INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94737, 2011, 'bmc', 'MotifMap: integrative genome-wide maps of regulatory motif sites for model species', 'Daily, Kenneth|Patel, Vishal R|Rigor, Paul|Xie, Xiaohui|Baldi, Pierre', 'Department of Computer Science, University of California Irvine, Irvine, CA 92697, USA.|Department of Computer Science, University of California Irvine, Irvine, CA 92697, USA.|Department of Computer Science, University of California Irvine, Irvine, CA 92697, USA.|Department of Computer Science, University of California Irvine, Irvine, CA 92697, USA.|Department of Computer Science, University of California Irvine, Irvine, CA 92697, USA.', 'United States|United States|United States|United States|United States', 90, 'Algorithms|Animals|Gene Expression Regulation|Genome, Human|Genome-Wide Association Study|Genomics|Hedgehog Proteins|Humans|Mice|Models, Animal|Nucleotide Motifs|Regulatory Sequences, Nucleic Acid|Signal Transduction|Tumor Suppressor Protein p53', 'Journal Article', '10.1186/1471-2105-12-495', '22208852', 'A central challenge of biology is to map and understand gene regulation on a genome-wide scale. For any given genome, only a small fraction of the regulatory elements embedded in the DNA sequence have been characterized, and there is great interest in developing computational methods to systematically map all these elements and understand their relationships. Such computational efforts, however, are significantly hindered by the overwhelming size of non-coding regions and the statistical variability and complex spatial organizations of regulatory elements and interactions. Genome-wide catalogs of regulatory elements for all model species simply do not yet exist.'),
(94738, 2011, 'bmc', 'A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels', 'Kopriva, Ivica|Filipovixc4x87, Marko', 'Division of Laser and Atomic R&D, Ruxc4x91er Boxc5xa1kovixc4x87 Institute, Bijenixc4x8dka cesta 54, 10000 Zagreb, Croatia. ikopriva@irb.hr|Division of Laser and Atomic R&D, Ruxc4x91er Boxc5xa1kovixc4x87 Institute, Bijenixc4x8dka cesta 54, 10000 Zagreb, Croatia. ikopriva@irb.hr', 'Croatia|Croatia', 0, 'Colonic Neoplasms|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genomics|Humans|Male|Models, Genetic|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Prostatic Neoplasms|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-12-496', '22208882', 'Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue.'),
(94739, 2011, 'bmc', 'Partition decoupling for multi-gene analysis of gene expression profiling data', 'Braun, Rosemary|Leibon, Gregory|Pauls, Scott|Rockmore, Daniel', 'Department of Preventive Medicine and Robert H, Lurie Cancer Center, Northwestern University, Chicago, IL, USA. rosemary.braun@gmail.com|Department of Preventive Medicine and Robert H, Lurie Cancer Center, Northwestern University, Chicago, IL, USA. rosemary.braun@gmail.com|Department of Preventive Medicine and Robert H, Lurie Cancer Center, Northwestern University, Chicago, IL, USA. rosemary.braun@gmail.com|Department of Preventive Medicine and Robert H, Lurie Cancer Center, Northwestern University, Chicago, IL, USA. rosemary.braun@gmail.com', 'United States|United States|United States|United States', 10, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Molecular Sequence Data|Neoplasms|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-12-497', '22208906', 'Multi-gene interactions likely play an important role in the development of complex phenotypes, and relationships between interacting genes pose a challenging statistical problem in microarray analysis, since the genes involved in these interactions may not exhibit marginal differential expression. As a result, it is necessary to develop tools that can identify sets of interacting genes that discriminate phenotypes without requiring that the classification boundary between phenotypes be convex.'),
(94740, 2012, 'bmc', 'GuiTope: an application for mapping random-sequence peptides to protein sequences', 'Halperin, Rebecca F|Stafford, Phillip|Emery, Jack S|Navalkar, Krupa Arun|Johnston, Stephen Albert', 'Center for Innovations in Medicine, The Biodesign Institute at Arizona State University, PO Box 875901, Tempe, AZ 85281, USA.|Center for Innovations in Medicine, The Biodesign Institute at Arizona State University, PO Box 875901, Tempe, AZ 85281, USA.|Center for Innovations in Medicine, The Biodesign Institute at Arizona State University, PO Box 875901, Tempe, AZ 85281, USA.|Center for Innovations in Medicine, The Biodesign Institute at Arizona State University, PO Box 875901, Tempe, AZ 85281, USA.|Center for Innovations in Medicine, The Biodesign Institute at Arizona State University, PO Box 875901, Tempe, AZ 85281, USA.', 'United States|United States|United States|United States|United States', 17, 'Algorithms|Amino Acid Sequence|Ligands|Peptide Library|Peptides|Programming Languages|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-13-1', '22214541', 'Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task.'),
(94741, 2012, 'bmc', 'Self-organizing ontology of biochemically relevant small molecules', 'Chepelev, Leonid L|Hastings, Janna|Ennis, Marcus|Steinbeck, Christoph|Dumontier, Michel', 'Department of Biology, Carleton University, Ottawa, Canada. leonid.chepelev@gmail.com|Department of Biology, Carleton University, Ottawa, Canada. leonid.chepelev@gmail.com|Department of Biology, Carleton University, Ottawa, Canada. leonid.chepelev@gmail.com|Department of Biology, Carleton University, Ottawa, Canada. leonid.chepelev@gmail.com|Department of Biology, Carleton University, Ottawa, Canada. leonid.chepelev@gmail.com', 'Canada|Canada|Canada|Canada|Canada', 0, 'Automation|Databases, Factual|Information Storage and Retrieval|Internet|Medical Subject Headings|Semantics|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-13-3', '22221313', 'The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI) are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest.'),
(94742, 2012, 'bmc', 'ABrowse--a customizable next-generation genome browser framework', 'Kong, Lei|Wang, Jun|Zhao, Shuqi|Gu, Xiaocheng|Luo, Jingchu|Gao, Ge', 'College of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, Peking University, Beijing, 100871, P.R. China.|College of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, Peking University, Beijing, 100871, P.R. China.|College of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, Peking University, Beijing, 100871, P.R. China.|College of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, Peking University, Beijing, 100871, P.R. China.|College of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, Peking University, Beijing, 100871, P.R. China.|College of Life Sciences, State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, Peking University, Beijing, 100871, P.R. China.', 'China|China|China|China|China|China', 10, 'Arabidopsis|Databases, Genetic|Genome|Information Storage and Retrieval|Internet|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-2', '22222089', 'With the rapid growth of genome sequencing projects, genome browser is becoming indispensable, not only as a visualization system but also as an interactive platform to support open data access and collaborative work. Thus a customizable genome browser framework with rich functions and flexible configuration is needed to facilitate various genome research projects.'),
(94743, 2012, 'bmc', 'A comparison study on feature selection of DNA structural properties for promoter prediction', 'Gan, Yanglan|Guan, Jihong|Zhou, Shuigeng', 'Department of Computer Science and Technology, Tongji University, Shanghai, China.|Department of Computer Science and Technology, Tongji University, Shanghai, China.|Department of Computer Science and Technology, Tongji University, Shanghai, China.', 'China|China|China', 20, 'Animals|Base Sequence|DNA|DNA-Directed RNA Polymerases|Genome, Human|Humans|Promoter Regions, Genetic|Sequence Analysis, DNA|Software|Support Vector Machine', 'Comparative Study', '10.1186/1471-2105-13-4', '22226192', 'Promoter prediction is an integrant step for understanding gene regulation and annotating genomes. Traditional promoter analysis is mainly based on sequence compositional features. Recently, many kinds of structural features have been employed in promoter prediction. However, considering the high-dimensionality and overfitting problems, it is unfeasible to utilize all available features for promoter prediction. Thus it is necessary to choose some appropriate features for the prediction task.'),
(94744, 2012, 'bmc', 'proTRAC--a software for probabilistic piRNA cluster detection, visualization and analysis', 'Rosenkranz, David|Zischler, Hans', 'Institute of Anthropology, Johannes Gutenberg-University Mainz, Colonel-Kleinmann-Weg 2, 55099 Mainz, Germany. rosenkrd@uni-mainz.de|Institute of Anthropology, Johannes Gutenberg-University Mainz, Colonel-Kleinmann-Weg 2, 55099 Mainz, Germany. rosenkrd@uni-mainz.de', 'Germany|Germany', 0, 'Animals|DNA Transposable Elements|Gene Library|Genomics|Humans|Mice|RNA Interference|RNA, Small Interfering|Rats|Software', 'Journal Article', '10.1186/1471-2105-13-5', '22233380', 'Throughout the metazoan lineage, typically gonadal expressed Piwi proteins and their guiding piRNAs (~26-32nt in length) form a protective mechanism of RNA interference directed against the propagation of transposable elements (TEs). Most piRNAs are generated from genomic piRNA clusters. Annotation of experimentally obtained piRNAs from small RNA/cDNA-libraries and detection of genomic piRNA clusters are crucial for a thorough understanding of the still enigmatic piRNA pathway, especially in an evolutionary context. Currently, detection of piRNA clusters relies on bioinformatics rather than detection and sequencing of primary piRNA cluster transcripts and the stringency of the methods applied in different studies differs considerably. Additionally, not all important piRNA cluster characteristics were taken into account during bioinformatic processing. Depending on the applied method this can lead to: i) an accidentally underrepresentation of TE related piRNAs, ii) overlook duplicated clusters harboring few or no single-copy loci and iii) false positive annotation of clusters that are in fact just accumulations of multi-copy loci corresponding to frequently mapped reads, but are not transcribed to piRNA precursors.'),
(94745, 2012, 'bmc', 'MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases', 'Kumar, Akhil|Suthers, Patrick F|Maranas, Costas D', 'Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA. costas@psu.edu|Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA. costas@psu.edu|Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA. costas@psu.edu', 'United States|United States|United States', 0, 'Algorithms|Databases, Factual|Humans|Internet|Knowledge Bases|Metabolic Networks and Pathways|Metabolomics|Models, Biological|Software', 'Journal Article', '10.1186/1471-2105-13-6', '22233419', 'Increasingly, metabolite and reaction information is organized in the form of genome-scale metabolic reconstructions that describe the reaction stoichiometry, directionality, and gene to protein to reaction associations. A key bottleneck in the pace of reconstruction of new, high-quality metabolic models is the inability to directly make use of metabolite/reaction information from biological databases or other models due to incompatibilities in content representation (i.e., metabolites with multiple names across databases and models), stoichiometric errors such as elemental or charge imbalances, and incomplete atomistic detail (e.g., use of generic R-group or non-explicit specification of stereo-specificity).'),
(94746, 2012, 'bmc', 'Protein docking prediction using predicted protein-protein interface', 'Li, Bin|Kihara, Daisuke', 'Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA.', 'United States|United States', 40, 'Algorithms|Animals|Binding Sites|Humans|Models, Molecular|Multiprotein Complexes|Protein Binding|Protein Interaction Maps|Proteins|Software', 'Journal Article', '10.1186/1471-2105-13-7', '22233443', 'Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations.'),
(94747, 2012, 'bmc', 'An integrative variant analysis suite for whole exome next-generation sequencing data', 'Challis, Danny|Yu, Jin|Evani, Uday S|Jackson, Andrew R|Paithankar, Sameer|Coarfa, Cristian|Milosavljevic, Aleksandar|Gibbs, Richard A|Yu, Fuli', 'The Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.|The Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.|The Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.|The Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.|The Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.|The Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.|The Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.|The Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.|The Human Genome Sequencing Center, Baylor College of Medicine, Houston, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Exome|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|INDEL Mutation|Open Reading Frames|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1186/1471-2105-13-8', '22239737', 'Whole exome capture sequencing allows researchers to cost-effectively sequence the coding regions of the genome. Although the exome capture sequencing methods have become routine and well established, there is currently a lack of tools specialized for variant calling in this type of data.'),
(94748, 2012, 'bmc', 'MIPHENO: data normalization for high throughput metabolite analysis', 'Bell, Shannon M|Burgoon, Lyle D|Last, Robert L', 'Quantitative Biology Program, Michigan State University, East Lansing, MI, USA.|Quantitative Biology Program, Michigan State University, East Lansing, MI, USA.|Quantitative Biology Program, Michigan State University, East Lansing, MI, USA.', 'United States|United States|United States', 7, 'Arabidopsis|Area Under Curve|Chloroplasts|Chromatography, High Pressure Liquid|Metabolome|Microarray Analysis|Mutation|Phenotype|Plant Proteins|Quality Control', 'Journal Article', '10.1186/1471-2105-13-10', '22244038', 'High throughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course of months and years, often without the controls needed to compare directly across the dataset. Few methods are available to facilitate comparisons of high throughput metabolic data generated in batches where explicit in-group controls for normalization are lacking.'),
(94749, 2012, 'bmc', 'Convergent evolution in structural elements of proteins investigated using cross profile analysis', 'Tomii, Kentaro|Sawada, Yoshito|Honda, Shinya', 'Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto Ward, Tokyo 135-0064, Japan.|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto Ward, Tokyo 135-0064, Japan.|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto Ward, Tokyo 135-0064, Japan.', 'Japan|Japan|Japan', 6, 'Evolution, Molecular|Humans|Models, Molecular|Peptides|Protein Conformation|Protein Folding|Proteins', 'Journal Article', '10.1186/1471-2105-13-11', '22244085', 'Evolutionary relations of similar segments shared by different protein folds remain controversial, even though many examples of such segments have been found. To date, several methods such as those based on the results of structure comparisons, sequence-based classifications, and sequence-based profile-profile comparisons have been applied to identify such protein segments that possess local similarities in both sequence and structure across protein folds. However, to capture more precise sequence-structure relations, no method reported to date combines structure-based profiles, and sequence-based profiles based on evolutionary information. The former are generally regarded as representing the amino acid preferences at each position of a specific conformation of protein segment. They might reflect the nature of ancient short peptide ancestors, using the results of structural classifications of protein segments.'),
(94750, 2012, 'bmc', 'PyElph - a software tool for gel images analysis and phylogenetics', 'Pavel, Ana Brxc3xa2nduxc5x9fa|Vasile, Cristian Ioan', 'Department of Automatic Control and Systems Engineering, Politehnica University of Bucharest, Splaiul Independenxc5xa3ei, No. 313, Bucharest, Romania. anabrandusa@gmail.com|Department of Automatic Control and Systems Engineering, Politehnica University of Bucharest, Splaiul Independenxc5xa3ei, No. 313, Bucharest, Romania. anabrandusa@gmail.com', 'Romania|Romania', 125, 'Amplified Fragment Length Polymorphism Analysis|Computational Biology|Genetic Markers|Image Processing, Computer-Assisted|Phylogeny|Polymorphism, Genetic|Programming Languages|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1186/1471-2105-13-9', '22244131', 'This paper presents PyElph, a software tool which automatically extracts data from gel images, computes the molecular weights of the analyzed molecules or fragments, compares DNA patterns which result from experiments with molecular genetic markers and, also, generates phylogenetic trees computed by five clustering methods, using the information extracted from the analyzed gel image. The software can be successfully used for population genetics, phylogenetics, taxonomic studies and other applications which require gel image analysis. Researchers and students working in molecular biology and genetics would benefit greatly from the proposed software because it is free, open source, easy to use, has a friendly Graphical User Interface and does not depend on specific image acquisition devices like other commercial programs with similar functionalities do.'),
(94751, 2012, 'bmc', 'Core module biomarker identification with network exploration for breast cancer metastasis', 'Yang, Ruoting|Daigle, Bernie J|Petzold, Linda R|Doyle, Francis J', 'Institute for Collaborative Biotechnologies, University of California Santa Barbara, Santa Barbara, CA 93106-5080, USA.|Institute for Collaborative Biotechnologies, University of California Santa Barbara, Santa Barbara, CA 93106-5080, USA.|Institute for Collaborative Biotechnologies, University of California Santa Barbara, Santa Barbara, CA 93106-5080, USA.|Institute for Collaborative Biotechnologies, University of California Santa Barbara, Santa Barbara, CA 93106-5080, USA.', 'United States|United States|United States|United States', 0, 'Biomarkers|Breast Neoplasms|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Genes, Neoplasm|Humans|Protein Interaction Maps', 'Journal Article', '10.1186/1471-2105-13-12', '22257533', 'In a complex disease, the expression of many genes can be significantly altered, leading to the appearance of a differentially expressed disease module. Some of these genes directly correspond to the disease phenotype, (i.e. driver genes), while others represent closely-related first-degree neighbours in gene interaction space. The remaining genes consist of further removed passenger genes, which are often not directly related to the original cause of the disease. For prognostic and diagnostic purposes, it is crucial to be able to separate the group of driver genes and their first-degree neighbours, (i.e. core module) from the general disease module.'),
(94752, 2012, 'bmc', 'TDT-HET: a new transmission disequilibrium test that incorporates locus heterogeneity into the analysis of family-based association data', 'Londono, Douglas|Buyske, Steven|Finch, Stephen J|Sharma, Swarkar|Wise, Carol A|Gordon, Derek', 'Department of Genetics and Human Genetics Institute, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.|Department of Genetics and Human Genetics Institute, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.|Department of Genetics and Human Genetics Institute, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.|Department of Genetics and Human Genetics Institute, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.|Department of Genetics and Human Genetics Institute, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.|Department of Genetics and Human Genetics Institute, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.', 'Jersey|Jersey|Jersey|Jersey|Jersey|Jersey', 6, 'Computer Simulation|Female|Genetic Association Studies|Genetic Heterogeneity|Genome-Wide Association Study|Genotype|Humans|Linkage Disequilibrium|Male|Models, Genetic|Pedigree|Polymorphism, Single Nucleotide|Probability|Scoliosis', 'Journal Article', '10.1186/1471-2105-13-13', '22264315', 'Locus heterogeneity is one of the most documented phenomena in genetics. To date, relatively little work had been done on the development of methods to address locus heterogeneity in genetic association analysis. Motivated by Zhou and Pans work, we present a mixture model of linked and unlinked trios and develop a statistical method to estimate the probability that a heterozygous parent transmits the disease allele at a di-allelic locus, and the probability that any trio is in the linked group. The purpose here is the development of a test that extends the classic transmission disequilibrium test (TDT) to one that accounts for locus heterogeneity.'),
(94753, 2012, 'bmc', 'Developing a powerful in silico tool for the discovery of novel caspase-3 substrates: a preliminary screening of the human proteome', 'Ayyash, Muneef|Tamimi, Hashem|Ashhab, Yaqoub', 'Biotechnology Research Centre, Palestine Polytechnic University, Hebron, Palestine.|Biotechnology Research Centre, Palestine Polytechnic University, Hebron, Palestine.|Biotechnology Research Centre, Palestine Polytechnic University, Hebron, Palestine.', '-|-|-', 0, 'Amino Acid Sequence|Animals|Apoptosis|Caspase 3|Computational Biology|Databases, Genetic|Humans|Mice|Position-Specific Scoring Matrices|Proteins|Proteome|Rats', 'Journal Article', '10.1186/1471-2105-13-14', '22269041', 'Caspases are a family of cysteinyl proteases that regulate apoptosis and other biological processes. Caspase-3 is considered the central executioner member of this family with a wide range of substrates. Identification of caspase-3 cellular targets is crucial to gain further insights into the cellular mechanisms that have been implicated in various diseases including: cancer, neurodegenerative, and immunodeficiency diseases. To date, over 200 caspase-3 substrates have been identified experimentally. However, many are still awaiting discovery.'),
(94754, 2012, 'bmc', 'The EnzymeTracker: an open-source laboratory information management system for sample tracking', 'Triplet, Thomas|Butler, Gregory', 'Department of Computer Science and Software Engineering, Concordia University, 1455 De Maisonneuve Blvd. West, Montreal, Quebec, H3G 1M8, Canada.|Department of Computer Science and Software Engineering, Concordia University, 1455 De Maisonneuve Blvd. West, Montreal, Quebec, H3G 1M8, Canada.', 'Canada|Canada', 8, 'Algorithms|Clinical Laboratory Information Systems|Database Management Systems|Databases, Genetic|Fungi|Information Dissemination|Internet|Management Information Systems|Quality Control|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-15', '22280360', 'In many laboratories, researchers store experimental data on their own workstation using spreadsheets. However, this approach poses a number of problems, ranging from sharing issues to inefficient data-mining. Standard spreadsheets are also error-prone, as data do not undergo any validation process. To overcome spreadsheets inherent limitations, a number of proprietary systems have been developed, which laboratories need to pay expensive license fees for. Those costs are usually prohibitive for most laboratories and prevent scientists from benefiting from more sophisticated data management systems.'),
(94755, 2012, 'bmc', 'Automatic categorization of diverse experimental information in the bioscience literature', 'Fang, Ruihua|Schindelman, Gary|Van Auken, Kimberly|Fernandes, Jolene|Chen, Wen|Wang, Xiaodong|Davis, Paul|Tuli, Mary Ann|Marygold, Steven J|Millburn, Gillian|Matthews, Beverley|Zhang, Haiyan|Brown, Nick|Gelbart, William M|Sternberg, Paul W', 'Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.|Howard Hughes Medical Institute and Biology Division, California Institute of Technology, Pasadena, CA 91125, USA.', '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', 14, 'Animals|Artificial Intelligence|Automation|Caenorhabditis elegans|Databases, Factual|Databases, Genetic|Drosophila melanogaster|Genomics|Mice|Publications|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-13-16', '22280404', 'Curation of information from bioscience literature into biological knowledge databases is a crucial way of capturing experimental information in a computable form. During the biocuration process, a critical first step is to identify from all published literature the papers that contain results for a specific data type the curator is interested in annotating. This step normally requires curators to manually examine many papers to ascertain which few contain information of interest and thus, is usually time consuming. We developed an automatic method for identifying papers containing these curation data types among a large pool of published scientific papers based on the machine learning method Support Vector Machine (SVM). This classification system is completely automatic and can be readily applied to diverse experimental data types. It has been in use in production for automatic categorization of 10 different experimental datatypes in the biocuration process at WormBase for the past two years and it is in the process of being adopted in the biocuration process at FlyBase and the Saccharomyces Genome Database (SGD). We anticipate that this method can be readily adopted by various databases in the biocuration community and thereby greatly reducing time spent on an otherwise laborious and demanding task. We also developed a simple, readily automated procedure to utilize training papers of similar data types from different bodies of literature such as C. elegans and D. melanogaster to identify papers with any of these data types for a single database. This approach has great significance because for some data types, especially those of low occurrence, a single corpus often does not have enough training papers to achieve satisfactory performance.'),
(94756, 2012, 'bmc', 'Training text chunkers on a silver standard corpus: can silver replace gold?', 'Kang, Ning|van Mulligen, Erik M|Kors, Jan A', 'Department of Medical Informatics, Erasmus University Medical Center, P,O, Box 2040, 3000 CA Rotterdam, The Netherlands. n.kang@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center, P,O, Box 2040, 3000 CA Rotterdam, The Netherlands. n.kang@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center, P,O, Box 2040, 3000 CA Rotterdam, The Netherlands. n.kang@erasmusmc.nl', 'Netherlands|Netherlands|Netherlands', 22, 'Computational Biology|Humans|Natural Language Processing|Neoplasms', 'Journal Article', '10.1186/1471-2105-13-17', '22289351', 'To train chunkers in recognizing noun phrases and verb phrases in biomedical text, an annotated corpus is required. The creation of gold standard corpora (GSCs), however, is expensive and time-consuming. GSCs therefore tend to be small and to focus on specific subdomains, which limits their usefulness. We investigated the use of a silver standard corpus (SSC) that is automatically generated by combining the outputs of multiple chunking systems. We explored two use scenarios: one in which chunkers are trained on an SSC in a new domain for which a GSC is not available, and one in which chunkers are trained on an available, although small GSC but supplemented with an SSC.'),
(94757, 2012, 'bmc', 'Propagating semantic information in biochemical network models', 'Schulz, Marvin|Klipp, Edda|Liebermeister, Wolfram', 'Institut für Biologie, Theoretische Biophysik, Humboldt-Universität zu Berlin, Invalidenstr 42, 10115 Berlin, Germany. marvin.schulz@biologie.hu-berlin.de|Institut für Biologie, Theoretische Biophysik, Humboldt-Universität zu Berlin, Invalidenstr 42, 10115 Berlin, Germany. marvin.schulz@biologie.hu-berlin.de|Institut für Biologie, Theoretische Biophysik, Humboldt-Universität zu Berlin, Invalidenstr 42, 10115 Berlin, Germany. marvin.schulz@biologie.hu-berlin.de', 'Germany|Germany|Germany', 8, 'Humans|Models, Biological|Protein Interaction Maps|Semantics|Software|Systems Biology', 'Journal Article', '10.1186/1471-2105-13-18', '22289386', 'To enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation.'),
(94758, 2012, 'bmc', 'TranscriptomeBrowser 30: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks', 'Lepoivre, Cyrille|Bergon, Aurélie|Lopez, Fabrice|Perumal, Narayanan B|Nguyen, Catherine|Imbert, Jean|Puthier, Denis', 'TAGC UMR_S 928, Inserm, Parc Scientifique de Luminy, Marseille, France.|TAGC UMR_S 928, Inserm, Parc Scientifique de Luminy, Marseille, France.|TAGC UMR_S 928, Inserm, Parc Scientifique de Luminy, Marseille, France.|TAGC UMR_S 928, Inserm, Parc Scientifique de Luminy, Marseille, France.|TAGC UMR_S 928, Inserm, Parc Scientifique de Luminy, Marseille, France.|TAGC UMR_S 928, Inserm, Parc Scientifique de Luminy, Marseille, France.|TAGC UMR_S 928, Inserm, Parc Scientifique de Luminy, Marseille, France.', 'France|France|France|France|France|France|France', 15, 'Animals|Cell Differentiation|Databases, Genetic|Dogs|Gene Expression Profiling|Gene Regulatory Networks|Genomics|Humans|Mice|Oligonucleotide Array Sequence Analysis|Proteins|Rats|Software|Thymocytes|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-19', '22292669', 'Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph.'),
(94759, 2012, 'bmc', 'graphite - a Bioconductor package to convert pathway topology to gene network', 'Sales, Gabriele|Calura, Enrica|Cavalieri, Duccio|Romualdi, Chiara', 'Department of Biology, University of Padova, via U, Bassi 58/B, Padova, Italy.|Department of Biology, University of Padova, via U, Bassi 58/B, Padova, Italy.|Department of Biology, University of Padova, via U, Bassi 58/B, Padova, Italy.|Department of Biology, University of Padova, via U, Bassi 58/B, Padova, Italy.', 'Italy|Italy|Italy|Italy', 90, 'Gene Regulatory Networks|Humans|Insulin|Oligonucleotide Array Sequence Analysis|Receptor, Notch1|Signal Transduction|Software', 'Journal Article', '10.1186/1471-2105-13-20', '22292714', 'Gene set analysis is moving towards considering pathway topology as a crucial feature. Pathway elements are complex entities such as protein complexes, gene family members and chemical compounds. The conversion of pathway topology to a gene/protein networks (where nodes are a simple element like a gene/protein) is a critical and challenging task that enables topology-based gene set analyses.Unfortunately, currently available R/Bioconductor packages provide pathway networks only from single databases. They do not propagate signals through chemical compounds and do not differentiate between complexes and gene families.'),
