomic and proteomic data. One of these methods is Domain Fusion, which has proven to be effective in predicting functional links between proteins.'),
(90244, 2004, 'bmc', 'Extractor for ESI quadrupole TOF tandem MS data enabled for high throughput batch processing', 'Boehm, Andreas M|Galvin, Robert P|Sickmann, Albert', 'Protein Mass Spectrometry and Functional Proteomics Group, Rudolf-Virchow-Center for Experimental Biomedicine, Universitaet Wuerzburg, Versbacher Strasse 9, D-97078 Wuerzburg, Germany. andreas.boehm@virchow.uni-wuerzburg.de|Protein Mass Spectrometry and Functional Proteomics Group, Rudolf-Virchow-Center for Experimental Biomedicine, Universitaet Wuerzburg, Versbacher Strasse 9, D-97078 Wuerzburg, Germany. andreas.boehm@virchow.uni-wuerzburg.de|Protein Mass Spectrometry and Functional Proteomics Group, Rudolf-Virchow-Center for Experimental Biomedicine, Universitaet Wuerzburg, Versbacher Strasse 9, D-97078 Wuerzburg, Germany. andreas.boehm@virchow.uni-wuerzburg.de', 'Germany|Germany|Germany', 29, 'Automation|Image Processing, Computer-Assisted|Proteomics|Software|Software Design|Spectrometry, Mass, Electrospray Ionization', 'Comparative Study', '10.1186/1471-2105-5-162', '15507135', 'Mass spectrometry based proteomics result in huge amounts of data that has to be processed in real time in order to efficiently feed identification algorithms and to easily integrate in automated environments. We present wiff2dta, a tool created to convert MS/MS data obtained using Applied Biosystems QStar and QTrap 2000 and 4000 series.'),
(90245, 2004, 'bmc', 'TETRA: a web-service and a stand-alone program for the analysis and comparison of tetranucleotide usage patterns in DNA sequences', 'Teeling, Hanno|Waldmann, Jost|Lombardot, Thierry|Bauer, Margarete|Glöckner, Frank Oliver', 'Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. hteeling@mpi-bremen.de <hteeling@mpi-bremen.de>|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. hteeling@mpi-bremen.de <hteeling@mpi-bremen.de>|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. hteeling@mpi-bremen.de <hteeling@mpi-bremen.de>|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. hteeling@mpi-bremen.de <hteeling@mpi-bremen.de>|Microbial Genomics Group, Max Planck Institute for Marine Microbiology, D-28359 Bremen, Germany. hteeling@mpi-bremen.de <hteeling@mpi-bremen.de>', 'Germany|Germany|Germany|Germany|Germany', 246, 'Base Composition|Bradyrhizobium|Chromosomes, Bacterial|DNA, Bacterial|Escherichia|Genome, Bacterial|Internet|Microsatellite Repeats|Prochlorococcus|Sequence Analysis, DNA|Shigella|Sinorhizobium|Software|Yersinia', 'Comparative Study', '10.1186/1471-2105-5-163', '15507136', 'In the emerging field of environmental genomics, direct cloning and sequencing of genomic fragments from complex microbial communities has proven to be a valuable source of new enzymes, expanding the knowledge of basic biological processes. The central problem of this so called metagenome-approach is that the cloned fragments often lack suitable phylogenetic marker genes, rendering the identification of clones that are likely to originate from the same genome difficult or impossible. In such cases, the analysis of intrinsic DNA-signatures like tetranucleotide frequencies can provide valuable hints on fragment affiliation. With this application in mind, the TETRA web-service and the TETRA stand-alone program have been developed, both of which automate the task of comparative tetranucleotide frequency analysis.'),
(90246, 2004, 'bmc', 'Multivariate search for differentially expressed gene combinations', 'Xiao, Yuanhui|Frisina, Robert|Gordon, Alexander|Klebanov, Lev|Yakovlev, Andrei', 'Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. yxiao@bst.rochester.edu <yxiao@bst.rochester.edu>|Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. yxiao@bst.rochester.edu <yxiao@bst.rochester.edu>|Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. yxiao@bst.rochester.edu <yxiao@bst.rochester.edu>|Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. yxiao@bst.rochester.edu <yxiao@bst.rochester.edu>|Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwood Avenue, Rochester, New York 14642, USA. yxiao@bst.rochester.edu <yxiao@bst.rochester.edu>', 'United States|United States|United States|United States|United States', 30, 'Aging|Algorithms|Animals|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Mice|Mice, Inbred CBA|Models, Genetic|Multivariate Analysis|Organ of Corti|Stria Vascularis', 'Journal Article', '10.1186/1471-2105-5-164', '15507138', 'To identify differentially expressed genes, it is standard practice to test a two-sample hypothesis for each gene with a proper adjustment for multiple testing. Such tests are essentially univariate and disregard the multidimensional structure of microarray data. A more general two-sample hypothesis is formulated in terms of the joint distribution of any sub-vector of expression signals.'),