(94760, 2012, 'bmc', 'Fast automatic quantitative cell replication with fluorescent live cell imaging', 'Wang, Ching-Wei', 'Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. cweiwang@mail.ntust.edu.tw', '-', 6, 'Cell Proliferation|Color|Entropy|Humans|Immunohistochemistry|Microscopy, Fluorescence|Neoplasms', 'Journal Article', '10.1186/1471-2105-13-21', '22292799', 'live cell imaging is a useful tool to monitor cellular activities in living systems. It is often necessary in cancer research or experimental research to quantify the dividing capabilities of cells or the cell proliferation level when investigating manipulations of the cells or their environment. Manual quantification of fluorescence microscopic image is difficult because human is neither sensitive to fine differences in color intensity nor effective to count and average fluorescence level among cells. However, auto-quantification is not a straightforward problem to solve. As the sampling location of the microscopy changes, the amount of cells in individual microscopic images varies, which makes simple measurement methods such as the sum of stain intensity values or the total number of positive stain within each image inapplicable. Thus, automated quantification with robust cell segmentation techniques is required.'),
(94761, 2012, 'bmc', 'Analysis of energy-based algorithms for RNA secondary structure prediction', 'Hajiaghayi, Monir|Condon, Anne|Hoos, Holger H', 'Computer Science Department, University of British Columbia, Vancouver, BC, Canada. monirh@cs.ubc.ca|Computer Science Department, University of British Columbia, Vancouver, BC, Canada. monirh@cs.ubc.ca|Computer Science Department, University of British Columbia, Vancouver, BC, Canada. monirh@cs.ubc.ca', 'Canada|Canada|Canada', 21, 'Algorithms|Nucleic Acid Conformation|Predictive Value of Tests|RNA|Ribonuclease P|Thermodynamics', 'Journal Article', '10.1186/1471-2105-13-22', '22296803', 'RNA molecules play critical roles in the cells of organisms, including roles in gene regulation, catalysis, and synthesis of proteins. Since RNA function depends in large part on its folded structures, much effort has been invested in developing accurate methods for prediction of RNA secondary structure from the base sequence. Minimum free energy (MFE) predictions are widely used, based on nearest neighbor thermodynamic parameters of Mathews, Turner et al. or those of Andronescu et al. Some recently proposed alternatives that leverage partition function calculations find the structure with maximum expected accuracy (MEA) or pseudo-expected accuracy (pseudo-MEA) methods. Advances in prediction methods are typically benchmarked using sensitivity, positive predictive value and their harmonic mean, namely F-measure, on datasets of known reference structures. Since such benchmarks document progress in improving accuracy of computational prediction methods, it is important to understand how measures of accuracy vary as a function of the reference datasets and whether advances in algorithms or thermodynamic parameters yield statistically significant improvements. Our work advances such understanding for the MFE and (pseudo-)MEA-based methods, with respect to the latest datasets and energy parameters.'),
(94762, 2012, 'bmc', 'Markov Chain Ontology Analysis (MCOA)', 'Frost, H Robert|McCray, Alexa T', 'Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA. rob_frost@hms.harvard.edu|Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA. rob_frost@hms.harvard.edu', 'United States|United States', 10, 'Animals|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Humans|Markov Chains|Molecular Sequence Annotation|Parkinson Disease|Probability|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-13-23', '22300537', 'Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data.'),
(94763, 2012, 'bmc', 'Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets', 'Yao, Fangzhou|Coquery, Jeff|Lê Cao, Kim-Anh', 'Queensland Facility for Advanced Bioinformatics, University of Queensland, St Lucia, Australia.|Queensland Facility for Advanced Bioinformatics, University of Queensland, St Lucia, Australia.|Queensland Facility for Advanced Bioinformatics, University of Queensland, St Lucia, Australia.', 'Australia|Australia|Australia', 67, 'Acetaminophen|Algorithms|Animals|Artifacts|Cluster Analysis|Computational Biology|Humans|Male|Principal Component Analysis|Prostatic Neoplasms|Rats|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-13-24', '22305354', 'A key question when analyzing high throughput data is whether the information provided by the measured biological entities (gene, metabolite expression for example) is related to the experimental conditions, or, rather, to some interfering signals, such as experimental bias or artefacts. Visualization tools are therefore useful to better understand the underlying structure of the data in a blind (unsupervised) way. A well-established technique to do so is Principal Component Analysis (PCA). PCA is particularly powerful if the biological question is related to the highest variance. Independent Component Analysis (ICA) has been proposed as an alternative to PCA as it optimizes an independence condition to give more meaningful components. However, neither PCA nor ICA can overcome both the high dimensionality and noisy characteristics of biological data.'),
(94764, 2012, 'bmc', 'Predicting tissue specific cis-regulatory modules in the human genome using pairs of co-occurring motifs', 'Girgis, Hani Z|Ovcharenko, Ivan', 'Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health 9600 Rockville Pike, Bethesda, MD 20896, USA.|Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health 9600 Rockville Pike, Bethesda, MD 20896, USA.', 'United States|United States', 11, 'Algorithms|Bayes Theorem|CD4-Positive T-Lymphocytes|Gene Expression Regulation|Genome, Human|Humans|Myocardium|Organ Specificity|Regulatory Elements, Transcriptional|Regulatory Sequences, Nucleic Acid|Signal-To-Noise Ratio|Software|Transcription Factors', 'Journal Article', '10.1186/1471-2105-13-25', '22313678', 'Researchers seeking to unlock the genetic basis of human physiology and diseases have been studying gene transcription regulation. The temporal and spatial patterns of gene expression are controlled by mainly non-coding elements known as cis-regulatory modules (CRMs) and epigenetic factors. CRMs modulating related genes share the regulatory signature which consists of transcription factor (TF) binding sites (TFBSs). Identifying such CRMs is a challenging problem due to the prohibitive number of sequence sets that need to be analyzed.'),
(94765, 2012, 'bmc', 'Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data', 'Viswanath, Satish|Madabhushi, Anant', 'Dept. of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, New Jersey 08854, USA. satish@eden.rutgers.edu|Dept. of Biomedical Engineering, Rutgers University, 599 Taylor Road, Piscataway, New Jersey 08854, USA. satish@eden.rutgers.edu', 'Jersey|Jersey', 8, 'Algorithms|Brain|Humans|Magnetic Resonance Imaging|Male|Pattern Recognition, Automated|Principal Component Analysis|Prostatic Neoplasms|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-13-26', '22316103', 'Dimensionality reduction (DR) enables the construction of a lower dimensional space (embedding) from a higher dimensional feature space while preserving object-class discriminability. However several popular DR approaches suffer from sensitivity to choice of parameters and/or presence of noise in the data. In this paper, we present a novel DR technique known as consensus embedding that aims to overcome these problems by generating and combining multiple low-dimensional embeddings, hence exploiting the variance among them in a manner similar to ensemble classifier schemes such as Bagging. We demonstrate theoretical properties of consensus embedding which show that it will result in a single stable embedding solution that preserves information more accurately as compared to any individual embedding (generated via DR schemes such as Principal Component Analysis, Graph Embedding, or Locally Linear Embedding). Intelligent sub-sampling (via mean-shift) and code parallelization are utilized to provide for an efficient implementation of the scheme.'),
(94766, 2012, 'bmc', 'Model-based peak alignment of metabolomic profiling from comprehensive two-dimensional gas chromatography mass spectrometry', 'Jeong, Jaesik|Shi, Xue|Zhang, Xiang|Kim, Seongho|Shen, Changyu', 'Department of Biostatistics, Indiana University, Indianapolis, IN 46202, USA.|Department of Biostatistics, Indiana University, Indianapolis, IN 46202, USA.|Department of Biostatistics, Indiana University, Indianapolis, IN 46202, USA.|Department of Biostatistics, Indiana University, Indianapolis, IN 46202, USA.|Department of Biostatistics, Indiana University, Indianapolis, IN 46202, USA.', 'India|India|India|India|India', 17, 'Algorithms|Animals|Bayes Theorem|Gas Chromatography-Mass Spectrometry|Metabolomics|Models, Theoretical|Plasma|Programming Languages|Rats|Software', 'Journal Article', '10.1186/1471-2105-13-27', '22316124', 'Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GCxGC/TOF-MS) has been used for metabolite profiling in metabolomics. However, there is still much experimental variation to be controlled including both within-experiment and between-experiment variation. For efficient analysis, an ideal peak alignment method to deal with such variations is in great need.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94767, 2012, 'bmc', 'Identification of polymorphic inversions from genotypes', 'Cáceres, Alejandro|Sindi, Suzanne S|Raphael, Benjamin J|Cáceres, Mario|González, Juan R', 'Center for Research in Environmental Epidemiology, and Institut Municipal dInvestigació Mèdica, Barcelona 08003, Spain. acaceres@creal.cat|Center for Research in Environmental Epidemiology, and Institut Municipal dInvestigació Mèdica, Barcelona 08003, Spain. acaceres@creal.cat|Center for Research in Environmental Epidemiology, and Institut Municipal dInvestigació Mèdica, Barcelona 08003, Spain. acaceres@creal.cat|Center for Research in Environmental Epidemiology, and Institut Municipal dInvestigació Mèdica, Barcelona 08003, Spain. acaceres@creal.cat|Center for Research in Environmental Epidemiology, and Institut Municipal dInvestigació Mèdica, Barcelona 08003, Spain. acaceres@creal.cat', 'Spain|Spain|Spain|Spain|Spain', 27, 'Chromosome Inversion|Chromosomes, Human, Pair 17|Genetics, Population|Genome-Wide Association Study|HapMap Project|Humans|Linkage Disequilibrium|Models, Genetic|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-13-28', '22321652', 'Polymorphic inversions are a source of genetic variability with a direct impact on recombination frequencies. Given the difficulty of their experimental study, computational methods have been developed to infer their existence in a large number of individuals using genome-wide data of nucleotide variation. Methods based on haplotype tagging of known inversions attempt to classify individuals as having a normal or inverted allele. Other methods that measure differences between linkage disequilibrium attempt to identify regions with inversions but unable to classify subjects accurately, an essential requirement for association studies.'),
(94768, 2012, 'bmc', 'Method: automatic segmentation of mitochondria utilizing patch classification, contour pair classification, and automatically seeded level sets', 'Giuly, Richard J|Martone, Maryann E|Ellisman, Mark H', 'Center for Research in Biological Systems, University of California, 9500 Gilman Dr., La Jolla, CA 92093, USA. rgiuly@gmail.com|Center for Research in Biological Systems, University of California, 9500 Gilman Dr., La Jolla, CA 92093, USA. rgiuly@gmail.com|Center for Research in Biological Systems, University of California, 9500 Gilman Dr., La Jolla, CA 92093, USA. rgiuly@gmail.com', 'United States|United States|United States', 0, 'Algorithms|Image Processing, Computer-Assisted|Microscopy, Electron|Mitochondria', 'Journal Article', '10.1186/1471-2105-13-29', '22321695', 'While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps.'),
(94769, 2012, 'bmc', 'ICGE: an R package for detecting relevant clusters and atypical units in gene expression', 'Irigoien, Itziar|Sierra, Basilio|Arenas, Concepcion', 'Department of Computation Science and Artificial Intelligence, University of the Basque Country, Donostia, Spain.|Department of Computation Science and Artificial Intelligence, University of the Basque Country, Donostia, Spain.|Department of Computation Science and Artificial Intelligence, University of the Basque Country, Donostia, Spain.', 'Spain|Spain|Spain', 0, 'Algorithms|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Humans|Lymphoproliferative Disorders|Neoplasms|Software', 'Journal Article', '10.1186/1471-2105-13-30', '22330431', 'Gene expression technologies have opened up new ways to diagnose and treat cancer and other diseases. Clustering algorithms are a useful approach with which to analyze genome expression data. They attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. An important problem associated with gene classification is to discern whether the clustering process can find a relevant partition as well as the identification of new genes classes. There are two key aspects to classification: the estimation of the number of clusters, and the decision as to whether a new unit (gene, tumor sample...) belongs to one of these previously identified clusters or to a new group.'),
(94770, 2012, 'bmc', 'PANDAseq: paired-end assembler for illumina sequences', 'Masella, Andre P|Bartram, Andrea K|Truszkowski, Jakub M|Brown, Daniel G|Neufeld, Josh D', 'Department of Biology, University of Waterloo, Waterloo, Ontario, Canada.|Department of Biology, University of Waterloo, Waterloo, Ontario, Canada.|Department of Biology, University of Waterloo, Waterloo, Ontario, Canada.|Department of Biology, University of Waterloo, Waterloo, Ontario, Canada.|Department of Biology, University of Waterloo, Waterloo, Ontario, Canada.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Bacteria|Metagenomics|RNA, Bacterial|RNA, Ribosomal, 16S|Software', 'Journal Article', '10.1186/1471-2105-13-31', '22333067', 'Illumina paired-end reads are used to analyse microbial communities by targeting amplicons of the 16S rRNA gene. Publicly available tools are needed to assemble overlapping paired-end reads while correcting mismatches and uncalled bases, many errors could be corrected to obtain higher sequence yields using quality information.'),
(94771, 2012, 'bmc', 'CodingMotif: exact determination of overrepresented nucleotide motifs in coding sequences', 'Ding, Yang|Lorenz, William A|Chuang, Jeffrey H', 'Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.', 'United States|United States|United States', 0, 'Algorithms|Chromatin Immunoprecipitation|Codon|DNA|Genomics|Humans|Nucleotide Motifs|Open Reading Frames|RNA|Software|Transcription Factors|Untranslated Regions', 'Journal Article', '10.1186/1471-2105-13-32', '22333114', 'It has been increasingly appreciated that coding sequences harbor regulatory sequence motifs in addition to encoding for protein. These sequence motifs are expected to be overrepresented in nucleotide sequences bound by a common protein or small RNA. However, detecting overrepresented motifs has been difficult because of interference by constraints at the protein level. Sampling-based approaches to solve this problem based on codon-shuffling have been limited to exploring only an infinitesimal fraction of the sequence space and by their use of parametric approximations.'),
(94772, 2012, 'bmc', 'BLANNOTATOR: enhanced homology-based function prediction of bacterial proteins', 'Kankainen, Matti|Ojala, Teija|Holm, Liisa', 'Institute of Biotechnology, University of Helsinki, Helsinki, Finland. matti.kankainen@helsinki.fi|Institute of Biotechnology, University of Helsinki, Helsinki, Finland. matti.kankainen@helsinki.fi|Institute of Biotechnology, University of Helsinki, Helsinki, Finland. matti.kankainen@helsinki.fi', 'Finland|Finland|Finland', 10, 'Bacteria|Bacterial Proteins|Computational Biology|Databases, Protein|Lactobacillus|Sequence Homology, Amino Acid', 'Journal Article', '10.1186/1471-2105-13-33', '22335941', 'Automated function prediction has played a central role in determining the biological functions of bacterial proteins. Typically, protein function annotation relies on homology, and function is inferred from other proteins with similar sequences. This approach has become popular in bacterial genomics because it is one of the few methods that is practical for large datasets and because it does not require additional functional genomics experiments. However, the existing solutions produce erroneous predictions in many cases, especially when query sequences have low levels of identity with the annotated source protein. This problem has created a pressing need for improvements in homology-based annotation.'),
(94773, 2012, 'bmc', 'PPINGUIN: Peptide Profiling Guided Identification of Proteins improves quantitation of iTRAQ ratios', 'Bauer, Chris|Kleinjung, Frank|Rutishauser, Dorothea|Panse, Christian|Chadt, Alexandra|Dreja, Tanja|Al-Hasani, Hadi|Reinert, Knut|Schlapbach, Ralph|Schuchhardt, Johannes', 'MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 4, 'Animals|Cluster Analysis|Diabetes Mellitus, Type 2|Gene Expression Profiling|Mice|Mice, Obese|Obesity|Peptides|Proteins|Proteomics|Reproducibility of Results|Ribosomal Proteins', 'Journal Article', '10.1186/1471-2105-13-34', '22340093', 'Recent development of novel technologies paved the way for quantitative proteomics. One of the most important among them is iTRAQ, employing isobaric tags for relative or absolute quantitation. Despite large progress in technology development, still many challenges remain for derivation and interpretation of quantitative results. One of these challenges is the consistent assignment of peptides to proteins.'),
(94774, 2012, 'bmc', 'Assessing statistical significance in causal graphs', 'Chindelevitch, Leonid|Loh, Po-Ru|Enayetallah, Ahmed|Berger, Bonnie|Ziemek, Daniel', 'Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA, USA.|Computational Sciences Center of Emphasis, Pfizer Worldwide Research & Development, Cambridge, MA, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Chondrocytes|Dexamethasone|Gene Expression Profiling|Hypoxia|Mice|Models, Biological|Oligonucleotide Array Sequence Analysis|Receptors, Glucocorticoid|Statistical Distributions', 'Journal Article', '10.1186/1471-2105-13-35', '22348444', 'Causal graphs are an increasingly popular tool for the analysis of biological datasets. In particular, signed causal graphs--directed graphs whose edges additionally have a sign denoting upregulation or downregulation--can be used to model regulatory networks within a cell. Such models allow prediction of downstream effects of regulation of biological entities, conversely, they also enable inference of causative agents behind observed expression changes. However, due to their complex nature, signed causal graph models present special challenges with respect to assessing statistical significance. In this paper we frame and solve two fundamental computational problems that arise in practice when computing appropriate null distributions for hypothesis testing.'),
(94775, 2012, 'bmc', 'miRTrail--a comprehensive webserver for analyzing gene and miRNA patterns to enhance the understanding of regulatory mechanisms in diseases', 'Laczny, Cedric|Leidinger, Petra|Haas, Jan|Ludwig, Nicole|Backes, Christina|Gerasch, Andreas|Kaufmann, Michael|Vogel, Britta|Katus, Hugo A|Meder, Benjamin|Stähler, Cord|Meese, Eckart|Lenhof, Hans-Peter|Keller, Andreas', 'Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.|Center for Bioinformatics, Saarland University, Campus E2 1, 66041 Saarbrücken, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 0, 'Animals|Computers|Gene Expression Regulation|Humans|Internet|Melanoma|Mice|MicroRNAs|RNA, Messenger|Skin Neoplasms|Transcriptome|Zebrafish', 'Journal Article', '10.1186/1471-2105-13-36', '22356618', 'Expression profiling provides new insights into regulatory and metabolic processes and in particular into pathogenic mechanisms associated with diseases. Besides genes, non-coding transcripts as microRNAs (miRNAs) gained increasing relevance in the last decade. To understand the regulatory processes of miRNAs on genes, integrative computer-aided approaches are essential, especially in the light of complex human diseases as cancer.'),
(94776, 2011, 'bmc', 'Towards big data science in the decade ahead from ten years of InCoB and the 1st ISCB-Asia Joint Conference', 'Ranganathan, Shoba|Schönbach, Christian|Kelso, Janet|Rost, Burkhard|Nathan, Sheila|Tan, Tin Wee', 'Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia. shoba.ranganathan@mq.edu.au|Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia. shoba.ranganathan@mq.edu.au|Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia. shoba.ranganathan@mq.edu.au|Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia. shoba.ranganathan@mq.edu.au|Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia. shoba.ranganathan@mq.edu.au|Department of Chemistry and Biomolecular Sciences and ARC Centre of Excellence in Bioinformatics, Macquarie University, Sydney NSW 2109, Australia. shoba.ranganathan@mq.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia', 17, 'Asia|Computational Biology|Genome, Human|Genomics|Humans|Software|Systems Biology', 'Introductory Journal Article', '10.1186/1471-2105-12-S13-S1', '22372736', 'The 2011 International Conference on Bioinformatics (InCoB) conference, which is the annual scientific conference of the Asia-Pacific Bioinformatics Network (APBioNet), is hosted by Kuala Lumpur, Malaysia, is co-organized with the first ISCB-Asia conference of the International Society for Computational Biology (ISCB). InCoB and the sequencing of the human genome are both celebrating their tenth anniversaries and InCoBs goalposts for the next decade, implementing standards in bioinformatics and globally distributed computational networks, will be discussed and adopted at this conference. Of the 49 manuscripts (selected from 104 submissions) accepted to BMC Genomics and BMC Bioinformatics conference supplements, 24 are featured in this issue, covering software tools, genome/proteome analysis, systems biology (networks, pathways, bioimaging) and drug discovery and design.'),
(94777, 2011, 'bmc', 'Investigation and identification of protein xcexb3-glutamyl carboxylation sites', 'Lee, Tzong-Yi|Lu, Cheng-Tsung|Chen, Shu-An|Bretaxc3xb1a, Neil Arvin|Cheng, Tzu-Hsiu|Su, Min-Gang|Huang, Kai-Yao', 'Department of Computer Science and Engineering, Yuan Ze University, Chung-Li 320, Taiwan. francis@saturn.yzu.edu.tw|Department of Computer Science and Engineering, Yuan Ze University, Chung-Li 320, Taiwan. francis@saturn.yzu.edu.tw|Department of Computer Science and Engineering, Yuan Ze University, Chung-Li 320, Taiwan. francis@saturn.yzu.edu.tw|Department of Computer Science and Engineering, Yuan Ze University, Chung-Li 320, Taiwan. francis@saturn.yzu.edu.tw|Department of Computer Science and Engineering, Yuan Ze University, Chung-Li 320, Taiwan. francis@saturn.yzu.edu.tw|Department of Computer Science and Engineering, Yuan Ze University, Chung-Li 320, Taiwan. francis@saturn.yzu.edu.tw|Department of Computer Science and Engineering, Yuan Ze University, Chung-Li 320, Taiwan. francis@saturn.yzu.edu.tw', '-|-|-|-|-|-|-', 0, '1-Carboxyglutamic Acid|Humans|Protein Processing, Post-Translational|Proteins|Substrate Specificity|Support Vector Machine|Vitamin K', 'Journal Article', '10.1186/1471-2105-12-S13-S10', '22372765', 'Carboxylation is a modification of glutamate (Glu) residues which occurs post-translation that is catalyzed by xcexb3-glutamyl carboxylase in the lumen of the endoplasmic reticulum. Vitamin K is a critical co-factor in the post-translational conversion of Glu residues to xcexb3-carboxyglutamate (Gla) residues. It has been shown that the process of carboxylation is involved in the blood clotting cascade, bone growth, and extraosseous calcification. However, studies in this field have been limited by the difficulty of experimentally studying substrate site specificity in xcexb3-glutamyl carboxylation. In silico investigations have the potential for characterizing carboxylated sites before experiments are carried out.'),
(94778, 2011, 'bmc', 'Revealing the functionality of hypothetical protein KPN00728 from Klebsiella pneumoniae MGH78578: molecular dynamics simulation approaches', 'Choi, Sy Bing|Normi, Yahaya M|Wahab, Habibah A', 'Pharmaceutical Design and Simulation Laboratory, School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Minden, Pulau Pinang, Malaysia.|Pharmaceutical Design and Simulation Laboratory, School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Minden, Pulau Pinang, Malaysia.|Pharmaceutical Design and Simulation Laboratory, School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 Minden, Pulau Pinang, Malaysia.', 'Malaysia|Malaysia|Malaysia', 0, 'Bacterial Proteins|Hydrogen Bonding|Klebsiella pneumoniae|Molecular Dynamics Simulation|Succinate Dehydrogenase|Ubiquinone', 'Journal Article', '10.1186/1471-2105-12-S13-S11', '22372825', 'Previously, the hypothetical protein, KPN00728 from Klebsiella pneumoniae MGH78578 was the Succinate dehydrogenase (SDH) chain C subunit via structural prediction and molecular docking simulation studies. However, due to limitation in docking simulation, an in-depth understanding of how SDH interaction occurs across the transmembrane of mitochondria could not be provided.'),
(94779, 2011, 'bmc', 'Assessment of predictive models for chlorophyll-a concentration of a tropical lake', 'Malek, Sorayya|Syed Ahmad, Sharifah Mumtazah|Singh, Sarinder Kaur Kashmir|Milow, Pozi|Salleh, Aishah', 'Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia. sorayya@um.edu.my|Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia. sorayya@um.edu.my|Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia. sorayya@um.edu.my|Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia. sorayya@um.edu.my|Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia. sorayya@um.edu.my', 'Malaysia|Malaysia|Malaysia|Malaysia|Malaysia', 14, 'Chlorophyll|Ecosystem|Eutrophication|Lakes|Linear Models|Malaysia|Models, Biological|Neural Networks (Computer)|Nitrogen', 'Journal Article', '10.1186/1471-2105-12-S13-S12', '22372859', 'This study assesses four predictive ecological models, Fuzzy Logic (FL), Recurrent Artificial Neural Network (RANN), Hybrid Evolutionary Algorithm (HEA) and multiple linear regressions (MLR) to forecast chlorophyll- a concentration using limnological data from 2001 through 2004 of unstratified shallow, oligotrophic to mesotrophic tropical Putrajaya Lake (Malaysia). Performances of the models are assessed using Root Mean Square Error (RMSE), correlation coefficient (r), and Area under the Receiving Operating Characteristic (ROC) curve (AUC). Chlorophyll-a have been used to estimate algal biomass in aquatic ecosystem as it is common in most algae. Algal biomass indicates of the trophic status of a water body. Chlorophyll- a therefore, is an effective indicator for monitoring eutrophication which is a common problem of lakes and reservoirs all over the world. Assessments of these predictive models are necessary towards developing a reliable algorithm to estimate chlorophyll- a concentration for eutrophication management of tropical lakes.'),
(94780, 2011, 'bmc', 'Near-membrane ensemble elongation in the proline-rich LRP6 intracellular domain may explain the mysterious initiation of the Wnt signaling pathway', 'Liu, Chengcheng|Yao, Mingxi|Hogue, Christopher W V', 'Computation and Systems Biology Programme, Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore.|Computation and Systems Biology Programme, Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore.|Computation and Systems Biology Programme, Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore.', 'Singapore|Singapore|Singapore', 0, 'Glycogen Synthase Kinase 3|Humans|Low Density Lipoprotein Receptor-Related Protein-6|Phosphorylation|Protein Folding|Protein Structure, Tertiary|Signal Transduction|Wnt Signaling Pathway|beta Catenin', 'Journal Article', '10.1186/1471-2105-12-S13-S13', '22372892', 'LRP6 is a membrane protein crucial in the initiation of canonical Wnt/xcexb2-catenin signalling. Its function is dependent on its proline-serine rich intracellular domain. LRP6 has five PPP(S/T)P motifs that are phosphorylated during activation, starting with the site closest to the membrane. Like all long proline rich regions, there is no stable 3D structure for this isolated, contiguous region.'),
(94781, 2011, 'bmc', 'Cell cycle phase classification in 3D in vivo microscopy of Drosophila embryogenesis', 'Du, Tie Hua|Puah, Wee Choo|Wasser, Martin', 'Imaging Informatics Division, Live-Cell Imaging and Automation of Image Analysis Group Bioinformatics Institute, Agency for Science, Technology and Research, Singapore.|Imaging Informatics Division, Live-Cell Imaging and Automation of Image Analysis Group Bioinformatics Institute, Agency for Science, Technology and Research, Singapore.|Imaging Informatics Division, Live-Cell Imaging and Automation of Image Analysis Group Bioinformatics Institute, Agency for Science, Technology and Research, Singapore.', 'Singapore|Singapore|Singapore', 10, 'Animals|Cell Cycle|Cell Nucleus|Chromatin|Drosophila|Embryonic Development|Imaging, Three-Dimensional|Microscopy, Confocal|Microscopy, Fluorescence|Neural Networks (Computer)|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-12-S13-S18', '22372955', 'Cell divisions play critical roles in disease and development. The analysis of cell division phenotypes in high content image-based screening and time-lapse microscopy relies on automated nuclear segmentation and classification of cell cycle phases. Automated identification of the cell cycle phase helps biologists quantify the effect of genetic perturbations and drug treatments. Most existing studies have dealt with 2D images of cultured cells. Few, if any, studies have addressed the problem of cell cycle classification in 3D image stacks of intact tissues.'),
(94782, 2011, 'bmc', 'Finding consistent disease subnetworks across microarray datasets', 'Soh, Donny|Dong, Difeng|Guo, Yike|Wong, Limsoon', 'National University of Singapore, 13 Computing Drive, Singapore 117417. donnysoh@gmail.com|National University of Singapore, 13 Computing Drive, Singapore 117417. donnysoh@gmail.com|National University of Singapore, 13 Computing Drive, Singapore 117417. donnysoh@gmail.com|National University of Singapore, 13 Computing Drive, Singapore 117417. donnysoh@gmail.com', 'Singapore|Singapore|Singapore|Singapore', 0, 'Algorithms|Gene Expression Profiling|Gene Regulatory Networks|Humans|Lung Neoplasms|Muscular Dystrophy, Duchenne|Oligonucleotide Array Sequence Analysis|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-12-S13-S15', '22372958', 'While contemporary methods of microarray analysis are excellent tools for studying individual microarray datasets, they have a tendency to produce different results from different datasets of the same disease. We aim to solve this reproducibility problem by introducing a technique (SNet). SNet provides both quantitative and descriptive analysis of microarray datasets by identifying specific connected portions of pathways that are significant. We term such portions within pathways as subnetworks.'),
(94783, 2011, 'bmc', 'Development, evaluation and application of 3D QSAR Pharmacophore model in the discovery of potential human renin inhibitors', 'John, Shalini|Thangapandian, Sundarapandian|Arooj, Mahreen|Hong, Jong Chan|Kim, Kwang Dong|Lee, Keun Woo', 'Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.', '-|-|-|-|-|-', 0, 'Antihypertensive Agents|Drug Discovery|Humans|Hydrophobic and Hydrophilic Interactions|Ligands|Molecular Docking Simulation|Protease Inhibitors|Quantitative Structure-Activity Relationship|Renin|Renin-Angiotensin System', 'Journal Article', '10.1186/1471-2105-12-S14-S4', '22372967', 'Renin has become an attractive target in controlling hypertension because of the high specificity towards its only substrate, angiotensinogen. The conversion of angiotensinogen to angiotensin I is the first and rate-limiting step of renin-angiotensin system and thus designing inhibitors to block this step is focused in this study.'),
(94784, 2012, 'bmc', 'Transparent mediation-based access to multiple yeast data sources using an ontology driven interface', 'Briache, Abdelaali|Marrakchi, Kamar|Kerzazi, Amine|Navas-Delgado, Ismael|Rossi Hassani, Badr D|Lairini, Khalid|Aldana-Montes, José F', 'Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.|Division of Applied Life Science (BK21 Program), Systems and Synthetic Agrobiotech Center, Research Institute of Natural Science, Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, 501 Jinju-daero, Gazha-dong, Jinju 660-701, Republic of Korea.', '-|-|-|-|-|-|-', 2, 'Biological Ontologies|Computational Biology|Data Mining|Databases, Factual|Internet|Saccharomyces cerevisiae|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-S1-S7', '22372975', 'Saccharomyces cerevisiae is recognized as a model system representing a simple eukaryote whose genome can be easily manipulated. Information solicited by scientists on its biological entities (Proteins, Genes, RNAs...) is scattered within several data sources like SGD, Yeastract, CYGD-MIPS, BioGrid, PhosphoGrid, etc. Because of the heterogeneity of these sources, querying them separately and then manually combining the returned results is a complex and time-consuming task for biologists most of whom are not bioinformatics expert. It also reduces and limits the use that can be made on the available data.'),
(94785, 2011, 'bmc', 'A quantitative analysis of monochromaticity in genetic interaction networks', 'Hsu, Chien-Hsiang|Wang, Tse-Yi|Chu, Hsueh-Ting|Kao, Cheng-Yan|Chen, Kuang-Chi', 'Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.|Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.|Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.|Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.|Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.', '-|-|-|-|-', 6, 'Computational Biology|Epistasis, Genetic|Metabolic Networks and Pathways|Multiprotein Complexes|Phenotype|Protein Biosynthesis|Saccharomyces cerevisiae|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-12-S13-S16', '22372977', 'A genetic interaction refers to the deviation of phenotypes from the expected when perturbing two genes simultaneously. Studying genetic interactions help clarify relationships between genes, such as compensation and masking, and identify gene groups of functional modules. Recently, several genome-scale experiments for measuring quantitative (positive and negative) genetic interactions have been conducted. The results revealed that genes in the same module usually interact with each other in a consistent way (pure positive or negative), this phenomenon was designated as monochromaticity. Monochromaticity might be the underlying principle that can be utilized to unveil the modularity of cellular networks. However, no appropriate quantitative measurement for this phenomenon has been proposed.'),
(94786, 2011, 'bmc', 'Correlation of cell membrane dynamics and cell motility', 'Veronika, Merlin|Welsch, Roy|Ng, Alvin|Matsudaira, Paul|Rajapakse, Jagath C', 'Computation and Systems Biology, Singapore-MIT Alliance, Nanyang Technological University, Singapore 637460.|Computation and Systems Biology, Singapore-MIT Alliance, Nanyang Technological University, Singapore 637460.|Computation and Systems Biology, Singapore-MIT Alliance, Nanyang Technological University, Singapore 637460.|Computation and Systems Biology, Singapore-MIT Alliance, Nanyang Technological University, Singapore 637460.|Computation and Systems Biology, Singapore-MIT Alliance, Nanyang Technological University, Singapore 637460.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Actins|Animals|Cell Line|Cell Membrane|Cell Movement|Cytoskeleton|Macrophages|Mice|Microtubules', 'Journal Article', '10.1186/1471-2105-12-S13-S19', '22372978', 'Essential events of cell development and homeostasis are revealed by the associated changes of cell morphology and therefore have been widely used as a key indicator of physiological states and molecular pathways affecting various cellular functions via cytoskeleton. Cell motility is a complex phenomenon primarily driven by the actin network, which plays an important role in shaping the morphology of the cells. Most of the morphology based features are approximated from cell periphery but its dynamics have received none to scant attention. We aim to bridge the gap between membrane dynamics and cell states from the perspective of whole cell movement by identifying cell edge patterns and its correlation with cell dynamics.'),
(94787, 2011, 'bmc', 'Integrative analysis workflow for the structural and functional classification of C-type lectins', 'Koh, Geoffrey|Low, Ariana|Poh, Daren|Yao, Yujian|Ng, Say Kong|Wong, Victor Vai Tak|Vagenende, Vincent|Lam, Kong-Peng|Lee, Dong-Yup', 'Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 3, 'Algorithms|Animals|Humans|Lectins, C-Type|Ligands|Models, Molecular|Polysaccharides|Sequence Analysis, Protein|Software|Workflow', 'Journal Article', '10.1186/1471-2105-12-S14-S5', '22372988', 'It is important to understand the roles of C-type lectins in the immune system due to their ubiquity and diverse range of functions in animal cells. It has been observed that currently confirmed C-type lectins share a highly conserved domain known as the C-type carbohydrate recognition domain (CRD). Using the sequence profile of the CRD, an increasing number of putative C-type lectins have been identified. Hence, it is highly needed to develop a systematic framework that enables us to elucidate their carbohydrate (glycan) recognition function, and discover their physiological and pathological roles.'),
(94788, 2012, 'bmc', 'Argudas: lessons for argumentation in biology based on a gene expression use case', 'McLeod, Kenneth|Ferguson, Gus|Burger, Albert', 'Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.|Bioprocessing Technology Institute, Agency for Science, Technology and Research, 20 Biopolis Way, #06-01, Centros, 138668, Singapore.', 'Singapore|Singapore|Singapore', 0, 'Algorithms|Animals|Computational Biology|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|In Situ Hybridization|Mice', 'Journal Article', '10.1186/1471-2105-13-S1-S8', '22372999', 'In situ hybridisation gene expression information helps biologists identify where a gene is expressed. However, the databases that republish the experimental information online are often both incomplete and inconsistent. Non-monotonic reasoning can help resolve such difficulties - one such form of reasoning is computational argumentation. Essentially this involves asking a computer to debate (i.e. reason about) the validity of a particular statement. Arguments are produced for both sides - the statement is true and, the statement is false - then the most powerful argument is used. In this work the computer is asked to debate whether or not a gene is expressed in a particular mouse anatomical structure. The information generated during the debate can be passed to the biological end-user, enabling their own decision-making process.'),
(94789, 2011, 'bmc', 'Stability of building gene regulatory networks with sparse autoregressive models', 'Rajapakse, Jagath C|Mundra, Piyushkumar A', 'BioInformatics Research Centre, School of Computer Engineering, Nanyang Technological University, Singapore 639798. asjagath@ntu.edu.sg|BioInformatics Research Centre, School of Computer Engineering, Nanyang Technological University, Singapore 639798. asjagath@ntu.edu.sg', 'Singapore|Singapore', 0, 'Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|HeLa Cells|Humans|Models, Genetic|Multivariate Analysis|Software', 'Journal Article', '10.1186/1471-2105-12-S13-S17', '22373004', 'Biological networks are constantly subjected to random perturbations, and efficient feedback and compensatory mechanisms exist to maintain their stability. There is an increased interest in building gene regulatory networks (GRNs) from temporal gene expression data because of their numerous applications in life sciences. However, because of the limited number of time points at which gene expressions can be gathered in practice, computational techniques of building GRN often lead to inaccuracies and instabilities. This paper investigates the stability of sparse auto-regressive models of building GRN from gene expression data.'),
(94790, 2011, 'bmc', 'Novel base triples in RNA structures revealed by graph theoretical searching methods', 'Firdaus-Raih, Mohd|Harrison, Anne-Marie|Willett, Peter|Artymiuk, Peter J', 'Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield S10 2TN, UK.|Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield S10 2TN, UK.|Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield S10 2TN, UK.|Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield S10 2TN, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Base Pairing|Databases, Genetic|Haloarcula marismortui|Hydrogen Bonding|Models, Molecular|Nucleic Acid Conformation|RNA|RNA, Ribosomal, 23S|Software|Thermus thermophilus', 'Journal Article', '10.1186/1471-2105-12-S13-S2', '22373013', 'Highly hydrogen bonded base interactions play a major part in stabilizing the tertiary structures of complex RNA molecules, such as transfer-RNAs, ribozymes and ribosomal RNAs.'),
(94791, 2011, 'bmc', 'iGepros: an integrated gene and protein annotation server for biological nature exploration', 'Zheng, Guangyong|Wang, Haibo|Wei, Chaochun|Li, Yixue', 'Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China. zhenggy@sibs.ac.cn|Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China. zhenggy@sibs.ac.cn|Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China. zhenggy@sibs.ac.cn|Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China. zhenggy@sibs.ac.cn', 'China|China|China|China', 9, 'Animals|Brain|Genomics|Humans|Internet|Mice|Molecular Sequence Annotation|Proteomics|Software', 'Journal Article', '10.1186/1471-2105-12-S14-S6', '22373022', 'In the post-genomic era, transcriptomics and proteomics provide important information to understand the genomes. With fast development of high-throughput technology, more and more transcriptomics and proteomics data are generated at an unprecedented rate. Therefore, requirement of software to annotate those omics data and explore their biological nature arises. In the past decade, some pioneer works were presented to address this issue, but limitations still exist. Fox example, some of these tools offer command line only, which is not suitable for those users with little or no experience in programming. Besides, some tools dont support large scale gene and protein analysis.'),
(94792, 2011, 'bmc', 'Construction and analysis of the protein-protein interaction networks for schizophrenia, bipolar disorder, and major depression', 'Lee, Sheng-An|Tsao, Theresa Tsun-Hui|Yang, Ko-Chun|Lin, Han|Kuo, Yu-Lun|Hsu, Chien-Hsiang|Lee, Wen-Kuei|Huang, Kuo-Chuan|Kao, Cheng-Yan', 'Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.', '-|-|-|-|-|-|-|-|-', 39, 'Bipolar Disorder|Depressive Disorder, Major|Gene Expression Profiling|Humans|Polymorphism, Single Nucleotide|Prefrontal Cortex|Protein Interaction Maps|Proteomics|Schizophrenia|Signal Transduction', 'Journal Article', '10.1186/1471-2105-12-S13-S20', '22373040', 'Schizophrenia, bipolar disorder, and major depression are devastating mental diseases, each with distinctive yet overlapping epidemiologic characteristics. Microarray and proteomics data have revealed genes which expressed abnormally in patients. Several single nucleotide polymorphisms (SNPs) and mutations are associated with one or more of the three diseases. Nevertheless, there are few studies on the interactions among the disease-associated genes and proteins.'),
(94793, 2012, 'bmc', 'Federated ontology-based queries over cancer data', 'González-Beltrán, Alejandra|Tagger, Ben|Finkelstein, Anthony', 'Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.|Department of Information Management, Kainan University, Taoyuan, Taiwan.', '-|-|-', 0, 'Biological Ontologies|Computational Biology|Data Mining|Database Management Systems|Humans|Information Dissemination|Internet|Neoplasms|Semantics', 'Journal Article', '10.1186/1471-2105-13-S1-S9', '22373043', 'Personalised medicine provides patients with treatments that are specific to their genetic profiles. It requires efficient data sharing of disparate data types across a variety of scientific disciplines, such as molecular biology, pathology, radiology and clinical practice. Personalised medicine aims to offer the safest and most effective therapeutic strategy based on the gene variations of each subject. In particular, this is valid in oncology, where knowledge about genetic mutations has already led to new therapies. Current molecular biology techniques (microarrays, proteomics, epigenetic technology and improved DNA sequencing technology) enable better characterisation of cancer tumours. The vast amounts of data, however, coupled with the use of different terms - or semantic heterogeneity - in each discipline makes the retrieval and integration of information difficult.'),
(94794, 2011, 'bmc', 'ClipCrop: a tool for detecting structural variations with single-base resolution using soft-clipping information', 'Suzuki, Shin|Yasuda, Tomohiro|Shiraishi, Yuichi|Miyano, Satoru|Nagasaki, Masao', 'Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minatoku, Tokyo, 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minatoku, Tokyo, 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minatoku, Tokyo, 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minatoku, Tokyo, 108-8639, Japan.|Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minatoku, Tokyo, 108-8639, Japan.', 'Japan|Japan|Japan|Japan|Japan', 29, 'Chromosome Aberrations|Computer Simulation|DNA Mutational Analysis|Genome, Human|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-S14-S7', '22373054', 'Structural variations (SVs) change the structure of the genome and are therefore the causes of various diseases. Next-generation sequencing allows us to obtain a multitude of sequence data, some of which can be used to infer the position of SVs.'),
(94795, 2011, 'bmc', 'Exploiting heterogeneous features to improve in silico prediction of peptide status - amyloidogenic or non-amyloidogenic', 'Nair, Smitha Sunil Kumaran|Subba Reddy, N V|Hareesha, K S', 'Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal University, Karnataka, India. smitha.sunil@manipal.edu|Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal University, Karnataka, India. smitha.sunil@manipal.edu|Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal University, Karnataka, India. smitha.sunil@manipal.edu', 'India|India|India', 12, 'Algorithms|Amyloid|Databases, Protein|Neural Networks (Computer)|Peptides|Protein Folding|Protein Structure, Tertiary|ROC Curve|Sensitivity and Specificity|Sequence Analysis, Protein|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-12-S13-S21', '22373069', 'Prediction of short stretches in protein sequences capable of forming amyloid-like fibrils is important in understanding the underlying cause of amyloid illnesses thereby aiding in the discovery of sequence-targeted anti-aggregation pharmaceuticals. Due to the constraints of experimental molecular techniques in identifying such motif segments, it is highly desirable to develop computational methods to provide better and affordable in silico predictions.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94796, 2011, 'bmc', 'Identification of ubiquitin/ubiquitin-like protein modification from tandem mass spectra with various PTMs', 'Kang, Chiyong|Yi, Gwan-Su', 'Department of Bio and Brain Engineering, KAIST, Daejeon 305-701, South Korea.|Department of Bio and Brain Engineering, KAIST, Daejeon 305-701, South Korea.', '-|-', 0, 'Algorithms|Humans|Mass Spectrometry|Protein Processing, Post-Translational|Proteome|Proteomics|Tandem Mass Spectrometry|Ubiquitin|Ubiquitins', 'Journal Article', '10.1186/1471-2105-12-S14-S8', '22373085', 'Various solutions have been introduced for the identification of post-translational modification (PTM) from tandem mass spectrometry (MS/MS) in proteomics field but the identification of peptide modifiers, such as Ubiquitin (Ub) and ubiquitin-like proteins (Ubls), is still a challenge. The fragmentation of peptide modifier produce complex shifted ion mass patterns in combination with other PTMs, which makes it difficult to identify and locate the PTMs on a protein sequence. Currently, most PTM identification methods do not consider the complex fragmentation of peptide modifier or deals it separately from the other PTMs.'),
(94797, 2011, 'bmc', 'A new protein-ligand binding sites prediction method based on the integration of protein sequence conservation information', 'Dai, Tianli|Liu, Qi|Gao, Jun|Cao, Zhiwei|Zhu, Ruixin', 'College of Life Science and Biotechnology, Tongji University, 200092, Shanghai, China.|College of Life Science and Biotechnology, Tongji University, 200092, Shanghai, China.|College of Life Science and Biotechnology, Tongji University, 200092, Shanghai, China.|College of Life Science and Biotechnology, Tongji University, 200092, Shanghai, China.|College of Life Science and Biotechnology, Tongji University, 200092, Shanghai, China.', 'China|China|China|China|China', 0, 'Algorithms|Amino Acid Sequence|Conserved Sequence|Drug Design|Ligands|Models, Molecular|Protein Binding|Proteins', 'Journal Article', '10.1186/1471-2105-12-S14-S9', '22373099', 'Prediction of protein-ligand binding sites is an important issue for protein function annotation and structure-based drug design. Nowadays, although many computational methods for ligand-binding prediction have been developed, there is still a demanding to improve the prediction accuracy and efficiency. In addition, most of these methods are purely geometry-based, if the prediction methods improvement could be succeeded by integrating physicochemical or sequence properties of protein-ligand binding, it may also be more helpful to address the biological question in such studies.'),
(94798, 2011, 'bmc', 'Non-nucleosidic inhibition of Herpes simplex virus DNA polymerase: mechanistic insights into the anti-herpetic mode of action of herbal drug withaferin A', 'Grover, Abhinav|Agrawal, Vibhuti|Shandilya, Ashutosh|Bisaria, Virendra S|Sundar, Durai', 'Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.|Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.|Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.|Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.|Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India.', 'India|India|India|India|India', 0, 'Antiviral Agents|DNA, Viral|DNA-Directed DNA Polymerase|Exodeoxyribonucleases|Herpes Simplex|Herpesviridae Infections|Humans|Molecular Dynamics Simulation|Nucleic Acid Synthesis Inhibitors|Prospective Studies|Simplexvirus|Viral Proteins|Withanolides', 'Journal Article', '10.1186/1471-2105-12-S13-S22', '22373101', 'Herpes Simplex Virus 1 and 2 causes several infections in humans including cold sores and encephalitis. Previous antiviral studies on herpes viruses have focussed on developing nucleoside analogues that can inhibit viral polymerase and terminate the replicating viral DNA. However, these drugs bear an intrinsic non-specificity as they can also inhibit cellular polymerase apart from the viral one. The present study is an attempt to elucidate the action mechanism of naturally occurring withaferin A in inhibiting viral DNA polymerase, thus providing an evidence for its development as a novel anti-herpetic drug.'),
(94799, 2011, 'bmc', 'A framework for publishing primary biodiversity data', 'Roberts, Dave|Moritz, Tom', 'Zoology Microbiology Research Group, Zoology Department, Natural History Museum, SW7 5BD, London, UK. dmr@nomencurator.org|Zoology Microbiology Research Group, Zoology Department, Natural History Museum, SW7 5BD, London, UK. dmr@nomencurator.org', 'United Kingdom|United Kingdom', 6, 'Access to Information|Biodiversity|Information Dissemination|Publishing', 'Introductory Journal Article', '10.1186/1471-2105-12-S15-I1', '22373130', '-'),
(94800, 2011, 'bmc', 'In silico modification of suberoylanilide hydroxamic acid (SAHA) as potential inhibitor for class II histone deacetylase (HDAC)', 'Tambunan, Usman S F|Bramantya, N|Parikesit, Arli A', 'Department of Chemistry, Faculty of Mathematics and Science, University of Indonesia, Depok, Indonesia. usman@ui.ac.id|Department of Chemistry, Faculty of Mathematics and Science, University of Indonesia, Depok, Indonesia. usman@ui.ac.id|Department of Chemistry, Faculty of Mathematics and Science, University of Indonesia, Depok, Indonesia. usman@ui.ac.id', 'Indonesia|Indonesia|Indonesia', 25, 'Histone Deacetylase Inhibitors|Histone Deacetylases|Humans|Hydroxamic Acids|Models, Molecular|Molecular Dynamics Simulation|Structure-Activity Relationship|Vorinostat', 'Journal Article', '10.1186/1471-2105-12-S13-S23', '22373132', 'The cervical cancer is the second most prevalent cancer for the woman in the world. It is caused by the oncogenic human papilloma virus (HPV). The inhibition activity of histone deacetylase (HDAC) is a potential strategy for cancer therapy. Suberoylanilide hydroxamic acid (SAHA) is widely known as a low toxicity HDAC inhibitor. This research presents in silico SAHA modification by utilizing triazole, in order to obtain a better inhibitor. We conducted docking of the SAHA inhibitor and 12 modified versions to six class II HDAC enzymes, and then proceeded with drug scanning of each one of them.'),
(94801, 2011, 'bmc', 'Towards mainstreaming of biodiversity data publishing: recommendations of the GBIF Data Publishing Framework Task Group', 'Moritz, Tom|Krishnan, S|Roberts, Dave|Ingwersen, Peter|Agosti, Donat|Penev, Lyubomir|Cockerill, Matthew|Chavan, Vishwas|Data Publishing Framework Task Group', '1968½ South Shenandoah Street, Los Angeles, California 90034-1208, USA. tom.moritz@gmail.com|1968½ South Shenandoah Street, Los Angeles, California 90034-1208, USA. tom.moritz@gmail.com|1968½ South Shenandoah Street, Los Angeles, California 90034-1208, USA. tom.moritz@gmail.com|1968½ South Shenandoah Street, Los Angeles, California 90034-1208, USA. tom.moritz@gmail.com|1968½ South Shenandoah Street, Los Angeles, California 90034-1208, USA. tom.moritz@gmail.com|1968½ South Shenandoah Street, Los Angeles, California 90034-1208, USA. tom.moritz@gmail.com|1968½ South Shenandoah Street, Los Angeles, California 90034-1208, USA. tom.moritz@gmail.com|1968½ South Shenandoah Street, Los Angeles, California 90034-1208, USA. tom.moritz@gmail.com|1968½ South Shenandoah Street, Los Angeles, California 90034-1208, USA. tom.moritz@gmail.com', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 20, 'Access to Information|Biodiversity|Information Dissemination|Policy Making|Publishing', 'Guideline', '10.1186/1471-2105-12-S15-S1', '22373150', 'Data are the evidentiary basis for scientific hypotheses, analyses and publication, for policy formation and for decision-making. They are essential to the evaluation and testing of results by peer scientists both present and future. There is broad consensus in the scientific and conservation communities that data should be freely, openly available in a sustained, persistent and secure way, and thus standards for free and open access to data have become well developed in recent years. The question of effective access to data remains highly problematic.'),
(94802, 2011, 'bmc', 'Structure-based and ligand-based virtual screening of novel methyltransferase inhibitors of the dengue virus', 'Lim, See Ven|Rahman, Mohd Basyaruddin A|Tejo, Bimo A', 'Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, 43400 UPM Serdang, Malaysia.|Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, 43400 UPM Serdang, Malaysia.|Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, 43400 UPM Serdang, Malaysia.', 'Malaysia|Malaysia|Malaysia', 0, 'Antiviral Agents|Binding Sites|Dengue|Dengue Virus|Enzyme Inhibitors|High-Throughput Screening Assays|Humans|Ligands|Methyltransferases|Models, Molecular|RNA Caps|S-Adenosylhomocysteine|S-Adenosylmethionine|Viral Nonstructural Proteins', 'Journal Article', '10.1186/1471-2105-12-S13-S24', '22373153', 'The dengue virus is the most significant arthropod-borne human pathogen, and an increasing number of cases have been reported over the last few decades. Currently neither vaccines nor drugs against the dengue virus are available. NS5 methyltransferase (MTase), which is located on the surface of the dengue virus and assists in viral attachment to the host cell, is a promising antiviral target. In order to search for novel inhibitors of NS5 MTase, we performed a computer-aided virtual screening of more than 5 million commercially available chemical compounds using two approaches: i) structure-based screening using the crystal structure of NS5 MTase and ii) ligand-based screening using active ligands of NS5 MTase. Structure-based screening was performed using the LIDAEUS (LIgand Discovery At Edinburgh UniverSity) program. The ligand-based screening was carried out using the EDULISS (EDinburgh University LIgand Selection System) program.'),
(94803, 2011, 'bmc', 'The data paper: a mechanism to incentivize data  publishing in biodiversity science', 'Chavan, Vishwas|Penev, Lyubomir', 'Global Biodiversity Information Facility Secretariat, Universitetsparken 15, DK 2100, Copenhagen, Denmark. vchavan@gbif.org|Global Biodiversity Information Facility Secretariat, Universitetsparken 15, DK 2100, Copenhagen, Denmark. vchavan@gbif.org', 'Denmark|Denmark', 100, 'Access to Information|Biodiversity|Intellectual Property|Periodicals as Topic|Pilot Projects|Publishing|Workflow', 'Journal Article', '10.1186/1471-2105-12-S15-S2', '22373175', 'Free and open access to primary biodiversity data is essential for informed decision-making to achieve conservation of biodiversity and sustainable development. However, primary biodiversity data are neither easily accessible nor discoverable. Among several impediments, one is a lack of incentives to data publishers for publishing of their data resources. One such mechanism currently lacking is recognition through conventional scholarly publication of enriched metadata, which should ensure rapid discovery of fit-for-use biodiversity data resources.'),
(94804, 2011, 'bmc', 'In silico approach to screen compounds active against parasitic nematodes of major socio-economic importance', 'Khanna, Varun|Ranganathan, Shoba', 'Dept. of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, Australia.|Dept. of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, Australia.', 'Australia|Australia', 8, 'Algorithms|Animals|Anthelmintics|Drug Discovery|Humans|Nematoda|Nematode Infections|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-12-S13-S25', '22373185', 'Infections due to parasitic nematodes are common causes of morbidity and fatality around the world especially in developing nations. At present however, there are only three major classes of drugs for treating human nematode infections. Additionally the scientific knowledge on the mechanism of action and the reason for the resistance to these drugs is poorly understood. Commercial incentives to design drugs that are endemic to developing countries are limited therefore, virtual screening in academic settings can play a vital role is discovering novel drugs useful against neglected diseases. In this study we propose to build robust machine learning model to classify and screen compounds active against parasitic nematodes.'),
(94805, 2011, 'bmc', 'Indicators for the Data Usage Index (DUI): an  incentive for publishing primary biodiversity data  through global information infrastructure', 'Ingwersen, Peter|Chavan, Vishwas', 'Royal School of Library and Information Sciences, Birketinget 6, DK 2300, Copenhagen, Denmark.|Royal School of Library and Information Sciences, Birketinget 6, DK 2300, Copenhagen, Denmark.', 'Denmark|Denmark', 0, 'Access to Information|Biodiversity|Environment|Information Dissemination|Motivation|Publishing', 'Journal Article', '10.1186/1471-2105-12-S15-S3', '22373200', 'A professional recognition mechanism is required to encourage expedited publishing of an adequate volume of fit-for-use biodiversity data. As a component of such a recognition mechanism, we propose the development of the Data Usage Index (DUI) to demonstrate to data publishers that their efforts of creating biodiversity datasets have impact by being accessed and used by a wide spectrum of user communities.'),
(94806, 2011, 'bmc', 'Building gene expression profile classifiers with a simple and efficient rejection option in R', 'Benso, Alfredo|Di Carlo, Stefano|Politano, Gianfranco|Savino, Alessandro|Hafeezurrehman, Hafeez', 'Control and Computer Engineering Department, Politecnico di Torino, Corso Duca degli Abruzzi 24,10129, Torino, Italy.|Control and Computer Engineering Department, Politecnico di Torino, Corso Duca degli Abruzzi 24,10129, Torino, Italy.|Control and Computer Engineering Department, Politecnico di Torino, Corso Duca degli Abruzzi 24,10129, Torino, Italy.|Control and Computer Engineering Department, Politecnico di Torino, Corso Duca degli Abruzzi 24,10129, Torino, Italy.|Control and Computer Engineering Department, Politecnico di Torino, Corso Duca degli Abruzzi 24,10129, Torino, Italy.', 'Italy|Italy|Italy|Italy|Italy', 5, 'Algorithms|Artificial Intelligence|Gene Expression Profiling|Humans|Lymphoma|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-12-S13-S3', '22373214', 'The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of known classes. However, in a clinical diagnostics setup, novel and unknown classes (new pathologies) may appear and one must be able to reject those samples that do not fit the trained model. The problem of implementing a rejection option in a multi-class classifier has not been widely addressed in the statistical literature. Gene expression profiles represent a critical case study since they suffer from the curse of dimensionality problem that negatively reflects on the reliability of both traditional rejection models and also more recent approaches such as one-class classifiers.'),
(94807, 2011, 'bmc', 'The Biodiversity Informatics Potential Index', 'Ariño, Arturo H|Chavan, Vishwas|King, Nick', 'Department of Zoology and Ecology, University of Navarra, E-31080 Pamplona, Spain. artarip@unav.es|Department of Zoology and Ecology, University of Navarra, E-31080 Pamplona, Spain. artarip@unav.es|Department of Zoology and Ecology, University of Navarra, E-31080 Pamplona, Spain. artarip@unav.es', 'Spain|Spain|Spain', 0, 'Biodiversity|Ecology|Informatics|Information Services|Models, Theoretical|Publishing', 'Journal Article', '10.1186/1471-2105-12-S15-S4', '22373233', 'Biodiversity informatics is a relatively new discipline extending computer science in the context of biodiversity data, and its development to date has not been uniform throughout the world. Digitizing effort and capacity building are costly, and ways should be found to prioritize them rationally. The proposed Biodiversity Informatics Potential (BIP) Index seeks to fulfill such a prioritization role. We propose that the potential for biodiversity informatics be assessed through three concepts: (a) the intrinsic biodiversity potential (the biological richness or ecological diversity) of a country, (b) the capacity of the country to generate biodiversity data records, and (c) the availability of technical infrastructure in a country for managing and publishing such records.'),