(90247, 2004, 'bmc', 'Identification and utilization of inter-species conserved (ISC) probesets on Affymetrix human GeneChip platforms for the optimization of the assessment of expression patterns in non human primate (NHP) samples', 'Wang, Zhining|Lewis, Mark G|Nau, Martin E|Arnold, Alma|Vahey, Maryanne T', 'Henry M Jackson Foundation for the Advancement of Military Medicine, Rockville, Maryland 20850, USA. zwang@hivresearch.org|Henry M Jackson Foundation for the Advancement of Military Medicine, Rockville, Maryland 20850, USA. zwang@hivresearch.org|Henry M Jackson Foundation for the Advancement of Military Medicine, Rockville, Maryland 20850, USA. zwang@hivresearch.org|Henry M Jackson Foundation for the Advancement of Military Medicine, Rockville, Maryland 20850, USA. zwang@hivresearch.org|Henry M Jackson Foundation for the Advancement of Military Medicine, Rockville, Maryland 20850, USA. zwang@hivresearch.org', 'United States|United States|United States|United States|United States', 38, 'Animals|Conserved Sequence|DNA Probes|Databases, Genetic|Expressed Sequence Tags|Gene Expression Profiling|Humans|Leukocytes, Mononuclear|Macaca mulatta|Microarray Analysis|Normal Distribution|Pan troglodytes|Species Specificity', 'Comparative Study', '10.1186/1471-2105-5-165', '15507140', 'While researchers have utilized versions of the Affymetrix human GeneChip for the assessment of expression patterns in non human primate (NHP) samples, there has been no comprehensive sequence analysis study undertaken to demonstrate that the probe sequences designed to detect human transcripts are reliably hybridizing with their orthologs in NHP. By aligning probe sequences with expressed sequence tags (ESTs) in NHP, inter-species conserved (ISC) probesets, which have two or more probes complementary to ESTs in NHP, were identified on human GeneChip platforms. The utility of human GeneChips for the assessment of NHP expression patterns can be effectively evaluated by analyzing the hybridization behaviour of ISC probesets. Appropriate normalization methods were identified that further improve the reliability of human GeneChips for interspecies (human vs NHP) comparisons.'),
(90248, 2004, 'bmc', 'A probabilistic model for the evolution of RNA structure', 'Holmes, Ian', 'Department of Bioengineering, University of California, Berkeley 94720-1762, USA. ihh@berkeley.edu', 'United States', 35, 'Evolution, Molecular|Models, Genetic|Mutagenesis|Nucleic Acid Conformation|RNA', 'Journal Article', '10.1186/1471-2105-5-166', '15507142', 'For the purposes of finding and aligning noncoding RNA gene- and cis-regulatory elements in multiple-genome datasets, it is useful to be able to derive multi-sequence stochastic grammars (and hence multiple alignment algorithms) systematically, starting from hypotheses about the various kinds of random mutation event and their rates.'),
(90249, 2004, 'bmc', 'Improvement of alignment accuracy utilizing sequentially conserved motifs', 'Chakrabarti, Saikat|Bhardwaj, Nitin|Anand, Prem A|Sowdhamini, Ramanathan', 'National Centre for Biological Sciences (TIFR), Bangalore 560065, India. saikat@ncbs.res.in <saikat@ncbs.res.in>|National Centre for Biological Sciences (TIFR), Bangalore 560065, India. saikat@ncbs.res.in <saikat@ncbs.res.in>|National Centre for Biological Sciences (TIFR), Bangalore 560065, India. saikat@ncbs.res.in <saikat@ncbs.res.in>|National Centre for Biological Sciences (TIFR), Bangalore 560065, India. saikat@ncbs.res.in <saikat@ncbs.res.in>', 'India|India|India|India', 9, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Benchmarking|Conserved Sequence|Databases, Protein|Genetic Variation|Globins|Molecular Sequence Data|Peptides|Protein Structure, Tertiary|Sequence Alignment|Software|Software Design', 'Comparative Study', '10.1186/1471-2105-5-167', '15509307', 'Multiple sequence alignment algorithms are very important tools in molecular biology today. Accurate alignment of proteins is central to several areas such as homology modelling, docking studies, understanding evolutionary trends and study of structure-function relationships. In recent times, improvement of existing progressing programs and implementation of new iterative algorithms have made a significant change in this field.'),