(94808, 2011, 'bmc', 'PTIGS-IdIt, a system for species identification by DNA sequences of the psbA-trnH intergenic spacer region', 'Liu, Chang|Liang, Dong|Gao, Ting|Pang, Xiaohui|Song, Jingyuan|Yao, Hui|Han, Jianping|Liu, Zhihua|Guan, Xiaojun|Jiang, Kun|Li, Huan|Chen, Shilin', 'The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn|The Key Laboratory of Bioactive Substances and Resources Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, P R China. cliu@implad.ac.cn', 'China|China|China|China|China|China|China|China|China|China|China|China', 0, 'Algorithms|DNA Barcoding, Taxonomic|DNA, Intergenic|DNA, Plant|Markov Chains|Plants|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-12-S13-S4', '22373238', 'DNA barcoding technology, which uses a short piece of DNA sequence to identify species, has wide ranges of applications. Until today, a universal DNA barcode marker for plants remains elusive. The rbcL and matK regions have been proposed as the core barcode for plants and the ITS2 and psbA-trnH intergenic spacer (PTIGS) regions were later added as supplemental barcodes. The use of PTIGS region as a supplemental barcode has been limited by the lack of computational tools that can handle significant insertions and deletions in the PTIGS sequences. Here, we compared the most commonly used alignment-based and alignment-free methods and developed a web server to allow the biologists to carry out PTIGS-based DNA barcoding analyses.'),
(94809, 2011, 'bmc', 'Data hosting infrastructure for primary biodiversity data', 'Goddard, Anthony|Wilson, Nathan|Cryer, Phil|Yamashita, Grant', 'Center for Library and Informatics, Woods Hole Marine Biological Laboratory, Woods Hole, MA 02543, USA. agoddard@mbl.edu|Center for Library and Informatics, Woods Hole Marine Biological Laboratory, Woods Hole, MA 02543, USA. agoddard@mbl.edu|Center for Library and Informatics, Woods Hole Marine Biological Laboratory, Woods Hole, MA 02543, USA. agoddard@mbl.edu|Center for Library and Informatics, Woods Hole Marine Biological Laboratory, Woods Hole, MA 02543, USA. agoddard@mbl.edu', 'United States|United States|United States|United States', 8, 'Access to Information|Biodiversity|Data Collection|Humans|Informatics|Information Dissemination|Public Sector', 'Journal Article', '10.1186/1471-2105-12-S15-S5', '22373257', 'Today, an unprecedented volume of primary biodiversity data are being generated worldwide, yet significant amounts of these data have been and will continue to be lost after the conclusion of the projects tasked with collecting them. To get the most value out of these data it is imperative to seek a solution whereby these data are rescued, archived and made available to the biodiversity community. To this end, the biodiversity informatics community requires investment in processes and infrastructure to mitigate data loss and provide solutions for long-term hosting and sharing of biodiversity data.'),
(94810, 2011, 'bmc', 'Prediction of dinucleotide-specific RNA-binding sites in proteins', 'Fernandez, Michael|Kumagai, Yutaro|Standley, Daron M|Sarai, Akinori|Mizuguchi, Kenji|Ahmad, Shandar', 'Kyushu Institute of Technology, Fukuoka, Japan.|Kyushu Institute of Technology, Fukuoka, Japan.|Kyushu Institute of Technology, Fukuoka, Japan.|Kyushu Institute of Technology, Fukuoka, Japan.|Kyushu Institute of Technology, Fukuoka, Japan.|Kyushu Institute of Technology, Fukuoka, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Amino Acids|Animals|Binding Sites|Humans|Models, Molecular|Neural Networks (Computer)|Nucleotides|RNA|RNA-Binding Proteins|ROC Curve', 'Journal Article', '10.1186/1471-2105-12-S13-S5', '22373260', 'Regulation of gene expression, protein synthesis, replication and assembly of many viruses involve RNA-protein interactions. Although some successful computational tools have been reported to recognize RNA binding sites in proteins, the problem of specificity remains poorly investigated. After the nucleotide base composition, the dinucleotide is the smallest unit of RNA sequence information and many RNA-binding proteins simply bind to regions enriched in one dinucleotide. Interaction preferences of protein subsequences and dinucleotides can be inferred from protein-RNA complex structures, enabling a training-based prediction approach.'),
(94811, 2012, 'bmc', 'Semantic Web applications and tools for the life sciences: SWAT4LS 2010', 'Burger, Albert|Paschke, Adrian|Romano, Paolo|Marshall, M Scott|Splendiani, Andrea', 'Kyushu Institute of Technology, Fukuoka, Japan.|Kyushu Institute of Technology, Fukuoka, Japan.|Kyushu Institute of Technology, Fukuoka, Japan.|Kyushu Institute of Technology, Fukuoka, Japan.|Kyushu Institute of Technology, Fukuoka, Japan.', 'Japan|Japan|Japan|Japan|Japan', 0, 'Computational Biology|Data Mining|Information Storage and Retrieval|Internet|Semantics', 'Introductory Journal Article', '10.1186/1471-2105-13-S1-S1', '22373274', 'As Semantic Web technologies mature and new releases of key elements, such as SPARQL 1.1 and OWL 2.0, become available, the Life Sciences continue to push the boundaries of these technologies with ever more sophisticated tools and applications. Unsurprisingly, therefore, interest in the SWAT4LS (Semantic Web Applications and Tools for the Life Sciences) activities have remained high, as was evident during the third international SWAT4LS workshop held in Berlin in December 2010. Contributors to this workshop were invited to submit extended versions of their papers, the best of which are now made available in the special supplement of BMC Bioinformatics. The papers reflect the wide range of work in this area, covering the storage and querying of Life Sciences data in RDF triple stores, tools for the development of biomedical ontologies and the semantics-based integration of Life Sciences as well as clinicial data. '),
(94812, 2011, 'bmc', 'PB1-F2 Finder: scanning influenza sequences for PB1-F2 encoding RNA segments', 'DeLuca, David S|Keskin, Derin B|Zhang, Guang Lan|Reinherz, Ellis L|Brusic, Vladimir', 'Cancer Vaccine Center, Dana-Farber Cancer Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.|Cancer Vaccine Center, Dana-Farber Cancer Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.|Cancer Vaccine Center, Dana-Farber Cancer Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.|Cancer Vaccine Center, Dana-Farber Cancer Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.|Cancer Vaccine Center, Dana-Farber Cancer Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Humans|Influenza A Virus, H1N1 Subtype|Influenza A virus|Influenza, Human|Sequence Analysis, RNA|Viral Proteins|Virulence Factors', 'Journal Article', '10.1186/1471-2105-12-S13-S6', '22373288', 'PB1-F2 is a major virulence factor of influenza A. This protein is a product of an alternative reading frame in the PB1-encoding RNA segment 2. Its presence of is dictated by the presence or absence of premature stop codons. This virulence factor is present in every influenza pandemic and major epidemic of the 20th century. Absence of PB1-F2 is associated with mild disease, such as the 2009 H1N1 (swine flu).'),
(94813, 2012, 'bmc', 'A semantic web framework to integrate cancer omics data with biological knowledge', 'Holford, Matthew E|McCusker, James P|Cheung, Kei-Hoi|Krauthammer, Michael', 'Cancer Vaccine Center, Dana-Farber Cancer Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.|Cancer Vaccine Center, Dana-Farber Cancer Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.|Cancer Vaccine Center, Dana-Farber Cancer Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.|Cancer Vaccine Center, Dana-Farber Cancer Institute, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.', 'United States|United States|United States|United States', 0, 'Azacitidine|Database Management Systems|Decitabine|Drug Resistance, Neoplasm|Epigenomics|Gene Expression Profiling|Gene Ontology|Gene Regulatory Networks|Humans|Internet|Melanoma|Semantics|Transcription Factors|Translational Medical Research', 'Journal Article', '10.1186/1471-2105-13-S1-S10', '22373303', 'The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge.'),
(94814, 2011, 'bmc', 'Prediction of RNA-binding amino acids from protein and RNA sequences', 'Choi, Sungwook|Han, Kyungsook', 'School of Computer Science and Engineering, Inha University, Inchon 402-751, South Korea.|School of Computer Science and Engineering, Inha University, Inchon 402-751, South Korea.', '-|-', 9, 'Amino Acids|Binding Sites|Models, Molecular|Nucleotides|RNA|RNA-Binding Proteins|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-12-S13-S7', '22373313', 'Many learning approaches to predicting RNA-binding residues in a protein sequence construct a non-redundant training dataset based on the sequence similarity. The sequence similarity-based method either takes a whole sequence or discards it for a training dataset. However, similar sequences or even identical sequences can have different interaction sites depending on their interaction partners, and this information is lost when the sequences are removed. Furthermore, a training dataset constructed by the sequence similarity-based method may contain redundant data when the remaining sequence contains similar subsequences within the sequence. In addition to the problem with the training dataset, most approaches do not consider the interacting partner (i.e., RNA) of a protein when they predict RNA-binding amino acids. Thus, they always predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNA molecules.'),
(94815, 2012, 'bmc', 'SPARQL assist language-neutral query composer', 'McCarthy, Luke|Vandervalk, Ben|Wilkinson, Mark', 'School of Computer Science and Engineering, Inha University, Inchon 402-751, South Korea.|School of Computer Science and Engineering, Inha University, Inchon 402-751, South Korea.|School of Computer Science and Engineering, Inha University, Inchon 402-751, South Korea.', '-|-|-', 8, 'Biological Ontologies|Computational Biology|Data Mining|Databases, Factual|Internet|Semantics|Software', 'Journal Article', '10.1186/1471-2105-13-S1-S2', '22373327', 'SPARQL query composition is difficult for the lay-person, and even the experienced bioinformatician in cases where the data model is unfamiliar. Moreover, established best-practices and internationalization concerns dictate that the identifiers for ontological terms should be opaque rather than human-readable, which further complicates the task of synthesizing queries manually.'),
(94816, 2011, 'bmc', 'Comprehensive evaluation of matrix factorization methods for the analysis of DNA microarray gene expression data', 'Kim, Mi Hyeon|Seo, Hwa Jeong|Joung, Je-Gun|Kim, Ju Han', 'Seoul National University Biomedical Informatics, Systems Biomedical Informatics Research Center, and Interdisciplinary Program of Medical Informatics Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea.|Seoul National University Biomedical Informatics, Systems Biomedical Informatics Research Center, and Interdisciplinary Program of Medical Informatics Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea.|Seoul National University Biomedical Informatics, Systems Biomedical Informatics Research Center, and Interdisciplinary Program of Medical Informatics Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea.|Seoul National University Biomedical Informatics, Systems Biomedical Informatics Research Center, and Interdisciplinary Program of Medical Informatics Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea.', '-|-|-|-', 11, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Humans|Leukemia|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-12-S13-S8', '22373334', 'Clustering-based methods on gene-expression analysis have been shown to be useful in biomedical applications such as cancer subtype discovery. Among them, Matrix factorization (MF) is advantageous for clustering gene expression patterns from DNA microarray experiments, as it efficiently reduces the dimension of gene expression data. Although several MF methods have been proposed for clustering gene expression patterns, a systematic evaluation has not been reported yet.'),
(94817, 2011, 'bmc', 'HabiSign: a novel approach for comparison of metagenomes and rapid identification of habitat-specific sequences', 'Ghosh, Tarini Shankar|Mohammed, Monzoorul Haque|Rajasingh, Hannah|Chadaram, Sudha|Mande, Sharmila S', 'Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.', 'India|India|India|India|India', 13, 'Algorithms|Animals|Bacterial Typing Techniques|Metagenome|Metagenomics', 'Journal Article', '10.1186/1471-2105-12-S13-S9', '22373355', 'One of the primary goals of comparative metagenomic projects is to study the differences in the microbial communities residing in diverse environments. Besides providing valuable insights into the inherent structure of the microbial populations, these studies have potential applications in several important areas of medical research like disease diagnostics, detection of pathogenic contamination and identification of hitherto unknown pathogens. Here we present a novel and rapid, alignment-free method called HabiSign, which utilizes patterns of tetra-nucleotide usage in microbial genomes to bring out the differences in the composition of both diverse and related microbial communities.'),
(94818, 2012, 'bmc', 'Gauging triple stores with actual biological data', 'Mironov, Vladimir|Seethappan, Nirmala|Blondé, Ward|Antezana, Erick|Splendiani, Andrea|Kuiper, Martin', 'Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.|Bio-sciences R&D Division, TCS Innovation Labs, Tata Consultancy Services Limited, 1 Software Units Layout, Madhapur, Hyderabad - 500081, Andhra Pradesh, India.', 'India|India|India|India|India|India', 0, 'Biological Ontologies|Computational Biology|Data Mining|Internet|Reproducibility of Results|Semantics|Time Factors', 'Journal Article', '10.1186/1471-2105-13-S1-S3', '22373359', 'Semantic Web technologies have been developed to overcome the limitations of the current Web and conventional data integration solutions. The Semantic Web is expected to link all the data present on the Internet instead of linking just documents. One of the foundations of the Semantic Web technologies is the knowledge representation language Resource Description Framework (RDF). Knowledge expressed in RDF is typically stored in so-called triple stores (also known as RDF stores), from which it can be retrieved with SPARQL, a language designed for querying RDF-based models. The Semantic Web technologies should allow federated queries over multiple triple stores. In this paper we compare the efficiency of a set of biologically relevant queries as applied to a number of different triple store implementations.'),
(94819, 2011, 'bmc', 'MUCHA: multiple chemical alignment algorithm to identify building block substructures of orphan secondary metabolites', 'Kotera, Masaaki|Tokimatsu, Toshiaki|Kanehisa, Minoru|Goto, Susumu', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.', 'Japan|Japan|Japan|Japan', 1, 'Algorithms|Chemistry|Metabolic Networks and Pathways', 'Journal Article', '10.1186/1471-2105-12-S14-S1', '22373367', 'In contrast to the increasing number of the successful genome projects, there still remain many orphan metabolites for which their synthesis processes are unknown. Metabolites, including these orphan metabolites, can be classified into groups that share the same core substructures, originated from the same biosynthetic pathways. It is known that many metabolites are synthesized by adding up building blocks to existing metabolites. Therefore, it is proposed that, for any given group of metabolites, finding the core substructure and the branched substructures can help predict their biosynthetic pathway. There already have been many reports on the multiple graph alignment techniques to find the conserved chemical substructures in relatively small molecules. However, they are optimized for ligand binding and are not suitable for metabolomic studies.'),
(94820, 2012, 'bmc', 'User centered and ontology based information retrieval system for life sciences', 'Sy, Mohameth-François|Ranwez, Sylvie|Montmain, Jacky|Regnault, Armelle|Crampes, Michel|Ranwez, Vincent', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 24, 'Biological Ontologies|Computational Biology|Hematopoiesis|Humans|Information Storage and Retrieval|Internet|Medical Subject Headings|PubMed|Semantics|Software|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-S1-S4', '22373375', 'Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations.'),
(94821, 2011, 'bmc', 'A protein-dependent side-chain rotamer library', 'Bhuyan, Md Shariful Islam|Gao, Xin', 'Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.', '-|-', 21, 'Algorithms|Computational Biology|Models, Molecular|Peptide Library|Probability|Protein Conformation|Proteins', 'Journal Article', '10.1186/1471-2105-12-S14-S10', '22373394', 'Protein side-chain packing problem has remained one of the key open problems in bioinformatics. The three main components of protein side-chain prediction methods are a rotamer library, an energy function and a search algorithm. Rotamer libraries summarize the existing knowledge of the experimentally determined structures quantitatively. Depending on how much contextual information is encoded, there are backbone-independent rotamer libraries and backbone-dependent rotamer libraries. Backbone-independent libraries only encode sequential information, whereas backbone-dependent libraries encode both sequential and locally structural information. However, side-chain conformations are determined by spatially local information, rather than sequentially local information. Since in the side-chain prediction problem, the backbone structure is given, spatially local information should ideally be encoded into the rotamer libraries.'),
(94822, 2012, 'bmc', 'Populous: a tool for building OWL ontologies from templates', 'Jupp, Simon|Horridge, Matthew|Iannone, Luigi|Klein, Julie|Owen, Stuart|Schanstra, Joost|Wolstencroft, Katy|Stevens, Robert', 'Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.', '-|-|-|-|-|-|-|-', 0, 'Biological Ontologies|Computational Biology|Databases, Factual|Semantics|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-S1-S5', '22373396', 'Ontologies are being developed for the life sciences to standardise the way we describe and interpret the wealth of data currently being generated. As more ontology based applications begin to emerge, tools are required that enable domain experts to contribute their knowledge to the growing pool of ontologies. There are many barriers that prevent domain experts engaging in the ontology development process and novel tools are needed to break down these barriers to engage a wider community of scientists.'),
(94823, 2012, 'bmc', 'Exploring and linking biomedical resources through multidimensional semantic spaces', 'Berlanga, Rafael|Jiménez-Ruiz, Ernesto|Nebot, Victoria', 'Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955, KSA.', '-|-|-', 12, 'Biological Ontologies|Biomedical Research|Computational Biology|Computer Graphics|Data Collection|Databases, Factual|Humans|PubMed|Semantics', 'Journal Article', '10.1186/1471-2105-13-S1-S6', '22373409', 'The semantic integration of biomedical resources is still a challenging issue which is required for effective information processing and data analysis. The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows disparate data formats and contents to be expressed under a common semantic space. In this paper, we propose a multidimensional representation for such a semantic space, where dimensions regard the different perspectives in biomedical research (e.g., population, disease, anatomy and protein/genes).'),
(94824, 2011, 'bmc', 'Optimizing de novo transcriptome assembly from short-read RNA-Seq data: a comparative study', 'Zhao, Qiong-Yi|Wang, Yi|Kong, Yi-Meng|Luo, Da|Li, Xuan|Hao, Pei', 'Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China.|Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China.|Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China.|Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China.|Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China.|Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200032, China.', 'China|China|China|China|China|China', 310, 'Camellia sinensis|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, RNA|Software|Transcriptome', 'Comparative Study', '10.1186/1471-2105-12-S14-S2', '22373417', 'With the fast advances in nextgen sequencing technology, high-throughput RNA sequencing has emerged as a powerful and cost-effective way for transcriptome study. De novo assembly of transcripts provides an important solution to transcriptome analysis for organisms with no reference genome. However, there lacked understanding on how the different variables affected assembly outcomes, and there was no consensus on how to approach an optimal solution by selecting software tool and suitable strategy based on the properties of RNA-Seq data.'),
(94825, 2011, 'bmc', 'Enumerating tree-like chemical graphs with given upper and lower bounds on path frequencies', 'Shimizu, Masaaki|Nagamochi, Hiroshi|Akutsu, Tatsuya', 'Graduate School of Informatics, Kyoto University, Yoshida, Kyoto 606-8501, Japan.|Graduate School of Informatics, Kyoto University, Yoshida, Kyoto 606-8501, Japan.|Graduate School of Informatics, Kyoto University, Yoshida, Kyoto 606-8501, Japan.', 'Japan|Japan|Japan', 0, 'Algorithms|Computational Biology|Drug Design', 'Journal Article', '10.1186/1471-2105-12-S14-S3', '22373441', 'Enumeration of chemical graphs satisfying given constraints is one of the fundamental problems in chemoinformatics and bioinformatics since it leads to a variety of useful applications including structure determination of novel chemical compounds and drug design.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94826, 2012, 'bmc', 'PhiSiGns: an online tool to identify signature genes in phages and design PCR primers for examining phage diversity', 'Dwivedi, Bhakti|Schmieder, Robert|Goldsmith, Dawn B|Edwards, Robert A|Breitbart, Mya', 'College of Marine Science, University of South Florida, St, Petersburg, FL 33701, USA. bhaktihd@gmail.com|College of Marine Science, University of South Florida, St, Petersburg, FL 33701, USA. bhaktihd@gmail.com|College of Marine Science, University of South Florida, St, Petersburg, FL 33701, USA. bhaktihd@gmail.com|College of Marine Science, University of South Florida, St, Petersburg, FL 33701, USA. bhaktihd@gmail.com|College of Marine Science, University of South Florida, St, Petersburg, FL 33701, USA. bhaktihd@gmail.com', 'United States|United States|United States|United States|United States', 0, 'Bacteriophages|Biological Evolution|Computational Biology|Genome, Viral|Phylogeny|Polymerase Chain Reaction|Sewage|Software|Virology', 'Journal Article', '10.1186/1471-2105-13-37', '22385976', 'Phages (viruses that infect bacteria) have gained significant attention because of their abundance, diversity and important ecological roles. However, the lack of a universal gene shared by all phages presents a challenge for phage identification and characterization, especially in environmental samples where it is difficult to culture phage-host systems. Homologous conserved genes (or signature genes) present in groups of closely-related phages can be used to explore phage diversity and define evolutionary relationships amongst these phages. Bioinformatic approaches are needed to identify candidate signature genes and design PCR primers to amplify those genes from environmental samples, however, there is currently no existing computational tool that biologists can use for this purpose.'),
(94827, 2012, 'bmc', 'Non-negative matrix factorisation methods for the spectral decomposition of MRS data from human brain tumours', 'Ortega-Martorell, Sandra|Lisboa, Paulo J G|Vellido, Alfredo|Julià-Sapé, Margarida|Arús, Carles', 'Departament de Bioquímica i Biología Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain. P.J.Lisboa@ljmu.ac.uk|Departament de Bioquímica i Biología Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain. P.J.Lisboa@ljmu.ac.uk|Departament de Bioquímica i Biología Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain. P.J.Lisboa@ljmu.ac.uk|Departament de Bioquímica i Biología Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain. P.J.Lisboa@ljmu.ac.uk|Departament de Bioquímica i Biología Molecular, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain. P.J.Lisboa@ljmu.ac.uk', 'Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Brain Neoplasms|Databases, Factual|Humans|Magnetic Resonance Spectroscopy|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-13-38', '22401579', 'In-vivo single voxel proton magnetic resonance spectroscopy (SV 1H-MRS), coupled with supervised pattern recognition (PR) methods, has been widely used in clinical studies of discrimination of brain tumour types and follow-up of patients bearing abnormal brain masses. SV 1H-MRS provides useful biochemical information about the metabolic state of tumours and can be performed at short (< 45 ms) or long (> 45 ms) echo time (TE), each with particular advantages. Short-TE spectra are more adequate for detecting lipids, while the long-TE provides a much flatter signal baseline in between peaks but also negative signals for metabolites such as lactate. Both, lipids and lactate, are respectively indicative of specific metabolic processes taking place. Ideally, the information provided by both TE should be of use for clinical purposes. In this study, we characterise the performance of a range of Non-negative Matrix Factorisation (NMF) methods in two respects: first, to derive sources correlated with the mean spectra of known tissue types (tumours and normal tissue), second, taking the best performing NMF method for source separation, we compare its accuracy for class assignment when using the mixing matrix directly as a basis for classification, as against using the method for dimensionality reduction (DR). For this, we used SV 1H-MRS data with positive and negative peaks, from a widely tested SV 1H-MRS human brain tumour database.'),
(94828, 2012, 'bmc', 'Visualisation of variable binding pockets on protein surfaces by probabilistic analysis of related structure sets', 'Ashford, Paul|Moss, David S|Alex, Alexander|Yeap, Siew K|Povia, Alice|Nobeli, Irene|Williams, Mark A', 'Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK.|Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK.|Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK.|Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK.|Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK.|Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK.|Institute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 11, 'Algorithms|Animals|Drug Design|Humans|Interleukin-2|Ligands|Models, Molecular|Protein Conformation|Protein Kinases|Proteins|Software|Surface Properties', 'Journal Article', '10.1186/1471-2105-13-39', '22417279', 'Protein structures provide a valuable resource for rational drug design. For a protein with no known ligand, computational tools can predict surface pockets that are of suitable size and shape to accommodate a complementary small-molecule drug. However, pocket prediction against single static structures may miss features of pockets that arise from proteins dynamic behaviour. In particular, ligand-binding conformations can be observed as transiently populated states of the apo protein, so it is possible to gain insight into ligand-bound forms by considering conformational variation in apo proteins. This variation can be explored by considering sets of related structures: computationally generated conformers, solution NMR ensembles, multiple crystal structures, homologues or homology models. It is non-trivial to compare pockets, either from different programs or across sets of structures. For a single structure, difficulties arise in defining particular pockets boundaries. For a set of conformationally distinct structures the challenge is how to make reasonable comparisons between them given that a perfect structural alignment is not possible.'),
(94829, 2012, 'bmc', 'PupDB: a database of pupylated proteins', 'Tung, Chun-Wei', 'School of Pharmacy, Kaohsiung Medical University, Kaohsiung 807, Taiwan. cwtung@kmu.edu.tw', '-', 29, 'Bacteria|Bacterial Proteins|Databases, Protein|Internet|Protein Processing, Post-Translational|Proteomics|Substrate Specificity|Ubiquitins', 'Journal Article', '10.1186/1471-2105-13-40', '22424087', 'Prokaryotic ubiquitin-like protein (Pup), the firstly identified post-translational protein modifier in prokaryotes, is an important signal for the selective degradation of proteins. Recently, large-scale proteomics technology has been applied to identify a large number of pupylated proteins. The development of a database for managing pupylated proteins and pupylation sites is important for further analyses.'),
(94830, 2012, 'bmc', 'Predicting protein-protein interface residues using local surface structural similarity', 'Jordan, Rafael A|El-Manzalawy, Yasser|Dobbs, Drena|Honavar, Vasant', 'Department of Computer Science, Iowa State University, Ames, IA 50011, USA. rjordan@iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011, USA. rjordan@iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011, USA. rjordan@iastate.edu|Department of Computer Science, Iowa State University, Ames, IA 50011, USA. rjordan@iastate.edu', 'United States|United States|United States|United States', 57, 'Algorithms|Models, Molecular|Protein Conformation|Protein Interaction Domains and Motifs|Proteins|Software', 'Journal Article', '10.1186/1471-2105-13-41', '22424103', 'Identification of the residues in protein-protein interaction sites has a significant impact in problems such as drug discovery. Motivated by the observation that the set of interface residues of a protein tend to be conserved even among remote structural homologs, we introduce PrISE, a family of local structural similarity-based computational methods for predicting protein-protein interface residues.'),
(94831, 2012, 'bmc', 'Cloud BioLinux: pre-configured and on-demand bioinformatics computing for the genomics community', 'Krampis, Konstantinos|Booth, Tim|Chapman, Brad|Tiwari, Bela|Bicak, Mesude|Field, Dawn|Nelson, Karen E', 'J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA. agbiotec@gmail.com|J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA. agbiotec@gmail.com|J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA. agbiotec@gmail.com|J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA. agbiotec@gmail.com|J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA. agbiotec@gmail.com|J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA. agbiotec@gmail.com|J. Craig Venter Institute, 9704 Medical Center Drive, Rockville, MD 20850, USA. agbiotec@gmail.com', 'United States|United States|United States|United States|United States|United States|United States', 119, 'Animals|Computers|Computing Methodologies|Genomics|Humans|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-13-42', '22429538', 'A steep drop in the cost of next-generation sequencing during recent years has made the technology affordable to the majority of researchers, but downstream bioinformatic analysis still poses a resource bottleneck for smaller laboratories and institutes that do not have access to substantial computational resources. Sequencing instruments are typically bundled with only the minimal processing and storage capacity required for data capture during sequencing runs. Given the scale of sequence datasets, scientific value cannot be obtained from acquiring a sequencer unless it is accompanied by an equal investment in informatics infrastructure.'),
(94832, 2012, 'bmc', 'Codon Deviation Coefficient: a novel measure for estimating codon usage bias and its statistical significance', 'Zhang, Zhang|Li, Jun|Cui, Peng|Ding, Feng|Li, Ang|Townsend, Jeffrey P|Yu, Jun', 'Computational Bioscience Research Center (CBRC), King Abdullah Universitof Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center (CBRC), King Abdullah Universitof Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center (CBRC), King Abdullah Universitof Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center (CBRC), King Abdullah Universitof Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center (CBRC), King Abdullah Universitof Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center (CBRC), King Abdullah Universitof Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.|Computational Bioscience Research Center (CBRC), King Abdullah Universitof Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.', 'Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia', 34, 'Amino Acids|Animals|Arabidopsis|Base Composition|Biological Evolution|Codon|Computer Simulation|Escherichia coli|Genome|Mutation|Saccharomyces cerevisiae|Selection, Genetic|Statistics as Topic', 'Journal Article', '10.1186/1471-2105-13-43', '22435713', 'Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB). Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis.'),
(94833, 2012, 'bmc', 'Grading amino acid properties increased accuracies of single point mutation on protein stability prediction', 'Liu, Jianguo|Kang, Xianjiang', 'Life Sciences School, Hebei University, Baoding, Hebei 071002, Peoples Republic of China.|Life Sciences School, Hebei University, Baoding, Hebei 071002, Peoples Republic of China.', 'China|China', 8, 'Algorithms|Amino Acids|Animals|Artificial Intelligence|Humans|Point Mutation|Protein Stability|Proteins', 'Journal Article', '10.1186/1471-2105-13-44', '22435732', 'Protein stabilities can be affected sometimes by point mutations introduced to the protein. Current sequence-information-based protein stability prediction encoding schemes of machine learning approaches include sparse encoding and amino acid property encoding. Property encoding schemes employ physical-chemical information of the mutated protein environments, however, they produce complexity in the mean time when many properties joined in the scheme. The complexity introduces noises that affect machine learning algorithm accuracies. In order to overcome the problem we described a new encoding scheme that graded twenty amino acids into groups according to their specific property values.'),
(94834, 2012, 'bmc', 'Arena3D: visualizing time-driven phenotypic differences in biological systems', 'Secrier, Maria|Pavlopoulos, Georgios A|Aerts, Jan|Schneider, Reinhard', 'Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, Heidelberg 69117, Germany. secrier@embl.de|Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, Heidelberg 69117, Germany. secrier@embl.de|Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, Heidelberg 69117, Germany. secrier@embl.de|Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, Heidelberg 69117, Germany. secrier@embl.de', 'Germany|Germany|Germany|Germany', 35, 'Animals|Cluster Analysis|Embryonic Stem Cells|Epigenesis, Genetic|Gene Knockdown Techniques|Genotype|Humans|Mice|Phenotype|Protein Biosynthesis|Proteins|Software|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-13-45', '22439608', 'Elucidating the genotype-phenotype connection is one of the big challenges of modern molecular biology. To fully understand this connection, it is necessary to consider the underlying networks and the time factor. In this context of data deluge and heterogeneous information, visualization plays an essential role in interpreting complex and dynamic topologies. Thus, software that is able to bring the network, phenotypic and temporal information together is needed. Arena3D has been previously introduced as a tool that facilitates link discovery between processes. It uses a layered display to separate different levels of information while emphasizing the connections between them. We present novel developments of the tool for the visualization and analysis of dynamic genotype-phenotype landscapes.'),
(94835, 2012, 'bmc', 'Correlation set analysis: detecting active regulators in disease populations using prior causal knowledge', 'Huang, Chia-Ling|Lamb, John|Chindelevitch, Leonid|Kostrowicki, Jarek|Guinney, Justin|Delisi, Charles|Ziemek, Daniel', 'Bioinformatics Graduate Program, and Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, USA.|Bioinformatics Graduate Program, and Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, USA.|Bioinformatics Graduate Program, and Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, USA.|Bioinformatics Graduate Program, and Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, USA.|Bioinformatics Graduate Program, and Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, USA.|Bioinformatics Graduate Program, and Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, USA.|Bioinformatics Graduate Program, and Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, USA.', 'United States|United States|United States|United States|United States|United States|United States', 9, 'Computational Biology|Computer Simulation|Female|Gene Regulatory Networks|Humans|Lymphoma, B-Cell|Metabolic Diseases|Ovarian Neoplasms|Sample Size|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-13-46', '22443377', 'Identification of active causal regulators is a crucial problem in understanding mechanism of diseases or finding drug targets. Methods that infer causal regulators directly from primary data have been proposed and successfully validated in some cases. These methods necessarily require very large sample sizes or a mix of different data types. Recent studies have shown that prior biological knowledge can successfully boost a methods ability to find regulators.'),
(94836, 2012, 'bmc', 'Analysis of high-depth sequence data for studying viral diversity: a comparison of next generation sequencing platforms using Segminator II', 'Archer, John|Baillie, Greg|Watson, Simon J|Kellam, Paul|Rambaut, Andrew|Robertson, David L', 'Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, UK. john.archer@manchester.ac.uk|Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, UK. john.archer@manchester.ac.uk|Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, UK. john.archer@manchester.ac.uk|Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, UK. john.archer@manchester.ac.uk|Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, UK. john.archer@manchester.ac.uk|Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, UK. john.archer@manchester.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 53, 'Genome, Viral|High-Throughput Nucleotide Sequencing|Humans|INDEL Mutation|Influenza A Virus, H1N1 Subtype|Influenza, Human|Programming Languages|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1186/1471-2105-13-47', '22443413', 'Next generation sequencing provides detailed insight into the variation present within viral populations, introducing the possibility of treatment strategies that are both reactive and predictive. Current software tools, however, need to be scaled up to accommodate for high-depth viral data sets, which are often temporally or spatially linked. In addition, due to the development of novel sequencing platforms and chemistries, each with implicit strengths and weaknesses, it will be helpful for researchers to be able to routinely compare and combine data sets from different platforms/chemistries. In particular, error associated with a specific sequencing process must be quantified so that true biological variation may be identified.'),
(94837, 2012, 'bmc', 'Mapsembler, targeted and micro assembly of large NGS datasets on a desktop computer', 'Peterlongo, Pierre|Chikhi, Rayan', 'INRIA Rennes - Bretagne Atlantique, EPI Symbiose, Rennes, France. pierre.peterlongo@inria.fr|INRIA Rennes - Bretagne Atlantique, EPI Symbiose, Rennes, France. pierre.peterlongo@inria.fr', 'France|France', 26, 'Algorithms|Breast Neoplasms|Computers|Female|Genome|Genomics|High-Throughput Nucleotide Sequencing|Humans|Oncogene Fusion|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software|Transcriptome', 'Journal Article', '10.1186/1471-2105-13-48', '22443449', 'The analysis of next-generation sequencing data from large genomes is a timely research topic. Sequencers are producing billions of short sequence fragments from newly sequenced organisms. Computational methods for reconstructing whole genomes/transcriptomes (de novo assemblers) are typically employed to process such data. However, these methods require large memory resources and computation time. Many basic biological questions could be answered targeting specific information in the reads, thus avoiding complete assembly.'),
(94838, 2012, 'bmc', 'Structural features based genome-wide characterization and prediction of nucleosome organization', 'Gan, Yanglan|Guan, Jihong|Zhou, Shuigeng|Zhang, Weixiong', 'Department of Computer Science and Technology, Tongji University, Shanghai, China.|Department of Computer Science and Technology, Tongji University, Shanghai, China.|Department of Computer Science and Technology, Tongji University, Shanghai, China.|Department of Computer Science and Technology, Tongji University, Shanghai, China.', 'China|China|China|China', 12, 'Centromere|Chromatin|DNA, Z-Form|Gene Expression Regulation, Fungal|Genome, Fungal|Genome-Wide Association Study|Markov Chains|Nucleosomes|Promoter Regions, Genetic|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-13-49', '22449207', 'Nucleosome distribution along chromatin dictates genomic DNA accessibility and thus profoundly influences gene expression. However, the underlying mechanism of nucleosome formation remains elusive. Here, taking a structural perspective, we systematically explored nucleosome formation potential of genomic sequences and the effect on chromatin organization and gene expression in S. cerevisiae.'),
(94839, 2012, 'bmc', 'The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain', 'Groza, Tudor|Hunter, Jane|Zankl, Andreas', 'School of ITEE, The University of Queensland, St, Lucia, Australia. tudor.groza@uq.edu.au|School of ITEE, The University of Queensland, St, Lucia, Australia. tudor.groza@uq.edu.au|School of ITEE, The University of Queensland, St, Lucia, Australia. tudor.groza@uq.edu.au', 'Australia|Australia|Australia', 17, 'Bone Diseases, Developmental|Databases, Genetic|Genotype|Humans|Knowledge Bases|Mutation|Phenotype|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-13-50', '22449239', 'Skeletal dysplasias are a rare and heterogeneous group of genetic disorders affecting skeletal development. Patients with skeletal dysplasias suffer from many complex medical issues including degenerative joint disease and neurological complications. Because the data and expertise associated with this field is both sparse and disparate, significant benefits will potentially accrue from the availability of an ontology that provides a shared conceptualisation of the domain knowledge and enables data integration, cross-referencing and advanced reasoning across the relevant but distributed data sources.'),
(94840, 2012, 'bmc', 'Progressive dry-core-wet-rim hydration trend in a nested-ring topology of protein binding interfaces', 'Li, Zhenhua|He, Ying|Wong, Limsoon|Li, Jinyan', 'Bioinformatics Research Center at the School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore.|Bioinformatics Research Center at the School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore.|Bioinformatics Research Center at the School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore.|Bioinformatics Research Center at the School of Computer Engineering, Nanyang Technological University, Singapore 639798, Singapore.', 'Singapore|Singapore|Singapore|Singapore', 6, '3,5-Cyclic-GMP Phosphodiesterases|Antigen-Antibody Complex|Binding Sites|Carboxypeptidases A|Crystallography, X-Ray|Desiccation|Hydrogen Bonding|Models, Molecular|Muramidase|Protease Inhibitors|Protein Binding|Protein Interaction Maps|Proteins|Software|Transducin|Water', 'Journal Article', '10.1186/1471-2105-13-51', '22452998', 'Water is an integral part of protein complexes. It shapes protein binding sites by filling cavities and it bridges local contacts by hydrogen bonds. However, water molecules are usually not included in protein interface models in the past, and few distribution profiles of water molecules in protein binding interfaces are known.'),
(94841, 2012, 'bmc', 'Detecting disease-associated genes with confounding variable adjustment and the impact on genomic meta-analysis: with application to major depressive disorder', 'Wang, Xingbin|Lin, Yan|Song, Chi|Sibille, Etienne|Tseng, George C', 'Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.|Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.|Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.|Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.|Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA 15261, USA.', 'United States|United States|United States|United States|United States', 43, 'Biomarkers|Case-Control Studies|Computer Simulation|Confounding Factors (Epidemiology)|Depressive Disorder, Major|Genomics|Humans|Meta-Analysis as Topic|Sample Size', 'Journal Article', '10.1186/1471-2105-13-52', '22458711', 'Detecting candidate markers in transcriptomic studies often encounters difficulties in complex diseases, particularly when overall signals are weak and sample size is small. Covariates including demographic, clinical and technical variables are often confounded with the underlying disease effects, which further hampers accurate biomarker detection. Our motivating example came from an analysis of five microarray studies in major depressive disorder (MDD), a heterogeneous psychiatric illness with mostly uncharacterized genetic mechanisms.'),
(94842, 2012, 'bmc', 'Mouse obesity network reconstruction with a variational Bayes algorithm to employ aggressive false positive control', 'Logsdon, Benjamin A|Hoffman, Gabriel E|Mezey, Jason G', '1Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.|1Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.|1Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.', 'United States|United States|United States', 19, 'Algorithms|Animals|Apolipoproteins E|Bayes Theorem|Computer Simulation|Humans|Mice|Mice, Inbred C3H|Mice, Inbred C57BL|Obesity|Quantitative Trait Loci', 'Journal Article', '10.1186/1471-2105-13-53', '22471599', 'We propose a novel variational Bayes network reconstruction algorithm to extract the most relevant disease factors from high-throughput genomic data-sets. Our algorithm is the only scalable method for regularized network recovery that employs Bayesian model averaging and that can internally estimate an appropriate level of sparsity to ensure few false positives enter the model without the need for cross-validation or a model selection criterion. We use our algorithm to characterize the effect of genetic markers and liver gene expression traits on mouse obesity related phenotypes, including weight, cholesterol, glucose, and free fatty acid levels, in an experiment previously used for discovery and validation of network connections: an F2 intercross between the C57BL/6 J and C3H/HeJ mouse strains, where apolipoprotein E is null on the background.'),
(94843, 2012, 'bmc', 'Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm', 'Tchagang, Alain B|Phan, Sieu|Famili, Fazel|Shearer, Heather|Fobert, Pierre|Huang, Yi|Zou, Jitao|Huang, Daiqing|Cutler, Adrian|Liu, Ziying|Pan, Youlian', 'Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca|Knowledge Discovery Group, Institute for Information Technology, National Research Council Canada, 1200 Montréal Road, Ottawa, ON K1A 0R6, Canada. alain.tchagang@nrc-cnrc.gc.ca', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 24, 'Algorithms|Animals|Arabidopsis|Brassica napus|Cluster Analysis|Cotyledon|Data Mining|Gene Expression Profiling|Malaria|Mice|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-13-54', '22475802', 'Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space.'),
(94844, 2011, 'bmc', 'Network-based functional enrichment', 'Poirel, Christopher L|Owens, Clifford C|Murali, T M', 'Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.', 'United States|United States|United States', 24, 'Algorithms|B-Lymphocytes|Cluster Analysis|DNA|Humans|Proteins', 'Journal Article', '10.1186/1471-2105-13-54', '22479706', 'Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account.'),
(94845, 2012, 'bmc', 'CLIPS-1D: analysis of multiple sequence alignments to deduce for residue-positions a role in catalysis, ligand-binding, or protein structure', 'Janda, Jan-Oliver|Busch, Markus|Kück, Fabian|Porfenenko, Mikhail|Merkl, Rainer', 'Institute of Biophysics and Physical Biochemistry, University of Regensburg, 93040 Regensburg, Germany. Rainer.Merkl@biologie.uni-regensburg.de|Institute of Biophysics and Physical Biochemistry, University of Regensburg, 93040 Regensburg, Germany. Rainer.Merkl@biologie.uni-regensburg.de|Institute of Biophysics and Physical Biochemistry, University of Regensburg, 93040 Regensburg, Germany. Rainer.Merkl@biologie.uni-regensburg.de|Institute of Biophysics and Physical Biochemistry, University of Regensburg, 93040 Regensburg, Germany. Rainer.Merkl@biologie.uni-regensburg.de|Institute of Biophysics and Physical Biochemistry, University of Regensburg, 93040 Regensburg, Germany. Rainer.Merkl@biologie.uni-regensburg.de', 'Germany|Germany|Germany|Germany|Germany', 11, 'Algorithms|Binding Sites|Catalysis|Glycerophosphates|Indole-3-Glycerol-Phosphate Synthase|Internet|Ligands|Models, Molecular|Proteins|Sequence Alignment|Sulfolobus solfataricus|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-13-55', '22480135', 'One aim of the in silico characterization of proteins is to identify all residue-positions, which are crucial for function or structure. Several sequence-based algorithms exist, which predict functionally important sites. However, with respect to sequence information, many functionally and structurally important sites are hard to distinguish and consequently a large number of incorrectly predicted functional sites have to be expected. This is why we were interested to design a new classifier that differentiates between functionally and structurally important sites and to assess its performance on representative datasets.'),
(94846, 2012, 'bmc', 'maskBAD--a package to detect and remove Affymetrix probes with binding affinity differences', 'Dannemann, Michael|Lachmann, Michael|Lorenc, Anna', 'Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany.|Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany.|Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany.', 'Germany|Germany|Germany', 0, 'Animals|Artifacts|Computational Biology|Electronic Data Processing|Gene Expression Profiling|Humans|INDEL Mutation|Mice|Mice, Inbred C57BL|Mice, Inbred DBA|Nucleic Acid Probes|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1186/1471-2105-13-56', '22507266', 'Hybridization differences caused by target sequence differences can be a confounding factor in analyzing gene expression on microarrays, lead to false positives and reduce power to detect real expression differences. We prepared an R Bioconductor compatible package to detect, characterize and remove such probes in Affymetrix 3IVT and exon-based arrays on the basis of correlation of signal intensities from probes within probe sets.'),
(94847, 2011, 'bmc', 'Proceedings of the 2010 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference, April 1-2, 2011, College Station, Texas', '-', '-', '-', 4, 'Animals|Computational Biology|Humans', 'Congress', '10.1186/1471-2105-13-56', '22509517', '-'),
(94848, 2012, 'bmc', 'F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks', 'Larhlimi, Abdelhalim|David, Laszlo|Selbig, Joachim|Bockmayr, Alexander', 'Department of Bioinformatics, Institute for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str, 24-25, D-14476 Potsdam, Germany. Larhlimi@mpimp-golm.mpg.de|Department of Bioinformatics, Institute for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str, 24-25, D-14476 Potsdam, Germany. Larhlimi@mpimp-golm.mpg.de|Department of Bioinformatics, Institute for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str, 24-25, D-14476 Potsdam, Germany. Larhlimi@mpimp-golm.mpg.de|Department of Bioinformatics, Institute for Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str, 24-25, D-14476 Potsdam, Germany. Larhlimi@mpimp-golm.mpg.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Computational Biology|Genome|Metabolic Networks and Pathways|Models, Biological|Software', 'Evaluation Studies', '10.1186/1471-2105-13-57', '22524245', 'Flux coupling analysis (FCA) has become a useful tool in the constraint-based analysis of genome-scale metabolic networks. FCA allows detecting dependencies between reaction fluxes of metabolic networks at steady-state. On the one hand, this can help in the curation of reconstructed metabolic networks by verifying whether the coupling between reactions is in agreement with the experimental findings. On the other hand, FCA can aid in defining intervention strategies to knock out target reactions.'),
(94849, 2012, 'bmc', 'Methods for visual mining of genomic and proteomic data atlases', 'Boyle, John|Kreisberg, Richard|Bressler, Ryan|Killcoyne, Sarah', 'Institute for Systems Biology, 401 Terry Ave N, Seattle, WA 98092, USA. john.boyle@systemsbiology.org|Institute for Systems Biology, 401 Terry Ave N, Seattle, WA 98092, USA. john.boyle@systemsbiology.org|Institute for Systems Biology, 401 Terry Ave N, Seattle, WA 98092, USA. john.boyle@systemsbiology.org|Institute for Systems Biology, 401 Terry Ave N, Seattle, WA 98092, USA. john.boyle@systemsbiology.org', 'United States|United States|United States|United States', 0, 'Colonic Neoplasms|Data Mining|Female|Genomics|Glioblastoma|Humans|Mass Spectrometry|Neoplasms|Ovarian Neoplasms|Proteomics|Software', 'Journal Article', '10.1186/1471-2105-13-58', '22524279', 'As the volume, complexity and diversity of the information that scientists work with on a daily basis continues to rise, so too does the requirement for new analytic software. The analytic software must solve the dichotomy that exists between the need to allow for a high level of scientific reasoning, and the requirement to have an intuitive and easy to use tool which does not require specialist, and often arduous, training to use. Information visualization provides a solution to this problem, as it allows for direct manipulation and interaction with diverse and complex data. The challenge addressing bioinformatics researches is how to apply this knowledge to data sets that are continually growing in a field that is rapidly changing.'),
(94850, 2012, 'bmc', 'A comparison of feature selection and classification methods in DNA methylation studies using the Illumina Infinium platform', 'Zhuang, Joanna|Widschwendter, Martin|Teschendorff, Andrew E', 'Statistical Genomics Group, Paul OGorman Building, UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6BT, UK.|Statistical Genomics Group, Paul OGorman Building, UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6BT, UK.|Statistical Genomics Group, Paul OGorman Building, UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6BT, UK.', 'United Kingdom|United Kingdom|United Kingdom', 66, 'Algorithms|DNA Methylation|Gene Expression Profiling|Humans|Neoplasms|Principal Component Analysis|Sample Size|Software|Support Vector Machine', 'Comparative Study', '10.1186/1471-2105-13-59', '22524302', 'The 27k Illumina Infinium Methylation Beadchip is a popular high-throughput technology that allows the methylation state of over 27,000 CpGs to be assayed. While feature selection and classification methods have been comprehensively explored in the context of gene expression data, relatively little is known as to how best to perform feature selection or classification in the context of Illumina Infinium methylation data. Given the rising importance of epigenomics in cancer and other complex genetic diseases, and in view of the upcoming epigenome wide association studies, it is critical to identify the statistical methods that offer improved inference in this novel context.'),
(94851, 2012, 'bmc', 'Is EC class predictable from reaction mechanism?', 'Nath, Neetika|Mitchell, John B O', 'Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland KY16 9ST, UK.|Biomedical Sciences Research Complex and EaStCHEM School of Chemistry, Purdie Building, University of St Andrews, North Haugh, St Andrews, Scotland KY16 9ST, UK.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Artificial Intelligence|Cluster Analysis|Databases, Protein|Enzymes|Models, Chemical|Support Vector Machine|Terminology as Topic', 'Journal Article', '10.1186/1471-2105-13-60', '22530800', 'We investigate the relationships between the EC (Enzyme Commission) class, the associated chemical reaction, and the reaction mechanism by building predictive models using Support Vector Machine (SVM), Random Forest (RF) and k-Nearest Neighbours (kNN). We consider two ways of encoding the reaction mechanism in descriptors, and also three approaches that encode only the overall chemical reaction. Both cross-validation and also an external test set are used.'),
(94852, 2012, 'bmc', 'EnzML: multi-label prediction of enzyme classes using InterPro signatures', 'De Ferrari, Luna|Aitken, Stuart|van Hemert, Jano|Goryanin, Igor', 'Computational Systems Biology and Bioinformatics, School of Informatics, University of Edinburgh, Informatics Forum, 10 Crichton Street, UK. luna.deferrari@ed.ac.uk|Computational Systems Biology and Bioinformatics, School of Informatics, University of Edinburgh, Informatics Forum, 10 Crichton Street, UK. luna.deferrari@ed.ac.uk|Computational Systems Biology and Bioinformatics, School of Informatics, University of Edinburgh, Informatics Forum, 10 Crichton Street, UK. luna.deferrari@ed.ac.uk|Computational Systems Biology and Bioinformatics, School of Informatics, University of Edinburgh, Informatics Forum, 10 Crichton Street, UK. luna.deferrari@ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 31, 'Algorithms|Animals|Arabidopsis|Artificial Intelligence|Computational Biology|Databases, Protein|Drosophila|Enzymes|Escherichia coli|Humans|Methanococcus|Mice|Proteome|Rats|Schizosaccharomyces|Software', 'Journal Article', '10.1186/1471-2105-13-61', '22533924', 'Manual annotation of enzymatic functions cannot keep up with automatic genome sequencing. In this work we explore the capacity of InterPro sequence signatures to automatically predict enzymatic function.'),
(94853, 2012, 'bmc', 'CBDB: the codon bias database', 'Hilterbrand, Adam|Saelens, Joseph|Putonti, Catherine', 'Department of Biology, Loyola University Chicago, 1032 W Sheridan Road, Chicago, IL 60660, USA.|Department of Biology, Loyola University Chicago, 1032 W Sheridan Road, Chicago, IL 60660, USA.|Department of Biology, Loyola University Chicago, 1032 W Sheridan Road, Chicago, IL 60660, USA.', 'United States|United States|United States', 0, 'Bacteria|Bacteriophages|Codon|Databases, Nucleic Acid|Genome, Bacterial|Internet|Mutation', 'Journal Article', '10.1186/1471-2105-13-62', '22536831', 'In many genomes, a clear preference in the usage of particular codons exists. The mechanisms that induce codon biases remain an open question, studies have attributed codon usage to translational selection, mutational bias and drift. Furthermore, correlations between codon usage within host genomes and their viral pathogens have been observed for a myriad of host-virus systems. As such, numerous studies have investigated codon usage and codon bias in an effort to better understand how species evolve. Numerous metrics have been developed to identify biases in codon usage. In addition, a few data repositories of codon bias data are available, differing in the metrics reported as well as the number and taxonomy of strains examined.'),
(94854, 2012, 'bmc', 'Proceedings from the Great Lakes Bioinformatics Conference 2011 Preface', 'Colvin, Robert A|Liu, Jundong', 'Department of Biology, Loyola University Chicago, 1032 W Sheridan Road, Chicago, IL 60660, USA.|Department of Biology, Loyola University Chicago, 1032 W Sheridan Road, Chicago, IL 60660, USA.', 'United States|United States', 0, 'Computational Biology|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|Proteins', 'Introductory Journal Article', '10.1186/1471-2105-13-S2-I1', '22536859', '-'),
(94855, 2012, 'bmc', 'Reordering based integrative expression profiling for microarray classification', 'Wu, Xiaogang|Huang, Hui|Sonachalam, Madhankumar|Reinhard, Sina|Shen, Jeffrey|Pandey, Ragini|Chen, Jake Y', 'School of Informatics, Indiana University, Indianapolis, IN 46202, USA.|School of Informatics, Indiana University, Indianapolis, IN 46202, USA.|School of Informatics, Indiana University, Indianapolis, IN 46202, USA.|School of Informatics, Indiana University, Indianapolis, IN 46202, USA.|School of Informatics, Indiana University, Indianapolis, IN 46202, USA.|School of Informatics, Indiana University, Indianapolis, IN 46202, USA.|School of Informatics, Indiana University, Indianapolis, IN 46202, USA.', 'India|India|India|India|India|India|India', 0, 'Algorithms|Alzheimer Disease|Cluster Analysis|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping', 'Journal Article', '10.1186/1471-2105-13-S2-S1', '22536860', 'Current network-based microarray analysis uses the information of interactions among concerned genes/gene products, but still considers each gene expression individually. We propose an organized knowledge-supervised approach - Integrative eXpression Profiling (IXP), to improve microarray classification accuracy, and help discover groups of genes that have been too weak to detect individually by traditional ways. To implement IXP, ant colony optimization reordering (ACOR) algorithm is used to group functionally related genes in an ordered way.'),