(90250, 2004, 'bmc', 'Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites', 'Meinicke, Peter|Tech, Maike|Morgenstern, Burkhard|Merkl, Rainer', 'Abteilung Bioinformatik, Institut für Mikrobiologie und Genetik, Georg-August-Universität Göttingen, Goldschmidtstr, 1, 37077 Göttingen, Germany. pmeinic@gwdg.de|Abteilung Bioinformatik, Institut für Mikrobiologie und Genetik, Georg-August-Universität Göttingen, Goldschmidtstr, 1, 37077 Göttingen, Germany. pmeinic@gwdg.de|Abteilung Bioinformatik, Institut für Mikrobiologie und Genetik, Georg-August-Universität Göttingen, Goldschmidtstr, 1, 37077 Göttingen, Germany. pmeinic@gwdg.de|Abteilung Bioinformatik, Institut für Mikrobiologie und Genetik, Georg-August-Universität Göttingen, Goldschmidtstr, 1, 37077 Göttingen, Germany. pmeinic@gwdg.de', 'Germany|Germany|Germany|Germany', 43, 'Algorithms|Artificial Intelligence|Codon, Initiator|Computational Biology|Computer Graphics|Databases, Genetic|Escherichia coli K12|Genes, Bacterial|Models, Genetic|Prokaryotic Initiation Factors|Sequence Alignment', 'Comparative Study', '10.1186/1471-2105-5-169', '15511290', 'Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks within the field of bioinformatics. Conventional kernels utilized so far do not provide an easy interpretation of the learnt representations in terms of positional and compositional variability of the underlying biological signals.'),
(90251, 2004, 'bmc', 'PhyME: a probabilistic algorithm for finding motifs in sets of orthologous sequences', 'Sinha, Saurabh|Blanchette, Mathieu|Tompa, Martin', 'Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 10021, USA. saurabh@lonnrot.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 10021, USA. saurabh@lonnrot.rockefeller.edu|Center for Studies in Physics and Biology, The Rockefeller University, New York, NY 10021, USA. saurabh@lonnrot.rockefeller.edu', 'United States|United States|United States', 142, 'Algorithms|Animals|Base Composition|DNA|DNA, Fungal|Drosophila|Drosophila melanogaster|Enhancer Elements, Genetic|Evolution, Molecular|Humans|Models, Genetic|Phylogeny|Saccharomyces|Saccharomyces cerevisiae|Software|Species Specificity', 'Comparative Study', '10.1186/1471-2105-5-170', '15511292', 'This paper addresses the problem of discovering transcription factor binding sites in heterogeneous sequence data, which includes regulatory sequences of one or more genes, as well as their orthologs in other species.'),
(90252, 2004, 'bmc', 'Incremental genetic K-means algorithm and its application in gene expression data analysis', 'Lu, Yi|Lu, Shiyong|Fotouhi, Farshad|Deng, Youping|Brown, Susan J', 'Dept. of Computer Science, Wayne State University, Detroit, MI 48202, USA. luyi@wayne.edu <luyi@wayne.edu>|Dept. of Computer Science, Wayne State University, Detroit, MI 48202, USA. luyi@wayne.edu <luyi@wayne.edu>|Dept. of Computer Science, Wayne State University, Detroit, MI 48202, USA. luyi@wayne.edu <luyi@wayne.edu>|Dept. of Computer Science, Wayne State University, Detroit, MI 48202, USA. luyi@wayne.edu <luyi@wayne.edu>|Dept. of Computer Science, Wayne State University, Detroit, MI 48202, USA. luyi@wayne.edu <luyi@wayne.edu>', 'United States|United States|United States|United States|United States', 91, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Genetics|Time Factors', 'Comparative Study', '10.1186/1471-2105-5-172', '15511294', 'In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms such as K-means, hierarchical clustering, SOM, etc, genes are partitioned into groups based on the similarity between their expression profiles. In this way, functionally related genes are identified. As the amount of laboratory data in molecular biology grows exponentially each year due to advanced technologies such as Microarray, new efficient and effective methods for clustering must be developed to process this growing amount of biological data.');