(94856, 2012, 'bmc', 'Matching phosphorylation response patterns of antigen-receptor-stimulated T cells via flow cytometry', 'Azad, Ariful|Pyne, Saumyadipta|Pothen, Alex', 'Department of Computer Science, Purdue University, West Lafayette, IN 47906, USA.|Department of Computer Science, Purdue University, West Lafayette, IN 47906, USA.|Department of Computer Science, Purdue University, West Lafayette, IN 47906, USA.', 'United States|United States|United States', 11, 'Algorithms|Flow Cytometry|Humans|Phosphorylation|Receptors, Antigen, T-Cell|T-Lymphocytes', 'Journal Article', '10.1186/1471-2105-13-S2-S10', '22536861', 'When flow cytometric data on mixtures of cell populations are collected from samples under different experimental conditions, computational methods are needed (a) to classify the samples into similar groups, and (b) to characterize the changes within the corresponding populations due to the different conditions. Manual inspection has been used in the past to study such changes, but high-dimensional experiments necessitate developing new computational approaches to this problem. A robust solution to this problem is to construct distinct templates to summarize all samples from a class, and then to compare these templates to study the changes across classes or conditions.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94857, 2012, 'bmc', 'Fold change and p-value cutoffs significantly alter microarray interpretations', 'Dalman, Mark R|Deeter, Anthony|Nimishakavi, Gayathri|Duan, Zhong-Hui', 'Department of Biology, University of Akron, Akron, OH, USA. mrd31@zips.uakron.edu|Department of Biology, University of Akron, Akron, OH, USA. mrd31@zips.uakron.edu|Department of Biology, University of Akron, Akron, OH, USA. mrd31@zips.uakron.edu|Department of Biology, University of Akron, Akron, OH, USA. mrd31@zips.uakron.edu', 'United States|United States|United States|United States', 0, 'Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-13-S2-S11', '22536862', 'As context is important to gene expression, so is the preprocessing of microarray to transcriptomics. Microarray data suffers from several normalization and significance problems. Arbitrary fold change (FC) cut-offs of >2 and significance p-values of <0.02 lead data collection to look only at genes which vary wildly amongst other genes. Therefore, questions arise as to whether the biology or the statistical cutoff are more important within the interpretation. In this paper, we reanalyzed a zebrafish (D. rerio) microarray data set using GeneSpring and different differential gene expression cut-offs and found the data interpretation was drastically different. Furthermore, despite the advances in microarray technology, the array captures a large portion of genes known but yet still leaving large voids in the number of genes assayed, such as leptin a pleiotropic hormone directly related to hypoxia-induced angiogenesis.'),
(94858, 2012, 'bmc', 'Predicting glioblastoma prognosis networks using weighted gene co-expression network analysis on TCGA data', 'Xiang, Yang|Zhang, Cun-Quan|Huang, Kun', 'Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.|Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.|Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.', 'United States|United States|United States', 24, 'Adult|Aged|Algorithms|Female|Gene Expression Profiling|Gene Regulatory Networks|Glioblastoma|Humans|Kaplan-Meier Estimate|Male|Middle Aged|Prognosis', 'Journal Article', '10.1186/1471-2105-13-S2-S12', '22536863', 'Using gene co-expression analysis, researchers were able to predict clusters of genes with consistent functions that are relevant to cancer development and prognosis. We applied a weighted gene co-expression network (WGCN) analysis algorithm on glioblastoma multiforme (GBM) data obtained from the TCGA project and predicted a set of gene co-expression networks which are related to GBM prognosis.'),
(94859, 2012, 'bmc', 'Computational and experimental analyses of retrotransposon-associated minisatellite DNAs in the soybean genome', 'Mogil, Lauren S|Slowikowski, Kamil|Laten, Howard M', 'Program in Bioinformatics, Loyola University Chicago, 1032 W, Sheridan Rd, Chicago, IL 60660, USA.|Program in Bioinformatics, Loyola University Chicago, 1032 W, Sheridan Rd, Chicago, IL 60660, USA.|Program in Bioinformatics, Loyola University Chicago, 1032 W, Sheridan Rd, Chicago, IL 60660, USA.', 'United States|United States|United States', 3, 'Chromosome Mapping|DNA, Plant|Genome, Plant|Minisatellite Repeats|Retroelements|Soybeans', 'Journal Article', '10.1186/1471-2105-13-S2-S13', '22536864', 'Retrotransposons are mobile DNA elements that spread through genomes via the action of element-encoded reverse transcriptases. They are ubiquitous constituents of most eukaryotic genomes, especially those of higher plants. The pericentromeric regions of soybean (Glycine max) chromosomes contain >3,200 intact copies of the Gmr9/GmOgre retrotransposon. Between the 3 end of the coding region and the long terminal repeat, this retrotransposon family contains a polymorphic minisatellite region composed of five distinct, interleaved minisatellite families. To better understand the possible role and origin of retrotransposon-associated minisatellites, a computational project to map and physically characterize all members of these families in the G. max genome, irrespective of their association with Gmr9, was undertaken.'),
(94860, 2012, 'bmc', 'A signal processing approach for enriched region detection in RNA polymerase II ChIP-seq data', 'Han, Zhi|Tian, Lu|Pécot, Thierry|Huang, Tim|Machiraju, Raghu|Huang, Kun', 'College of Software, Nankai University, Tianjin, China.|College of Software, Nankai University, Tianjin, China.|College of Software, Nankai University, Tianjin, China.|College of Software, Nankai University, Tianjin, China.|College of Software, Nankai University, Tianjin, China.|College of Software, Nankai University, Tianjin, China.', 'China|China|China|China|China|China', 0, 'Algorithms|Breast Neoplasms|Cell Line, Tumor|Chromatin Immunoprecipitation|Female|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Male|Prostatic Neoplasms|RNA Polymerase II|Sequence Analysis, DNA|Signal Processing, Computer-Assisted', 'Evaluation Studies', '10.1186/1471-2105-13-S2-S2', '22536865', 'RNA polymerase II (PolII) is essential in gene transcription and ChIP-seq experiments have been used to study PolII binding patterns over the entire genome. However, since PolII enriched regions in the genome can be very long, existing peak finding algorithms for ChIP-seq data are not adequate for identifying such long regions.'),
(94861, 2012, 'bmc', 'Amino acid function and docking site prediction through combining disease variants, structure alignments, sequence alignments, and molecular dynamics: a study of the HMG domain', 'Prokop, Jeremy W|Leeper, Thomas C|Duan, Zhong-Hui|Milsted, Amy', 'Department of Biology, Program in Integrated Bioscience, The University of Akron, Akron, OH, USA. jwp7@zips.uakron.edu|Department of Biology, Program in Integrated Bioscience, The University of Akron, Akron, OH, USA. jwp7@zips.uakron.edu|Department of Biology, Program in Integrated Bioscience, The University of Akron, Akron, OH, USA. jwp7@zips.uakron.edu|Department of Biology, Program in Integrated Bioscience, The University of Akron, Akron, OH, USA. jwp7@zips.uakron.edu', 'United States|United States|United States|United States', 0, 'Amino Acids|DNA|Disease|Genetic Variation|HMG-Box Domains|High Mobility Group Proteins|Humans|Molecular Dynamics Simulation|Protein Structure, Secondary|Sequence Alignment|Sequence Analysis, Protein|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-13-S2-S3', '22536866', 'The DNA binding domain of HMG proteins is known to be important in many diseases, with the Sox sub-family of HMG proteins of particular significance. Numerous natural variants in HMG proteins are associated with disease phenotypes. Integrating these natural variants, molecular dynamic simulations of DNA interaction and sequence and structure alignments give detailed molecular knowledge of potential amino acid function such as DNA or protein interaction.'),
(94862, 2012, 'bmc', 'THINK Back: KNowledge-based Interpretation of High Throughput data', 'Farfán, Fernando|Ma, Jun|Sartor, Maureen A|Michailidis, George|Jagadish, Hosagrahar V', 'Computer Science and Engineering Department, University of Michigan, Ann Arbor, MI, USA. ffarfan@umich.edu|Computer Science and Engineering Department, University of Michigan, Ann Arbor, MI, USA. ffarfan@umich.edu|Computer Science and Engineering Department, University of Michigan, Ann Arbor, MI, USA. ffarfan@umich.edu|Computer Science and Engineering Department, University of Michigan, Ann Arbor, MI, USA. ffarfan@umich.edu|Computer Science and Engineering Department, University of Michigan, Ann Arbor, MI, USA. ffarfan@umich.edu', 'United States|United States|United States|United States|United States', 8, 'Genes|High-Throughput Nucleotide Sequencing|Internet|Knowledge Bases|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-13-S2-S4', '22536867', 'Results of high throughput experiments can be challenging to interpret. Current approaches have relied on bulk processing the set of expression levels, in conjunction with easily obtained external evidence, such as co-occurrence. While such techniques can be used to reason probabilistically, they are not designed to shed light on what any individual gene, or a network of genes acting together, may be doing. Our belief is that today we have the information extraction ability and the computational power to perform more sophisticated analyses that consider the individual situation of each gene. The use of such techniques should lead to qualitatively superior results. The specific aim of this project is to develop computational techniques to generate a small number of biologically meaningful hypotheses based on observed results from high throughput microarray experiments, gene sequences, and next-generation sequences. Through the use of relevant known biomedical knowledge, as represented in published literature and public databases, we can generate meaningful hypotheses that will aide biologists to interpret their experimental data. We are currently developing novel approaches that exploit the rich information encapsulated in biological pathway graphs. Our methods perform a thorough and rigorous analysis of biological pathways, using complex factors such as the topology of the pathway graph and the frequency in which genes appear on different pathways, to provide more meaningful hypotheses to describe the biological phenomena captured by high throughput experiments, when compared to other existing methods that only consider partial information captured by biological pathways.'),
(94863, 2012, 'bmc', 'Interfacing medicinal chemistry with structural bioinformatics: implications for T box riboswitch RNA drug discovery', 'Jentzsch, Franziska|Hines, Jennifer V', 'Department of Chemistry, Leipzig University, Leipzig, Germany.|Department of Chemistry, Leipzig University, Leipzig, Germany.', 'Germany|Germany', 6, 'Amino Acyl-tRNA Synthetases|Computational Biology|Drug Discovery|RNA, Bacterial|Riboswitch|Terminator Regions, Genetic', 'Journal Article', '10.1186/1471-2105-13-S2-S5', '22536868', 'The T box riboswitch controls bacterial transcription by structurally responding to tRNA aminoacylation charging ratios. Knowledge of the thermodynamic stability difference between two competing structural elements within the riboswitch, the terminator and the antiterminator, is critical for effective T box-targeted drug discovery.'),
(94864, 2012, 'bmc', 'Evaluation of multiple protein docking structures using correctly predicted pairwise subunits', 'Esquivel-Rodríguez, Juan|Kihara, Daisuke', 'Department of Computer Science, College of Science, Purdue University, West Lafayette, IN 47907, USA.|Department of Computer Science, College of Science, Purdue University, West Lafayette, IN 47907, USA.', 'United States|United States', 7, 'Computational Biology|Humans|Models, Molecular|Molecular Docking Simulation|Multiprotein Complexes|Protein Conformation|Protein Subunits', 'Journal Article', '10.1186/1471-2105-13-S2-S6', '22536869', 'Many functionally important proteins in a cell form complexes with multiple chains. Therefore, computational prediction of multiple protein complexes is an important task in bioinformatics. In the development of multiple protein docking methods, it is important to establish a metric for evaluating prediction results in a reasonable and practical fashion. However, since there are only few works done in developing methods for multiple protein docking, there is no study that investigates how accurate structural models of multiple protein complexes should be to allow scientists to gain biological insights.'),
(94865, 2012, 'bmc', 'Constructing patch-based ligand-binding pocket database for predicting function of proteins', 'Sael, Lee|Kihara, Daisuke', 'Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA.|Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA.', 'United States|United States', 7, 'Algorithms|Binding Sites|Databases, Protein|Humans|Ligands|Protein Conformation|Proteins', 'Journal Article', '10.1186/1471-2105-13-S2-S7', '22536870', 'Many of solved tertiary structures of unknown functions do not have global sequence and structural similarities to proteins of known function. Often functional clues of unknown proteins can be obtained by predicting small ligand molecules that bind to the proteins.'),
(94866, 2012, 'bmc', 'Convergence of genetic influences in comorbidity', 'McEachin, Richard C|Sannareddy, Keerthi S|Cavalcoli, James D|Karnovsky, Alla|Vink, Jacqueline M|Sartor, Maureen A', 'Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48105, USA. mceachin@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48105, USA. mceachin@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48105, USA. mceachin@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48105, USA. mceachin@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48105, USA. mceachin@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48105, USA. mceachin@umich.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Comorbidity|Genome-Wide Association Study|Genotype|Humans|Linkage Disequilibrium|Phenotype|Polymorphism, Single Nucleotide|Substance-Related Disorders|Tobacco Use Disorder', 'Journal Article', '10.1186/1471-2105-13-S2-S8', '22536871', 'Predisposition to complex diseases is explained in part by genetic variation, and complex diseases are frequently comorbid, consistent with pleiotropic genetic variation influencing comorbidity. Genome Wide Association (GWA) studies typically assess association between SNPs and a single-disease phenotype. Fisher meta-analysis combines evidence of association from single-disease GWA studies, assuming that each study is an independent test of the same hypothesis. The Rank Product (RP) method overcomes limitations posed by Fisher assumptions, though RP was not designed for GWA data.'),
(94867, 2012, 'bmc', 'Interpolative multidimensional scaling techniques for the identification of clusters in very large sequence sets', 'Hughes, Adam|Ruan, Yang|Ekanayake, Saliya|Bae, Seung-Hee|Dong, Qunfeng|Rho, Mina|Qiu, Judy|Fox, Geoffrey', 'Pervasive Technology Institute, Indiana University, Bloomington, IN 47408, USA.|Pervasive Technology Institute, Indiana University, Bloomington, IN 47408, USA.|Pervasive Technology Institute, Indiana University, Bloomington, IN 47408, USA.|Pervasive Technology Institute, Indiana University, Bloomington, IN 47408, USA.|Pervasive Technology Institute, Indiana University, Bloomington, IN 47408, USA.|Pervasive Technology Institute, Indiana University, Bloomington, IN 47408, USA.|Pervasive Technology Institute, Indiana University, Bloomington, IN 47408, USA.|Pervasive Technology Institute, Indiana University, Bloomington, IN 47408, USA.', 'India|India|India|India|India|India|India|India', 0, 'Algorithms|Cluster Analysis|Metagenomics|RNA, Ribosomal, 16S|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-13-S2-S9', '22536872', 'Modern pyrosequencing techniques make it possible to study complex bacterial populations, such as 16S rRNA, directly from environmental or clinical samples without the need for laboratory purification. Alignment of sequences across the resultant large data sets (100,000+ sequences) is of particular interest for the purpose of identifying potential gene clusters and families, but such analysis represents a daunting computational task. The aim of this work is the development of an efficient pipeline for the clustering of large sequence read sets.'),
(94868, 2012, 'bmc', 'Learning pair-wise gene functional similarity by multiplex gene expression maps', 'An, Li|Ling, Haibin|Obradovic, Zoran|Smith, Desmond J|Megalooikonomou, Vasileios', 'Data Engineering Laboratory, Department of Computer and Information Sciences, Temple University, PA, USA. anli@temple.edu|Data Engineering Laboratory, Department of Computer and Information Sciences, Temple University, PA, USA. anli@temple.edu|Data Engineering Laboratory, Department of Computer and Information Sciences, Temple University, PA, USA. anli@temple.edu|Data Engineering Laboratory, Department of Computer and Information Sciences, Temple University, PA, USA. anli@temple.edu|Data Engineering Laboratory, Department of Computer and Information Sciences, Temple University, PA, USA. anli@temple.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Artificial Intelligence|Brain|Mice|Regression Analysis|Transcriptome', 'Journal Article', '10.1186/1471-2105-13-S3-S1', '22536893', 'The relationships between the gene functional similarity and gene expression profile, and between gene function annotation and gene sequence have been studied extensively. However, not much work has considered the connection between gene functions and location of a genes expression in the mammalian tissues. On the other hand, although unsupervised learning methods have been commonly used in functional genomics, supervised learning cannot be directly applied to a set of normal genes without having a target (class) attribute.'),
(94869, 2012, 'bmc', 'FUSE: a profit maximization approach for functional summarization of biological networks', 'Seah, Boon-Siew|Bhowmick, Sourav S|Dewey, C Forbes|Yu, Hanry', 'School of Computer Engineering, Nanyang Technological University, Singapore. seah0097@ntu.edu.sg|School of Computer Engineering, Nanyang Technological University, Singapore. seah0097@ntu.edu.sg|School of Computer Engineering, Nanyang Technological University, Singapore. seah0097@ntu.edu.sg|School of Computer Engineering, Nanyang Technological University, Singapore. seah0097@ntu.edu.sg', 'Singapore|Singapore|Singapore|Singapore', 7, 'Algorithms|Alzheimer Disease|Cluster Analysis|Humans|Protein Interaction Maps|Proteins', 'Journal Article', '10.1186/1471-2105-13-S3-S10', '22536894', 'The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein interaction network (PPI) using graph theoretic analysis. Despite the recent progress, systems level analysis of PPIS remains a daunting task as it is challenging to make sense out of the deluge of high-dimensional interaction data. Specifically, techniques that automatically abstract and summarize PPIS at multiple resolutions to provide high level views of its functional landscape are still lacking. We present a novel data-driven and generic algorithm called FUSE (Functional Summary Generator) that generates functional maps of a PPI at different levels of organization, from broad process-process level interactions to in-depth complex-complex level interactions, through a pro t maximization approach that exploits Minimum Description Length (MDL) principle to maximize information gain of the summary graph while satisfying the level of detail constraint.'),
(94870, 2012, 'bmc', 'Scalable global alignment for multiple biological networks', 'Shih, Yu-Keng|Parthasarathy, Srinivasan', 'Department of Computer Science and Engineering, Ohio State University, Columbus, OH, USA.|Department of Computer Science and Engineering, Ohio State University, Columbus, OH, USA.', 'United States|United States', 26, 'Algorithms|Amino Acid Sequence|Animals|Cluster Analysis|Computational Biology|Humans|Protein Interaction Maps|Proteins|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-13-S3-S11', '22536895', 'Advances in high-throughput technology has led to an increased amount of available data on protein-protein interaction (PPI) data. Detecting and extracting functional modules that are common across multiple networks is an important step towards understanding the role of functional modules and how they have evolved across species. A global protein-protein interaction network alignment algorithm attempts to find such functional orthologs across multiple networks.'),
(94871, 2012, 'bmc', 'Genome-scale NCRNA homology search using a Hamming distance-based filtration strategy', 'Sun, Yanni|Aljawad, Osama|Lei, Jikai|Liu, Alex', 'Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA. yannisun@msu.edu|Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA. yannisun@msu.edu|Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA. yannisun@msu.edu|Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA. yannisun@msu.edu', 'United States|United States|United States|United States', 3, 'Algorithms|Animals|Base Sequence|Burkholderia cenocepacia|Conserved Sequence|Genome|Genome, Bacterial|Humans|Mice|Molecular Sequence Data|RNA, Bacterial|RNA, Untranslated|Ralstonia solanacearum|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-13-S3-S12', '22536896', 'NCRNAs (noncoding RNAs) play important roles in many biological processes. Existing genome-scale ncRNA search tools identify ncRNAs in local sequence alignments generated by conventional sequence comparison methods. However, some types of ncRNA lack strong sequence conservation and tend to be missed or mis-aligned by conventional sequence comparison.'),
(94872, 2012, 'bmc', 'Comparative analysis and visualization of multiple collinear genomes', 'Wang, Jeremy R|de Villena, Fernando Pardo-Manuel|McMillan, Leonard', 'Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. jrwang@cs.unc.edu|Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. jrwang@cs.unc.edu|Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. jrwang@cs.unc.edu', 'United States|United States|United States', 29, 'Animals|Cluster Analysis|Genome|Internet|Mice|Mice, Inbred Strains|Phylogeny|Polymorphism, Single Nucleotide|Software', 'Comparative Study', '10.1186/1471-2105-13-S3-S13', '22536897', 'Genome browsers are a common tool used by biologists to visualize genomic features including genes, polymorphisms, and many others. However, existing genome browsers and visualization tools are not well-suited to perform meaningful comparative analysis among a large number of genomes. With the increasing quantity and availability of genomic data, there is an increased burden to provide useful visualization and analysis tools for comparison of multiple collinear genomes such as the large panels of model organisms which are the basis for much of the current genetic research.'),
(94873, 2012, 'bmc', 'Efficient path-based computations on pedigree graphs with compact encodings', 'Yang, Lei|Cheng, En|xc3x96zsoyoxc4x9flu, Z Meral', 'Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH, USA. lxy105@case.edu|Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH, USA. lxy105@case.edu|Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, OH, USA. lxy105@case.edu', 'United States|United States|United States', 1, 'Adenomatous Polyposis Coli|Algorithms|Consanguinity|Female|Genealogy and Heraldry|Humans|Inheritance Patterns|Male|Pedigree', 'Journal Article', '10.1186/1471-2105-13-S3-S14', '22536898', 'A pedigree is a diagram of family relationships, and it is often used to determine the mode of inheritance (dominant, recessive, etc.) of genetic diseases. Along with rapidly growing knowledge of genetics and accumulation of genealogy information, pedigree data is becoming increasingly important. In large pedigree graphs, path-based methods for efficiently computing genealogical measurements, such as inbreeding and kinship coefficients of individuals, depend on efficient identification and processing of paths. In this paper, we propose a new compact path encoding scheme on large pedigrees, accompanied by an efficient algorithm for identifying paths. We demonstrate the utilization of our proposed method by applying it to the inbreeding coefficient computation. We present time and space complexity analysis, and also manifest the efficiency of our method for evaluating inbreeding coefficients as compared to previous methods by experimental results using pedigree graphs with real and synthetic data. Both theoretical and experimental results demonstrate that our method is more scalable and efficient than previous methods in terms of time and space requirements.'),
(94874, 2012, 'bmc', 'A novel k-mer mixture logistic regression for methylation susceptibility modeling of CpG dinucleotides in human gene promoters', 'Yang, Youngik|Nephew, Kenneth|Kim, Sun', 'J Craig Venter Institute, San Diego, CA, USA.|J Craig Venter Institute, San Diego, CA, USA.|J Craig Venter Institute, San Diego, CA, USA.', 'United States|United States|United States', 11, 'Chromosomes, Human, Pair 21|CpG Islands|DNA Methylation|Down Syndrome|Humans|Logistic Models|Models, Genetic|Neoplasms|Promoter Regions, Genetic', 'Journal Article', '10.1186/1471-2105-13-S3-S15', '22536899', 'DNA methylation is essential for normal development and differentiation and plays a crucial role in the development of nearly all types of cancer. Aberrant DNA methylation patterns, including genome-wide hypomethylation and region-specific hypermethylation, are frequently observed and contribute to the malignant phenotype. A number of studies have recently identified distinct features of genomic sequences that can be used for modeling specific DNA sequences that may be susceptible to aberrant CpG methylation in both cancer and normal cells. Although it is now possible, using next generation sequencing technologies, to assess human methylomes at base resolution, no reports currently exist on modeling cell type-specific DNA methylation susceptibility. Thus, we conducted a comprehensive modeling study of cell type-specific DNA methylation susceptibility at three different resolutions: CpG dinucleotides, CpG segments, and individual gene promoter regions.'),
(94875, 2012, 'bmc', 'Metabolic network alignment in large scale by network compression', 'Ay, Ferhat|Dang, Michael|Kahveci, Tamer', 'Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA. ferhatay@uw.edu|Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA. ferhatay@uw.edu|Computer and Information Science and Engineering, University of Florida, Gainesville, FL 32611, USA. ferhatay@uw.edu', 'United States|United States|United States', 6, 'Algorithms|Animals|Computational Biology|Data Compression|Databases, Genetic|Humans|Metabolic Networks and Pathways|Mice', 'Journal Article', '10.1186/1471-2105-13-S3-S2', '22536900', 'Metabolic network alignment is a system scale comparative analysis that discovers important similarities and differences across different metabolisms and organisms. Although the problem of aligning metabolic networks has been considered in the past, the computational complexity of the existing solutions has so far limited their use to moderately sized networks. In this paper, we address the problem of aligning two metabolic networks, particularly when both of them are too large to be dealt with using existing methods. We develop a generic framework that can significantly improve the scale of the networks that can be aligned in practical time. Our framework has three major phases, namely the compression phase, the alignment phase and the refinement phase. For the first phase, we develop an algorithm which transforms the given networks to a compressed domain where they are summarized using fewer nodes, termed supernodes, and interactions. In the second phase, we carry out the alignment in the compressed domain using an existing network alignment method as our base algorithm. This alignment results in supernode mappings in the compressed domain, each of which are smaller instances of network alignment problem. In the third phase, we solve each of the instances using the base alignment algorithm to refine the alignment results. We provide a user defined parameter to control the number of compression levels which generally determines the tradeoff between the quality of the alignment versus how fast the algorithm runs. Our experiments on the networks from KEGG pathway database demonstrate that the compression method we propose reduces the sizes of metabolic networks by almost half at each compression level which provides an expected speedup of more than an order of magnitude. We also observe that the alignments obtained by only one level of compression capture the original alignment results with high accuracy. Together, these suggest that our framework results in alignments that are comparable to existing algorithms and can do this with practical resource utilization for large scale networks that existing algorithms could not handle. As an example of our methods performance in practice, the alignment of organism-wide metabolic networks of human (1615 reactions) and mouse (1600 reactions) was performed under three minutes by only using a single level of compression.'),
(94876, 2012, 'bmc', 'Algorithms for optimizing cross-overs in DNA shuffling', 'He, Lu|Friedman, Alan M|Bailey-Kellogg, Chris', 'Dept of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH 03755, USA.|Dept of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH 03755, USA.|Dept of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH 03755, USA.', 'United States|United States|United States', 4, 'African Swine Fever Virus|Algorithms|Amino Acid Sequence|Animals|Bacteria|Codon|DNA Shuffling|Escherichia coli|Gene Library|Humans|Phosphoribosylglycinamide Formyltransferase|Protein Engineering|Rats|Sequence Alignment|Software|beta-Lactamases', 'Journal Article', '10.1186/1471-2105-13-S3-S3', '22536901', 'DNA shuffling generates combinatorial libraries of chimeric genes by stochastically recombining parent genes. The resulting libraries are subjected to large-scale genetic selection or screening to identify those chimeras with favorable properties (e.g., enhanced stability or enzymatic activity). While DNA shuffling has been applied quite successfully, it is limited by its homology-dependent, stochastic nature. Consequently, it is used only with parents of sufficient overall sequence identity, and provides no control over the resulting chimeric library.'),
(94877, 2012, 'bmc', 'Combining automated peak tracking in SAR by NMR with structure-based backbone assignment from 15N-NOESY', 'Jang, Richard|Gao, Xin|Li, Ming', 'David R Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada.|David R Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada.|David R Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada.', 'Canada|Canada|Canada', 10, 'Algorithms|Bacteria|Humans|Models, Chemical|Models, Molecular|Nuclear Magnetic Resonance, Biomolecular|Plants|Proteins|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-13-S3-S4', '22536902', 'Chemical shift mapping is an important technique in NMR-based drug screening for identifying the atoms of a target protein that potentially bind to a drug molecule upon the molecules introduction in increasing concentrations. The goal is to obtain a mapping of peaks with known residue assignment from the reference spectrum of the unbound protein to peaks with unknown assignment in the target spectrum of the bound protein. Although a series of perturbed spectra help to trace a path from reference peaks to target peaks, a one-to-one mapping generally is not possible, especially for large proteins, due to errors, such as noise peaks, missing peaks, missing but then reappearing, overlapped, and new peaks not associated with any peaks in the reference. Due to these difficulties, the mapping is typically done manually or semi-automatically, which is not efficient for high-throughput drug screening.'),
(94878, 2012, 'bmc', 'Predicting folding pathways between RNA conformational structures guided by RNA stacks', 'Li, Yuan|Zhang, Shaojie', 'Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816-2362, USA.|Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL 32816-2362, USA.', 'United States|United States', 11, 'Algorithms|Nucleic Acid Conformation|RNA|RNA Folding|Thermodynamics', 'Journal Article', '10.1186/1471-2105-13-S3-S5', '22536903', 'Accurately predicting low energy barrier folding pathways between conformational secondary structures of an RNA molecule can provide valuable information for understanding its catalytic and regulatory functions. Most existing heuristic algorithms guide the construction of folding pathways by free energies of intermediate structures in the next move during the folding. However due to the size and ruggedness of RNA energy landscape, energy-guided search can become trapped in local optima.'),
(94879, 2012, 'bmc', 'Detection of gene expression changes at chromosomal rearrangement breakpoints in evolution', 'Muñoz, Adriana|Sankoff, David', 'School of Information Technology & Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada. adri.embo@gmail.com|School of Information Technology & Engineering, University of Ottawa, Ottawa, K1N 6N5, Canada. adri.embo@gmail.com', 'Canada|Canada', 7, 'Animals|Biological Evolution|Blood Cells|Cercopithecus aethiops|Cerebral Cortex|Chromosome Breakpoints|Chromosomes, Mammalian|Gene Expression|Genome|Humans|Macaca fascicularis|Pan troglodytes|Phylogeny|Primates', 'Journal Article', '10.1186/1471-2105-13-S3-S6', '22536904', 'We study the relation between genome rearrangements, breakpoints and gene expression. Genome rearrangement research has been concerned with the creation of breakpoints and their position in the chromosome, but the functional consequences of individual breakpoints remain virtually unknown, and there are no direct genome-wide studies of breakpoints from this point of view. A question arises of what the biological consequences of breakpoint creation are, rather than just their structural aspects. The question is whether proximity to the site of a breakpoint event changes the activity of a gene.'),
(94880, 2012, 'bmc', 'Win percentage: a novel measure for assessing the suitability of machine classifiers for biological problems', 'Parry, R Mitchell|Phan, John H|Wang, May D', 'The Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.|The Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.|The Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA.', 'Georgia|Georgia|Georgia', 2, 'Algorithms|Breast Neoplasms|Humans|Monte Carlo Method|Multiple Myeloma|Neuroblastoma|Normal Distribution|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-13-S3-S7', '22536905', 'Selecting an appropriate classifier for a particular biological application poses a difficult problem for researchers and practitioners alike. In particular, choosing a classifier depends heavily on the features selected. For high-throughput biomedical datasets, feature selection is often a preprocessing step that gives an unfair advantage to the classifiers built with the same modeling assumptions. In this paper, we seek classifiers that are suitable to a particular problem independent of feature selection. We propose a novel measure, called win percentage, for assessing the suitability of machine classifiers to a particular problem. We define win percentage as the probability a classifier will perform better than its peers on a finite random sample of feature sets, giving each classifier equal opportunity to find suitable features.'),
(94881, 2012, 'bmc', 'Ab initio detection of fuzzy amino acid tandem repeats in protein sequences', 'Pellegrini, Marco|Renda, Maria Elena|Vecchio, Alessio', 'Istituto di Informatica e Telematica, CNR - Consiglio Nazionale delle Ricerche, Pisa I-56124, Italy. marco.pellegrini@iit.cnr.it|Istituto di Informatica e Telematica, CNR - Consiglio Nazionale delle Ricerche, Pisa I-56124, Italy. marco.pellegrini@iit.cnr.it|Istituto di Informatica e Telematica, CNR - Consiglio Nazionale delle Ricerche, Pisa I-56124, Italy. marco.pellegrini@iit.cnr.it', 'Italy|Italy|Italy', 11, 'Algorithms|Amino Acid Sequence|Databases, Protein|Humans|Membrane Proteins|Protein Structure, Secondary|Proteins', 'Journal Article', '10.1186/1471-2105-13-S3-S8', '22536906', 'Tandem repetitions within protein amino acid sequences often correspond to regular secondary structures and form multi-repeat 3D assemblies of varied size and function. Developing internal repetitions is one of the evolutionary mechanisms that proteins employ to adapt their structure and function under evolutionary pressure. While there is keen interest in understanding such phenomena, detection of repeating structures based only on sequence analysis is considered an arduous task, since structure and function is often preserved even under considerable sequence divergence (fuzzy tandem repeats).'),
(94882, 2012, 'bmc', 'Sensitive detection of pathway perturbations in cancers', 'Rivera, Corban G|Tyler, Brett M|Murali, T M', 'Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.', 'United States|United States|United States', 2, 'Algorithms|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Neoplasms|Protein Interaction Maps|Signal Transduction', 'Journal Article', '10.1186/1471-2105-13-S3-S9', '22536907', 'The normal functioning of a living cell is characterized by complex interaction networks involving many different types of molecules. Associations detected between diseases and perturbations in well-defined pathways within such interaction networks have the potential to illuminate the molecular mechanisms underlying disease progression and response to treatment.'),
(94883, 2012, 'bmc', 'Bioinformatics in Italy: BITS2011, the Eighth Annual Meeting of the Italian Society of Bioinformatics', 'Romano, Paolo|Helmer-Citterich, Manuela', 'Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.', 'United States|United States', 0, 'Algorithms|Computational Biology|Databases, Genetic|Genomics|Humans|Italy|Proteins|Synthetic Biology|Systems Biology', 'Introductory Journal Article', '10.1186/1471-2105-13-S4-I1', '22536954', 'The BITS2011 meeting, held in Pisa on June 20-22, 2011, brought together more than 120 Italian researchers working in the field of Bioinformatics, as well as students in Bioinformatics, Computational Biology, Biology, Computer Sciences, and Engineering, representing a landscape of Italian bioinformatics research.This preface provides a brief overview of the meeting and introduces the peer-reviewed manuscripts that were accepted for publication in this Supplement.'),
(94884, 2012, 'bmc', 'Accurate multiple sequence alignment of transmembrane proteins with PSI-Coffee', 'Chang, Jia-Ming|Di Tommaso, Paolo|Taly, Jean-François|Notredame, Cedric', 'Bioinformatics and Genomics program, Centre for Genomic Regulation (CRG) and UPF, Barcelona 08003, Spain.|Bioinformatics and Genomics program, Centre for Genomic Regulation (CRG) and UPF, Barcelona 08003, Spain.|Bioinformatics and Genomics program, Centre for Genomic Regulation (CRG) and UPF, Barcelona 08003, Spain.|Bioinformatics and Genomics program, Centre for Genomic Regulation (CRG) and UPF, Barcelona 08003, Spain.', 'Spain|Spain|Spain|Spain', 75, 'Algorithms|Animals|Databases, Protein|Drosophila|Drosophila melanogaster|Membrane Proteins|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-13-S4-S1', '22536955', 'Transmembrane proteins (TMPs) constitute about 20~30% of all protein coding genes. The relative lack of experimental structure has so far made it hard to develop specific alignment methods and the current state of the art (PRALINE™) only manages to recapitulate 50% of the positions in the reference alignments available from the BAliBASE2-ref7.'),
(94885, 2012, 'bmc', 'Stochastic simulations of minimal cells: the Ribocell model', 'Mavelli, Fabio', 'Chemistry Department, University Aldo Moro, Bari, 70125, Italy. mavelli@chimica.uniba.it', 'Italy', 29, 'Algorithms|Artificial Cells|Biological Evolution|Catalysis|Computer Simulation|Lipids|Liposomes|Models, Biological|RNA, Catalytic|Software', 'Journal Article', '10.1186/1471-2105-13-S4-S10', '22536956', 'Over the last two decades, lipid compartments (liposomes, lipid-coated droplets) have been extensively used as in vitro minimal cell models. In particular, simple and complex biomolecular reactions have been carried out inside these self-assembled micro- and nano-sized compartments, leading to the synthesis of RNA and functional proteins inside liposomes. Despite this experimental progress, a detailed physical understanding of the underlying dynamics is missing. In particular, the combination of solute compartmentalization, reactivity and stochastic effects has not yet been clarified. A combination of experimental and computational approaches can reveal interesting mechanisms governing the behavior of micro compartmentalized systems, in particular by highlighting the intrinsic stochastic diversity within a population of synthetic cells.'),
(94886, 2012, 'bmc', 'Characterization of an inducible promoter in different DNA copy number conditions', 'Zucca, Susanna|Pasotti, Lorenzo|Mazzini, Giuliano|De Angelis, Maria Gabriella Cusella|Magni, Paolo', 'Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, I-27100 Pavia, Italy.|Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, I-27100 Pavia, Italy.|Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, I-27100 Pavia, Italy.|Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, I-27100 Pavia, Italy.|Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, I-27100 Pavia, Italy.', 'Italy|Italy|Italy|Italy|Italy', 23, '4-Butyrolactone|Escherichia coli|Gene Dosage|Gene Expression Regulation, Bacterial|Models, Biological|Plasmids|Promoter Regions, Genetic|Synthetic Biology', 'Journal Article', '10.1186/1471-2105-13-S4-S11', '22536957', 'The bottom-up programming of living organisms to implement novel user-defined biological capabilities is one of the main goals of synthetic biology. Currently, a predominant problem connected with the construction of even simple synthetic biological systems is the unpredictability of the genetic circuitry when assembled and incorporated in living cells. Copy number, transcriptional/translational demand and toxicity of the DNA-encoded functions are some of the major factors which may lead to cell overburdening and thus to nonlinear effects on system output. It is important to disclose the linearity working boundaries of engineered biological systems when dealing with such phenomena.'),
(94887, 2012, 'bmc', 'In-silico and in-vivo analyses of EST databases unveil conserved miRNAs from Carthamus tinctorius and Cynara cardunculus', 'Catalano, Domenico|Pignone, Domenico|Sonnante, Gabriella|Finetti-Sialer, Mariella M', 'Istituto di Genetica Vegetale, Consiglio Nazionale delle Ricerche, Bari, 70126, Italy. domenico.catalano@igv.cnr.it|Istituto di Genetica Vegetale, Consiglio Nazionale delle Ricerche, Bari, 70126, Italy. domenico.catalano@igv.cnr.it|Istituto di Genetica Vegetale, Consiglio Nazionale delle Ricerche, Bari, 70126, Italy. domenico.catalano@igv.cnr.it|Istituto di Genetica Vegetale, Consiglio Nazionale delle Ricerche, Bari, 70126, Italy. domenico.catalano@igv.cnr.it', 'Italy|Italy|Italy|Italy', 0, 'Base Sequence|Carthamus tinctorius|Cynara|Databases, Genetic|Expressed Sequence Tags|MicroRNAs|Molecular Sequence Data|Nucleic Acid Conformation|RNA, Messenger|RNA, Plant|Sequence Analysis, RNA', 'Comparative Study', '10.1186/1471-2105-13-S4-S12', '22536958', 'MicroRNAs (miRNAs) are small RNAs (21-24 bp) providing an RNA-based system of gene regulation highly conserved in plants and animals. In plants, miRNAs control mRNA degradation or restrain translation, affecting development and responses to stresses. Plant miRNAs show imperfect but extensive complementarity to mRNA targets, making their computational prediction possible, useful when data mining is applied on different species. In this study we used a comparative approach to identify both miRNAs and their targets, in artichoke and safflower.'),
(94888, 2012, 'bmc', 'Design of a multi-signature ensemble classifier predicting neuroblastoma patients outcome', 'Cornero, Andrea|Acquaviva, Massimo|Fardin, Paolo|Versteeg, Rogier|Schramm, Alexander|Eva, Alessandra|Bosco, Maria Carla|Blengio, Fabiola|Barzaghi, Sara|Varesio, Luigi', 'Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.|Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.|Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.|Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.|Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.|Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.|Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.|Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.|Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.|Laboratory of Molecular Biology, G. Gaslini Institute, Genoa 16147, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Gene Expression Profiling|Humans|Infant|Neural Networks (Computer)|Neuroblastoma|Prognosis|Risk Assessment|Treatment Outcome', 'Journal Article', '10.1186/1471-2105-13-S4-S13', '22536959', 'Neuroblastoma is the most common pediatric solid tumor of the sympathetic nervous system. Development of improved predictive tools for patients stratification is a crucial requirement for neuroblastoma therapy. Several studies utilized gene expression-based signatures to stratify neuroblastoma patients and demonstrated a clear advantage of adding genomic analysis to risk assessment. There is little overlapping among signatures and merging their prognostic potential would be advantageous. Here, we describe a new strategy to merge published neuroblastoma related gene signatures into a single, highly accurate, Multi-Signature Ensemble (MuSE)-classifier of neuroblastoma (NB) patients outcome.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94889, 2012, 'bmc', 'Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms', 'Falda, Marco|Toppo, Stefano|Pescarolo, Alessandro|Lavezzo, Enrico|Di Camillo, Barbara|Facchinetti, Andrea|Cilia, Elisa|Velasco, Riccardo|Fontana, Paolo', 'Department of Molecular Medicine, University of Padova, via U. Bassi 58/B, 35121, Padova, Italy. marco.falda@unipd.it|Department of Molecular Medicine, University of Padova, via U. Bassi 58/B, 35121, Padova, Italy. marco.falda@unipd.it|Department of Molecular Medicine, University of Padova, via U. Bassi 58/B, 35121, Padova, Italy. marco.falda@unipd.it|Department of Molecular Medicine, University of Padova, via U. Bassi 58/B, 35121, Padova, Italy. marco.falda@unipd.it|Department of Molecular Medicine, University of Padova, via U. Bassi 58/B, 35121, Padova, Italy. marco.falda@unipd.it|Department of Molecular Medicine, University of Padova, via U. Bassi 58/B, 35121, Padova, Italy. marco.falda@unipd.it|Department of Molecular Medicine, University of Padova, via U. Bassi 58/B, 35121, Padova, Italy. marco.falda@unipd.it|Department of Molecular Medicine, University of Padova, via U. Bassi 58/B, 35121, Padova, Italy. marco.falda@unipd.it|Department of Molecular Medicine, University of Padova, via U. Bassi 58/B, 35121, Padova, Italy. marco.falda@unipd.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Databases, Genetic|Genome, Plant|High-Throughput Nucleotide Sequencing|Malus|Markov Chains|Molecular Sequence Annotation|Proteins|Semantics|Vitis|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-13-S4-S14', '22536960', 'Predicting protein function has become increasingly demanding in the era of next generation sequencing technology. The task to assign a curator-reviewed function to every single sequence is impracticable. Bioinformatics tools, easy to use and able to provide automatic and reliable annotations at a genomic scale, are necessary and urgent. In this scenario, the Gene Ontology has provided the means to standardize the annotation classification with a structured vocabulary which can be easily exploited by computational methods.'),
(94890, 2012, 'bmc', 'Primates and mouse NumtS in the UCSC Genome Browser', 'Calabrese, Francesco Maria|Simone, Domenico|Attimonelli, Marcella', 'Dipartimento di Bioscienze, Biotecnologie e Scienze Farmacologiche, Università di Bari, Bari, 70126, Italy.|Dipartimento di Bioscienze, Biotecnologie e Scienze Farmacologiche, Università di Bari, Bari, 70126, Italy.|Dipartimento di Bioscienze, Biotecnologie e Scienze Farmacologiche, Università di Bari, Bari, 70126, Italy.', 'Italy|Italy|Italy', 28, 'Animals|Cell Nucleus|DNA, Mitochondrial|Genes, Mitochondrial|Genome|Humans|Macaca mulatta|Mice|Mitochondria|Pan troglodytes|Software', 'Journal Article', '10.1186/1471-2105-13-S4-S15', '22536961', 'NumtS (Nuclear MiTochondrial Sequences) are mitochondrial DNA sequences that, after stress events involving the mitochondrion, colonized the nuclear genome. Accurate mapping of NumtS avoids contamination during mtDNA PCR amplification, thus supplying reliable bases for detecting false heteroplasmies. In addition, since they commonly populate mammalian genomes (especially primates) and are polymorphic, in terms of presence/absence and content of SNPs, they may be used as evolutionary markers in intra- and inter-species population analyses.'),
(94891, 2012, 'bmc', 'Intuitive representation of surface properties of biomolecules using BioBlender', 'Andrei, Raluca Mihaela|Callieri, Marco|Zini, Maria Francesca|Loni, Tiziana|Maraziti, Giuseppe|Pan, Mike Chen|Zoppè, Monica', 'Scientific Visualization Unit, Institute of Clinical Physiology, CNR of Italy, Area della Ricerca, Pisa, 56124, Italy.|Scientific Visualization Unit, Institute of Clinical Physiology, CNR of Italy, Area della Ricerca, Pisa, 56124, Italy.|Scientific Visualization Unit, Institute of Clinical Physiology, CNR of Italy, Area della Ricerca, Pisa, 56124, Italy.|Scientific Visualization Unit, Institute of Clinical Physiology, CNR of Italy, Area della Ricerca, Pisa, 56124, Italy.|Scientific Visualization Unit, Institute of Clinical Physiology, CNR of Italy, Area della Ricerca, Pisa, 56124, Italy.|Scientific Visualization Unit, Institute of Clinical Physiology, CNR of Italy, Area della Ricerca, Pisa, 56124, Italy.|Scientific Visualization Unit, Institute of Clinical Physiology, CNR of Italy, Area della Ricerca, Pisa, 56124, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 36, 'Hydrophobic and Hydrophilic Interactions|Image Processing, Computer-Assisted|Models, Molecular|Proteins|Software|Static Electricity|Surface Properties', 'Journal Article', '10.1186/1471-2105-13-S4-S16', '22536962', 'In living cells, proteins are in continuous motion and interaction with the surrounding medium and/or other proteins and ligands. These interactions are mediated by protein features such as electrostatic and lipophilic potentials. The availability of protein structures enables the study of their surfaces and surface characteristics, based on atomic contribution. Traditionally, these properties are calculated by physico-chemical programs and visualized as range of colors that vary according to the tool used and imposes the necessity of a legend to decrypt it. The use of color to encode both characteristics makes the simultaneous visualization almost impossible, requiring these features to be visualized in different images. In this work, we describe a novel and intuitive code for the simultaneous visualization of these properties.'),
(94892, 2012, 'bmc', 'Identification of binding pockets in protein structures using a knowledge-based potential derived from local structural similarities', 'Bianchi, Valerio|Gherardini, Pier Federico|Helmer-Citterich, Manuela|Ausiello, Gabriele', 'Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica snc, Rome 00133, Italy.|Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica snc, Rome 00133, Italy.|Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica snc, Rome 00133, Italy.|Centre for Molecular Bioinformatics, Department of Biology, University of Rome Tor Vergata, Via della Ricerca Scientifica snc, Rome 00133, Italy.', 'Italy|Italy|Italy|Italy', 0, 'Algorithms|Animals|Binding Sites|Databases, Protein|Knowledge Bases|Ligands|Models, Molecular|Protein Binding|Protein Conformation|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1186/1471-2105-13-S4-S17', '22536963', 'The identification of ligand binding sites is a key task in the annotation of proteins with known structure but uncharacterized function. Here we describe a knowledge-based method exploiting the observation that unrelated binding sites share small structural motifs that bind the same chemical fragments irrespective of the nature of the ligand as a whole.'),
(94893, 2012, 'bmc', 'Bluues: a program for the analysis of the electrostatic properties of proteins based on generalized Born radii', 'Fogolari, Federico|Corazza, Alessandra|Yarra, Vijaylakshmi|Jalaru, Anusha|Viglino, Paolo|Esposito, Gennaro', 'Dipartimento di Scienze Mediche e Biologiche, Università di Udine, Piazzale Kolbe, 4, Udine 33100, Italy. federico.fogolari@uniud.it|Dipartimento di Scienze Mediche e Biologiche, Università di Udine, Piazzale Kolbe, 4, Udine 33100, Italy. federico.fogolari@uniud.it|Dipartimento di Scienze Mediche e Biologiche, Università di Udine, Piazzale Kolbe, 4, Udine 33100, Italy. federico.fogolari@uniud.it|Dipartimento di Scienze Mediche e Biologiche, Università di Udine, Piazzale Kolbe, 4, Udine 33100, Italy. federico.fogolari@uniud.it|Dipartimento di Scienze Mediche e Biologiche, Università di Udine, Piazzale Kolbe, 4, Udine 33100, Italy. federico.fogolari@uniud.it|Dipartimento di Scienze Mediche e Biologiche, Università di Udine, Piazzale Kolbe, 4, Udine 33100, Italy. federico.fogolari@uniud.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 27, 'Hydrogen-Ion Concentration|Models, Chemical|Proteins|Software|Static Electricity|Thermodynamics', 'Journal Article', '10.1186/1471-2105-13-S4-S18', '22536964', 'The Poisson-Boltzmann (PB) equation and its linear approximation have been widely used to describe biomolecular electrostatics. Generalized Born (GB) models offer a convenient computational approximation for the more fundamental approach based on the Poisson-Boltzmann equation, and allows estimation of pairwise contributions to electrostatic effects in the molecular context.'),
(94894, 2012, 'bmc', 'CONS-COCOMAPS: a novel tool to measure and visualize the conservation of inter-residue contacts in multiple docking solutions', 'Vangone, Anna|Oliva, Romina|Cavallo, Luigi', 'Department of Applied Sciences, University Parthenope of Naples, Centro Direzionale Isola C4, Naples, 80143, Italy.|Department of Applied Sciences, University Parthenope of Naples, Centro Direzionale Isola C4, Naples, 80143, Italy.|Department of Applied Sciences, University Parthenope of Naples, Centro Direzionale Isola C4, Naples, 80143, Italy.', 'Italy|Italy|Italy', 20, 'Bacteria|Cell Membrane|Internet|Models, Molecular|Protein Binding|Protein Interaction Maps|Proteins|RNA', 'Journal Article', '10.1186/1471-2105-13-S4-S19', '22536965', 'The development of accurate protein-protein docking programs is making this kind of simulations an effective tool to predict the 3D structure and the surface of interaction between the molecular partners in macromolecular complexes. However, correctly scoring multiple docking solutions is still an open problem. As a consequence, the accurate and tedious screening of many docking models is usually required in the analysis step.'),
(94895, 2012, 'bmc', 'PyMod: sequence similarity searches, multiple sequence-structure alignments, and homology modeling within PyMOL', 'Bramucci, Emanuele|Paiardini, Alessandro|Bossa, Francesco|Pascarella, Stefano', 'Dipartimento di Scienze Biochimiche A, Rossi Fanelli, Sapienza Università di Roma, Roma 00185, Italy.|Dipartimento di Scienze Biochimiche A, Rossi Fanelli, Sapienza Università di Roma, Roma 00185, Italy.|Dipartimento di Scienze Biochimiche A, Rossi Fanelli, Sapienza Università di Roma, Roma 00185, Italy.|Dipartimento di Scienze Biochimiche A, Rossi Fanelli, Sapienza Università di Roma, Roma 00185, Italy.', 'Italy|Italy|Italy|Italy', 0, 'Programming Languages|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-13-S4-S2', '22536966', 'In recent years, an exponential growing number of tools for protein sequence analysis, editing and modeling tasks have been put at the disposal of the scientific community. Despite the vast majority of these tools have been released as open source software, their deep learning curves often discourages even the most experienced users.'),
(94896, 2012, 'bmc', 'Modeling gene regulatory network motifs using Statecharts', 'Fioravanti, Fabio|Helmer-Citterich, Manuela|Nardelli, Enrico', 'Department of Biology, University of Rome Tor Vergata, Rome I-00133, Italy.|Department of Biology, University of Rome Tor Vergata, Rome I-00133, Italy.|Department of Biology, University of Rome Tor Vergata, Rome I-00133, Italy.', 'Italy|Italy|Italy', 10, 'Escherichia coli|Gene Regulatory Networks|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1186/1471-2105-13-S4-S20', '22536967', 'Gene regulatory networks are widely used by biologists to describe the interactions among genes, proteins and other components at the intra-cellular level. Recently, a great effort has been devoted to give gene regulatory networks a formal semantics based on existing computational frameworks.For this purpose, we consider Statecharts, which are a modular, hierarchical and executable formal model widely used to represent software systems. We use Statecharts for modeling small and recurring patterns of interactions in gene regulatory networks, called motifs.'),
(94897, 2012, 'bmc', 'BEAT: Bioinformatics Exon Array Tool to store, analyze and visualize Affymetrix GeneChip Human Exon Array data from disease experiments', 'Consiglio, Arianna|Carella, Massimo|De Caro, Giorgio|Delle Foglie, Gianfranco|Giovannelli, Candida|Grillo, Giorgio|Ianigro, Massimo|Licciulli, Flavio|Palumbo, Orazio|Piepoli, Ada|Ranieri, Elena|Liuni, Sabino', 'Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.|Institute for Biomedical Technologies of Bari - ITB, National Research Council, Bari, 70126, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Alternative Splicing|Carcinoma, Renal Cell|Colorectal Neoplasms|Databases, Genetic|Gene Expression Profiling|Humans|Internet|Kidney Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-13-S4-S21', '22536968', 'It is known from recent studies that more than 90% of human multi-exon genes are subject to Alternative Splicing (AS), a key molecular mechanism in which multiple transcripts may be generated from a single gene. It is widely recognized that a breakdown in AS mechanisms plays an important role in cellular differentiation and pathologies. Polymerase Chain Reactions, microarrays and sequencing technologies have been applied to the study of transcript diversity arising from alternative expression. Last generation Affymetrix GeneChip Human Exon 1.0 ST Arrays offer a more detailed view of the gene expression profile providing information on the AS patterns. The exon array technology, with more than five million data points, can detect approximately one million exons, and it allows performing analyses at both gene and exon level. In this paper we describe BEAT, an integrated user-friendly bioinformatics framework to store, analyze and visualize exon arrays datasets. It combines a data warehouse approach with some rigorous statistical methods for assessing the AS of genes involved in diseases. Meta statistics are proposed as a novel approach to explore the analysis results. BEAT is available at http://beat.ba.itb.cnr.it.'),
(94898, 2012, 'bmc', 'Improving biomarker list stability by integration of biological knowledge in the learning process', 'Sanavia, Tiziana|Aiolli, Fabio|Da San Martino, Giovanni|Bisognin, Andrea|Di Camillo, Barbara', 'Department of Information Engineering, University of Padova, via G, Gradenigo 6/B, 35131 Padova, Italy.|Department of Information Engineering, University of Padova, via G, Gradenigo 6/B, 35131 Padova, Italy.|Department of Information Engineering, University of Padova, via G, Gradenigo 6/B, 35131 Padova, Italy.|Department of Information Engineering, University of Padova, via G, Gradenigo 6/B, 35131 Padova, Italy.|Department of Information Engineering, University of Padova, via G, Gradenigo 6/B, 35131 Padova, Italy.', 'Italy|Italy|Italy|Italy|Italy', 10, 'Algorithms|Artificial Intelligence|Biomarkers|Breast Neoplasms|Databases, Genetic|Gene Expression Profiling|Genomics|Humans|Oligonucleotide Array Sequence Analysis|Protein Interaction Maps|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-13-S4-S22', '22536969', 'The identification of robust lists of molecular biomarkers related to a disease is a fundamental step for early diagnosis and treatment. However, methodologies for biomarker discovery using microarray data often provide results with limited overlap. It has been suggested that one reason for these inconsistencies may be that in complex diseases, such as cancer, multiple genes belonging to one or more physiological pathways are associated with the outcomes. Thus, a possible approach to improve list stability is to integrate biological information from genomic databases in the learning process, however, a comprehensive assessment based on different types of biological information is still lacking in the literature. In this work we have compared the effect of using different biological information in the learning process like functional annotations, protein-protein interactions and expression correlation among genes.'),
(94899, 2012, 'bmc', 'Tandem repeats discovery service (TReaDS) applied to finding novel cis-acting factors in repeat expansion diseases', 'Pellegrini, Marco|Renda, Maria Elena|Vecchio, Alessio', 'Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, Pisa I-56124, Italy.|Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, Pisa I-56124, Italy.|Istituto di Informatica e Telematica, Consiglio Nazionale delle Ricerche, Pisa I-56124, Italy.', 'Italy|Italy|Italy', 7, 'Algorithms|DNA Repeat Expansion|Humans|Neurodegenerative Diseases|Neuromuscular Diseases|Peptides|Polymorphism, Single Nucleotide|Search Engine|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-13-S4-S3', '22536970', 'Tandem repeats are multiple duplications of substrings in the DNA that occur contiguously, or at a short distance, and may involve some mutations (such as substitutions, insertions, and deletions). Tandem repeats have been extensively studied also for their association with the class of repeat expansion diseases (mostly affecting the nervous system). Comparative studies on the output of different tools for finding tandem repeats highlighted significant differences among the sets of detected tandem repeats, while many authors pointed up how critical it is the right choice of parameters.'),
(94900, 2012, 'bmc', 'GIDL: a rule based expert system for GenBank Intelligent Data Loading into the Molecular Biodiversity Database', 'Pannarale, Paolo|Catalano, Domenico|De Caro, Giorgio|Grillo, Giorgio|Leo, Pietro|Pappadà, Graziano|Rubino, Francesco|Scioscia, Gaetano|Licciulli, Flavio', 'IBM GBS BAO Advanced Analytics Services and MBLab, Bari, 70100, Italy.|IBM GBS BAO Advanced Analytics Services and MBLab, Bari, 70100, Italy.|IBM GBS BAO Advanced Analytics Services and MBLab, Bari, 70100, Italy.|IBM GBS BAO Advanced Analytics Services and MBLab, Bari, 70100, Italy.|IBM GBS BAO Advanced Analytics Services and MBLab, Bari, 70100, Italy.|IBM GBS BAO Advanced Analytics Services and MBLab, Bari, 70100, Italy.|IBM GBS BAO Advanced Analytics Services and MBLab, Bari, 70100, Italy.|IBM GBS BAO Advanced Analytics Services and MBLab, Bari, 70100, Italy.|IBM GBS BAO Advanced Analytics Services and MBLab, Bari, 70100, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 6, 'Animals|Biodiversity|Computational Biology|Databases, Nucleic Acid|Expert Systems|Internet|Software', 'Journal Article', '10.1186/1471-2105-13-S4-S4', '22536971', 'In the scientific biodiversity community, it is increasingly perceived the need to build a bridge between molecular and traditional biodiversity studies. We believe that the information technology could have a preeminent role in integrating the information generated by these studies with the large amount of molecular data we can find in bioinformatics public databases. This work is primarily aimed at building a bioinformatic infrastructure for the integration of public and private biodiversity data through the development of GIDL, an Intelligent Data Loader coupled with the Molecular Biodiversity Database. The system presented here organizes in an ontological way and locally stores the sequence and annotation data contained in the GenBank primary database.'),
(94901, 2012, 'bmc', 'An ICT infrastructure to integrate clinical and molecular data in oncology research', 'Segagni, Daniele|Tibollo, Valentina|Dagliati, Arianna|Zambelli, Alberto|Priori, Silvia G|Bellazzi, Riccardo', 'IRCCS Fondazione Salvatore Maugeri, Pavia, 27100, Italy.|IRCCS Fondazione Salvatore Maugeri, Pavia, 27100, Italy.|IRCCS Fondazione Salvatore Maugeri, Pavia, 27100, Italy.|IRCCS Fondazione Salvatore Maugeri, Pavia, 27100, Italy.|IRCCS Fondazione Salvatore Maugeri, Pavia, 27100, Italy.|IRCCS Fondazione Salvatore Maugeri, Pavia, 27100, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Breast Neoplasms|Databases, Factual|Hospital Information Systems|Humans|Information Storage and Retrieval|Medical Oncology|Natural Language Processing|Software|Translational Medical Research', 'Journal Article', '10.1186/1471-2105-13-S4-S5', '22536972', 'The ONCO-i2b2 platform is a bioinformatics tool designed to integrate clinical and research data and support translational research in oncology. It is implemented by the University of Pavia and the IRCCS Fondazione Maugeri hospital (FSM), and grounded on the software developed by the Informatics for Integrating Biology and the Bedside (i2b2) research center. I2b2 has delivered an open source suite based on a data warehouse, which is efficiently interrogated to find sets of interesting patients through a query tool interface.'),
(94902, 2012, 'bmc', 'OREMPdb: a semantic dictionary of computational pathway models', 'Umeton, Renato|Nicosia, Giuseppe|Dewey, C Forbes', 'Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.|Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.|Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.', 'United States|United States|United States', 5, 'Computer Simulation|Internet|Knowledge Bases|Medical Informatics|Research|Semantics|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-13-S4-S6', '22536973', 'The information coming from biomedical ontologies and computational pathway models is expanding continuously: research communities keep this process up and their advances are generally shared by means of dedicated resources published on the web. In fact, such models are shared to provide the characterization of molecular processes, while biomedical ontologies detail a semantic context to the majority of those pathways. Recent advances in both fields pave the way for a scalable information integration based on aggregate knowledge repositories, but the lack of overall standard formats impedes this progress. Indeed, having different objectives and different abstraction levels, most of these resources speak different languages. Semantic web technologies are here explored as a means to address some of these problems.'),
(94903, 2012, 'bmc', 'Towards linked open gene mutations data', 'Zappa, Achille|Splendiani, Andrea|Romano, Paolo', 'Bioinformatics, IRCCS AOU San Martino-IST National Cancer Research Institute, Genoa, I-16132, Italy.|Bioinformatics, IRCCS AOU San Martino-IST National Cancer Research Institute, Genoa, I-16132, Italy.|Bioinformatics, IRCCS AOU San Martino-IST National Cancer Research Institute, Genoa, I-16132, Italy.', 'Italy|Italy|Italy', 10, 'Databases, Genetic|Genes, p53|Genetic Variation|Humans|Internet|Mutation|Semantics|Software', 'Journal Article', '10.1186/1471-2105-13-S4-S7', '22536974', 'With the advent of high-throughput technologies, a great wealth of variation data is being produced. Such information may constitute the basis for correlation analyses between genotypes and phenotypes and, in the future, for personalized medicine. Several databases on gene variation exist, but this kind of information is still scarce in the Semantic Web framework. In this paper, we discuss issues related to the integration of mutation data in the Linked Open Data infrastructure, part of the Semantic Web framework. We present the development of a mapping from the IARC TP53 Mutation database to RDF and the implementation of servers publishing this data.'),
(94904, 2012, 'bmc', 'Fine-tuning anti-tumor immunotherapies via stochastic simulations', 'Caravagna, Giulio|Barbuti, Roberto|dOnofrio, Alberto', 'Institute for Informatics and Telematics, National Research Council, Pisa, Italy.|Institute for Informatics and Telematics, National Research Council, Pisa, Italy.|Institute for Informatics and Telematics, National Research Council, Pisa, Italy.', 'Italy|Italy|Italy', 13, 'Computer Simulation|Humans|Immunotherapy|Immunotherapy, Adoptive|Interleukins|Neoplasms|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-13-S4-S8', '22536975', 'Anti-tumor therapies aim at reducing to zero the number of tumor cells in a host within their end or, at least, aim at leaving the patient with a sufficiently small number of tumor cells so that the residual tumor can be eradicated by the immune system. Besides severe side-effects, a key problem of such therapies is finding a suitable scheduling of their administration to the patients. In this paper we study the effect of varying therapy-related parameters on the final outcome of the interplay between a tumor and the immune system.'),
(94905, 2012, 'bmc', 'Characterization of the emergent properties of a synthetic quasi-cellular system', 'Lazzerini-Ospri, Lorenzo|Stano, Pasquale|Luisi, PierLuigi|Marangoni, Roberto', 'Dipartimento di Informatica, Università di Pisa, L.go B, Pontecorvo 3, 56127 Pisa, Italy.|Dipartimento di Informatica, Università di Pisa, L.go B, Pontecorvo 3, 56127 Pisa, Italy.|Dipartimento di Informatica, Università di Pisa, L.go B, Pontecorvo 3, 56127 Pisa, Italy.|Dipartimento di Informatica, Università di Pisa, L.go B, Pontecorvo 3, 56127 Pisa, Italy.', 'Italy|Italy|Italy|Italy', 0, 'Artificial Cells|Escherichia coli|Kinetics|Liposomes|Metabolic Networks and Pathways|Protein Biosynthesis', 'Journal Article', '10.1186/1471-2105-13-S4-S9', '22536976', 'The process of solutes entrapment during liposomes formation is interesting for the investigation of the relationship between the formation of compartments and the distribution of molecules inside them, a relevant issue in the studies of the origin of life. Theoretically, when no interactions are supposed among the chemical species to be entrapped, the entrapment is described by a standard Poisson process. But very recent experimental findings show that, for small liposomes (100 nm diameter), the distribution of entrapped molecules is best described by a power-law function. This is of a great importance, as the two random processes give rise to two completely different scenarios. Here we present an in silico stochastic simulation of the encapsulation of a cell-free molecular translation system (the PURE system), obtained following two different entrapment models: a pure Poisson process, and a power-law. The protein synthesis inside the liposomes has been studied in both cases, with the aim to highlight experimental observables that could be measured to assess which model gives a better representation of the real process.'),
(94906, 2012, 'bmc', 'Stable stem enabled Shannon entropies distinguish non-coding RNAs from random backgrounds', 'Wang, Yingfeng|Manzour, Amir|Shareghi, Pooya|Shaw, Timothy I|Li, Ying-Wai|Malmberg, Russell L|Cai, Liming', 'Department of Computer Science, University of Georgia, Athens, Georgia 30602, USA. ywang802@uga.edu|Department of Computer Science, University of Georgia, Athens, Georgia 30602, USA. ywang802@uga.edu|Department of Computer Science, University of Georgia, Athens, Georgia 30602, USA. ywang802@uga.edu|Department of Computer Science, University of Georgia, Athens, Georgia 30602, USA. ywang802@uga.edu|Department of Computer Science, University of Georgia, Athens, Georgia 30602, USA. ywang802@uga.edu|Department of Computer Science, University of Georgia, Athens, Georgia 30602, USA. ywang802@uga.edu|Department of Computer Science, University of Georgia, Athens, Georgia 30602, USA. ywang802@uga.edu', 'Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia', 7, 'Algorithms|Base Pairing|Entropy|Nucleic Acid Conformation|Probability|RNA Folding|RNA, Untranslated', 'Journal Article', '10.1186/1471-2105-13-S5-S1', '22537005', 'The computational identification of RNAs in genomic sequences requires the identification of signals of RNA sequences. Shannon base pairing entropy is an indicator for RNA secondary structure fold certainty in detection of structural, non-coding RNAs (ncRNAs). Under the Boltzmann ensemble of secondary structures, the probability of a base pair is estimated from its frequency across all the alternative equilibrium structures. However, such an entropy has yet to deliver the desired performance for distinguishing ncRNAs from random sequences. Developing novel methods to improve the entropy measure performance may result in more effective ncRNA gene finding based on structure detection.'),
(94907, 2012, 'bmc', 'PIntron: a fast method for detecting the gene structure due to alternative splicing via maximal pairings of a pattern and a text', 'Pirola, Yuri|Rizzi, Raffaella|Picardi, Ernesto|Pesole, Graziano|Della Vedova, Gianluca|Bonizzoni, Paola', 'Dipartimento di Informatica Sistemistica e Comunicazione, Univ, degli Studi di Milano-Bicocca, Milano, 20126, Italy.|Dipartimento di Informatica Sistemistica e Comunicazione, Univ, degli Studi di Milano-Bicocca, Milano, 20126, Italy.|Dipartimento di Informatica Sistemistica e Comunicazione, Univ, degli Studi di Milano-Bicocca, Milano, 20126, Italy.|Dipartimento di Informatica Sistemistica e Comunicazione, Univ, degli Studi di Milano-Bicocca, Milano, 20126, Italy.|Dipartimento di Informatica Sistemistica e Comunicazione, Univ, degli Studi di Milano-Bicocca, Milano, 20126, Italy.|Dipartimento di Informatica Sistemistica e Comunicazione, Univ, degli Studi di Milano-Bicocca, Milano, 20126, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 7, 'Algorithms|Alternative Splicing|Animals|Exons|Expressed Sequence Tags|Genomics|Humans|Introns|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-13-S5-S2', '22537006', 'A challenging issue in designing computational methods for predicting the gene structure into exons and introns from a cluster of transcript (EST, mRNA) sequences, is guaranteeing accuracy as well as efficiency in time and space, when large clusters of more than 20,000 ESTs and genes longer than 1 Mb are processed. Traditionally, the problem has been faced by combining different tools, not specifically designed for this task.'),
(94908, 2012, 'bmc', 'Accelerating pairwise statistical significance estimation for local alignment by harvesting GPUs power', 'Zhang, Yuhong|Misra, Sanchit|Agrawal, Ankit|Patwary, Md Mostofa Ali|Liao, Wei-Keng|Qin, Zhiguang|Choudhary, Alok', 'School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China. yuhongzhang@uestc.edu.cn|School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China. yuhongzhang@uestc.edu.cn|School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China. yuhongzhang@uestc.edu.cn|School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China. yuhongzhang@uestc.edu.cn|School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China. yuhongzhang@uestc.edu.cn|School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China. yuhongzhang@uestc.edu.cn|School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China. yuhongzhang@uestc.edu.cn', 'China|China|China|China|China|China|China', 0, 'Algorithms|Computer Graphics|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-13-S5-S3', '22537007', 'Pairwise statistical significance has been recognized to be able to accurately identify related sequences, which is a very important cornerstone procedure in numerous bioinformatics applications. However, it is both computationally and data intensive, which poses a big challenge in terms of performance and scalability.'),
(94909, 2012, 'bmc', 'Multi-dimensional characterization of electrostatic surface potential computation on graphics processors', 'Daga, Mayank|Feng, Wu-Chun', 'Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, USA. mdaga@cs.vt.edu|Department of Computer Science, Virginia Tech, Blacksburg, VA 24060, USA. mdaga@cs.vt.edu', 'United States|United States', 2, 'Algorithms|Chromatin|Computer Graphics|Computer Storage Devices|Models, Molecular|Proteins|Software|Static Electricity', 'Journal Article', '10.1186/1471-2105-13-S5-S4', '22537008', 'Calculating the electrostatic surface potential (ESP) of a biomolecule is critical towards understanding biomolecular function. Because of its quadratic computational complexity (as a function of the number of atoms in a molecule), there have been continual efforts to reduce its complexity either by improving the algorithm or the underlying hardware on which the calculations are performed.'),
(94910, 2012, 'bmc', 'Parametric modeling of cellular state transitions as measured with flow cytometry', 'Ho, Hsiu J|Lin, Tsung I|Chang, Hannah H|Haase, Steven B|Huang, Sui|Pyne, Saumyadipta', 'Department of Applied Mathematics and Institute of Statistics, National Chung Hsing University, Taichung 402, Taiwan.|Department of Applied Mathematics and Institute of Statistics, National Chung Hsing University, Taichung 402, Taiwan.|Department of Applied Mathematics and Institute of Statistics, National Chung Hsing University, Taichung 402, Taiwan.|Department of Applied Mathematics and Institute of Statistics, National Chung Hsing University, Taichung 402, Taiwan.|Department of Applied Mathematics and Institute of Statistics, National Chung Hsing University, Taichung 402, Taiwan.|Department of Applied Mathematics and Institute of Statistics, National Chung Hsing University, Taichung 402, Taiwan.', '-|-|-|-|-|-', 10, 'Algorithms|Cell Cycle|Cyclin B|Flow Cytometry|Normal Distribution|S Phase|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-13-S5-S5', '22537009', 'Gradual or sudden transitions among different states as exhibited by cell populations in a biological sample under particular conditions or stimuli can be detected and profiled by flow cytometric time course data. Often such temporal profiles contain features due to transient states that present unique modeling challenges. These could range from asymmetric non-Gaussian distributions to outliers and tail subpopulations, which need to be modeled with precision and rigor.'),
(94911, 2012, 'bmc', 'Maximum expected accuracy structural neighbors of an RNA secondary structure', 'Clote, Peter|Lou, Feng|Lorenz, William A', 'Department of Biology, Boston College, Chestnut Hill, MA 02467, USA. clote@bc.edu|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA. clote@bc.edu|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA. clote@bc.edu', 'United States|United States|United States', 0, 'Algorithms|Base Sequence|Molecular Sequence Data|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA|Thermodynamics', 'Journal Article', '10.1186/1471-2105-13-S5-S6', '22537010', 'Since RNA molecules regulate genes and control alternative splicing by allostery, it is important to develop algorithms to predict RNA conformational switches. Some tools, such as paRNAss, RNAshapes and RNAbor, can be used to predict potential conformational switches, nevertheless, no existent tool can detect general (i.e., not family specific) entire riboswitches (both aptamer and expression platform) with accuracy. Thus, the development of additional algorithms to detect conformational switches seems important, especially since the difference in free energy between the two metastable secondary structures may be as large as 15-20 kcal/mol. It has recently emerged that RNA secondary structure can be more accurately predicted by computing the maximum expected accuracy (MEA) structure, rather than the minimum free energy (MFE) structure.'),
(94912, 2012, 'bmc', 'Inferring serum proteolytic activity from LC-MS/MS data', 'Dittwald, Piotr|Ostrowski, Jerzy|Karczmarski, Jakub|Gambin, Anna', 'Institute of Informatics, University of Warsaw, Banacha 2, 02-097 Warsaw, Poland. piotr.dittwald@mimuw.edu.pl|Institute of Informatics, University of Warsaw, Banacha 2, 02-097 Warsaw, Poland. piotr.dittwald@mimuw.edu.pl|Institute of Informatics, University of Warsaw, Banacha 2, 02-097 Warsaw, Poland. piotr.dittwald@mimuw.edu.pl|Institute of Informatics, University of Warsaw, Banacha 2, 02-097 Warsaw, Poland. piotr.dittwald@mimuw.edu.pl', 'Poland|Poland|Poland|Poland', 0, 'Algorithms|Chromatography, Liquid|Colorectal Neoplasms|Humans|Markov Chains|Mass Spectrometry|Models, Statistical|Peptide Hydrolases|Proteolysis|Serum|Tandem Mass Spectrometry', 'Journal Article', '10.1186/1471-2105-13-S5-S7', '22537011', 'In this paper we deal with modeling serum proteolysis process from tandem mass spectrometry data. The parameters of peptide degradation process inferred from LC-MS/MS data correspond directly to the activity of specific enzymes present in the serum samples of patients and healthy donors. Our approach integrate the existing knowledge about peptidases activity stored in MEROPS database with the efficient procedure for estimation the model parameters.'),
(94913, 2012, 'bmc', 'Exploring behaviors of stochastic differential equation models of biological systems using change of measures', 'Jha, Sumit Kumar|Langmead, Christopher James', 'Electrical Engineering and Computer Science Department, University of Central Florida, Orlando, FL 32816 USA. jha@eecs.ucf.edu|Electrical Engineering and Computer Science Department, University of Central Florida, Orlando, FL 32816 USA. jha@eecs.ucf.edu', 'United States|United States', 10, 'Algorithms|Bayes Theorem|Cell Transformation, Neoplastic|Humans|Models, Biological|Probability|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-13-S5-S8', '22537012', 'Stochastic Differential Equations (SDE) are often used to model the stochastic dynamics of biological systems. Unfortunately, rare but biologically interesting behaviors (e.g., oncogenesis) can be difficult to observe in stochastic models. Consequently, the analysis of behaviors of SDE models using numerical simulations can be challenging. We introduce a method for solving the following problem: given a SDE model and a high-level behavioral specification about the dynamics of the model, algorithmically decide whether the model satisfies the specification. While there are a number of techniques for addressing this problem for discrete-state stochastic models, the analysis of SDE and other continuous-state models has received less attention. Our proposed solution uses a combination of Bayesian sequential hypothesis testing, non-identically distributed samples, and Girsanovs theorem for change of measures to examine rare behaviors. We use our algorithm to analyze two SDE models of tumor dynamics. Our use of non-identically distributed samples sampling contributes to the state of the art in statistical verification and model checking of stochastic models by providing an effective means for exposing rare events in SDEs, while retaining the ability to compute bounds on the probability that those events occur.'),
(94914, 2012, 'bmc', 'Exploiting sparseness in de novo genome assembly', 'Ye, Chengxi|Ma, Zhanshan Sam|Cannon, Charles H|Pop, Mihai|Yu, Douglas W', 'Ecology & Evolution of Plant-Animal Interaction Group, Xishuangbanna Tropical Botanic Garden, Chinese Academy of Sciences, Menglun, Yunnan 666303 China. cxy@umd.edu|Ecology & Evolution of Plant-Animal Interaction Group, Xishuangbanna Tropical Botanic Garden, Chinese Academy of Sciences, Menglun, Yunnan 666303 China. cxy@umd.edu|Ecology & Evolution of Plant-Animal Interaction Group, Xishuangbanna Tropical Botanic Garden, Chinese Academy of Sciences, Menglun, Yunnan 666303 China. cxy@umd.edu|Ecology & Evolution of Plant-Animal Interaction Group, Xishuangbanna Tropical Botanic Garden, Chinese Academy of Sciences, Menglun, Yunnan 666303 China. cxy@umd.edu|Ecology & Evolution of Plant-Animal Interaction Group, Xishuangbanna Tropical Botanic Garden, Chinese Academy of Sciences, Menglun, Yunnan 666303 China. cxy@umd.edu', 'China|China|China|China|China', 83, 'Algorithms|Computer Storage Devices|Escherichia coli|Genome|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-13-S6-S1', '22537038', 'The very large memory requirements for the construction of assembly graphs for de novo genome assembly limit current algorithms to super-computing environments.'),
(94915, 2012, 'bmc', 'Reconstructing cancer genomes from paired-end sequencing data', 'Oesper, Layla|Ritz, Anna|Aerni, Sarah J|Drebin, Ryan|Raphael, Benjamin J', 'Department of Computer Science, Brown University, Providence, RI, USA. layla@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI, USA. layla@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI, USA. layla@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI, USA. layla@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI, USA. layla@cs.brown.edu', 'United States|United States|United States|United States|United States', 25, 'Algorithms|Chromosome Aberrations|DNA Copy Number Variations|Female|Genome, Human|Humans|Mutation|Ovarian Neoplasms|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-13-S6-S10', '22537039', 'A cancer genome is derived from the germline genome through a series of somatic mutations. Somatic structural variants - including duplications, deletions, inversions, translocations, and other rearrangements - result in a cancer genome that is a scrambling of intervals, or blocks of the germline genome sequence. We present an efficient algorithm for reconstructing the block organization of a cancer genome from paired-end DNA sequencing data.'),
(94916, 2012, 'bmc', 'Challenges in estimating percent inclusion of alternatively spliced junctions from RNA-seq data', 'Kakaradov, Boyko|Xiong, Hui Yuan|Lee, Leo J|Jojic, Nebojsa|Frey, Brendan J', 'Department of Electrical and Computer Engineering, University of Toronto, ON, Canada.|Department of Electrical and Computer Engineering, University of Toronto, ON, Canada.|Department of Electrical and Computer Engineering, University of Toronto, ON, Canada.|Department of Electrical and Computer Engineering, University of Toronto, ON, Canada.|Department of Electrical and Computer Engineering, University of Toronto, ON, Canada.', 'Canada|Canada|Canada|Canada|Canada', 0, 'Alternative Splicing|Exons|Gene Expression Profiling|HeLa Cells|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Reverse Transcriptase Polymerase Chain Reaction|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-13-S6-S11', '22537040', 'Transcript quantification is a long-standing problem in genomics and estimating the relative abundance of alternatively-spliced isoforms from the same transcript is an important special case. Both problems have recently been illuminated by high-throughput RNA sequencing experiments which are quickly generating large amounts of data. However, much of the signal present in this data is corrupted or obscured by biases resulting in non-uniform and non-proportional representation of sequences from different transcripts. Many existing analyses attempt to deal with these and other biases with various task-specific approaches, which makes direct comparison between them difficult. However, two popular tools for isoform quantification, MISO and Cufflinks, have adopted a general probabilistic framework to model and mitigate these biases in a more general fashion. These advances motivate the need to investigate the effects of RNA-seq biases on the accuracy of different approaches for isoform quantification. We conduct the investigation by building models of increasing sophistication to account for noise introduced by the biases and compare their accuracy to the established approaches. We focus on methods that estimate the expression of alternatively-spliced isoforms with the percent-spliced-in (PSI) metric for each exon skipping event. To improve their estimates, many methods use evidence from RNA-seq reads that align to exon bodies. However, the methods we propose focus on reads that span only exon-exon junctions. As a result, our approaches are simpler and less sensitive to exon definitions than existing methods, which enables us to distinguish their strengths and weaknesses more easily. We present several probabilistic models of of position-specific read counts with increasing complexity and compare them to each other and to the current state-of-the-art methods in isoform quantification, MISO and Cufflinks. On a validation set with RT-PCR measurements for 26 cassette events, some of our methods are more accurate and some are significantly more consistent than these two popular tools. This comparison demonstrates the challenges in estimating the percent inclusion of alternatively spliced junctions and illuminates the tradeoffs between different approaches.'),
(94917, 2012, 'bmc', 'MGMR: leveraging RNA-Seq population data to optimize expression estimation', 'Rozov, Roye|Halperin, Eran|Shamir, Ron', 'The Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv 69978, Israel.', 'Israel|Israel|Israel', 3, 'Gene Expression Profiling|Genetics, Population|Genome|HapMap Project|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-13-S6-S2', '22537041', 'RNA-Seq is a technique that uses Next Generation Sequencing to identify transcripts and estimate transcription levels. When applying this technique for quantification, one must contend with reads that align to multiple positions in the genome (multireads). Previous efforts to resolve multireads have shown that RNA-Seq expression estimation can be improved using probabilistic allocation of reads to genes. These methods use a probabilistic generative model for data generation and resolve ambiguity using likelihood-based approaches. In many instances, RNA-seq experiments are performed in the context of a population. The generative models of current methods do not take into account such population information, and it is an open question whether this information can improve quantification of the individual samples'),
(94918, 2012, 'bmc', 'Haplotype reconstruction using perfect phylogeny and sequence data', 'Efros, Anatoly|Halperin, Eran', 'The Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel. talefros@gmail.com|The Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel. talefros@gmail.com', 'Israel|Israel', 0, 'Algorithms|Disease|Genetic Association Studies|Genotype|Haplotypes|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Phylogeny|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-13-S6-S3', '22537042', 'Haplotype phasing is a well studied problem in the context of genotype data. With the recent developments in high-throughput sequencing, new algorithms are needed for haplotype phasing, when the number of samples sequenced is low and when the sequencing coverage is blow. High-throughput sequencing technologies enables new possibilities for the inference of haplotypes. Since each read is originated from a single chromosome, all the variant sites it covers must derive from the same haplotype. Moreover, the sequencing process yields much higher SNP density than previous methods, resulting in a higher correlation between neighboring SNPs. We offer a new approach for haplotype phasing, which leverages on these two properties. Our suggested algorithm, called Perfect Phlogeny Haplotypes from Sequencing (PPHS) uses a perfect phylogeny model and it models the sequencing errors explicitly. We evaluated our method on real and simulated data, and we demonstrate that the algorithm outperforms previous methods when the sequencing error rate is high or when coverage is low.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94919, 2012, 'bmc', 'Biases in read coverage demonstrated by interlaboratory and interplatform comparison of 117 mRNA and genome sequencing experiments', 'Khrameeva, Ekaterina E|Gelfand, Mikhail S', 'Institute for Information Transmission Problems, Russian Academy of Sciences, 19 Bolshoy Karetny per., Moscow, 127994, Russia. khrameeva@genebee.msu.ru|Institute for Information Transmission Problems, Russian Academy of Sciences, 19 Bolshoy Karetny per., Moscow, 127994, Russia. khrameeva@genebee.msu.ru', '-|-', 5, 'Genome, Human|High-Throughput Nucleotide Sequencing|Humans|RNA, Messenger|Sequence Analysis, DNA|Sequence Analysis, RNA|Transcriptome', 'Comparative Study', '10.1186/1471-2105-13-S6-S4', '22537043', 'High-throughput sequencing of whole genomes and transcriptomes allows one to generate large amounts of sequence data very rapidly and at a low cost. The goal of most mRNA sequencing studies is to perform the comparison of the expression level between different samples. However, given a broad variety of modern sequencing protocols, platforms and versions thereof, it is not clear to what extent the obtained results are consistent across platforms and laboratories. The comparison of 117 human mRNA and genome high-throughput sequencing experiments performed on the Illumina and SOLiD platforms at 26 institutions all over the world demonstrated high dependency of the gene coverage profiles on the producing laboratory. Gene coverage profiles showed laboratory-specific non-uniformity that survived the 3-bias correction and mappability normalization, suggesting that there are other yet unknown mRNA-associated biases.'),
(94920, 2012, 'bmc', 'KISSPLICE: de-novo calling alternative splicing events from RNA-seq data', 'Sacomoto, Gustavo A T|Kielbassa, Janice|Chikhi, Rayan|Uricaru, Raluca|Antoniou, Pavlos|Sagot, Marie-France|Peterlongo, Pierre|Lacroix, Vincent', 'INRIA Grenoble Rhône-Alpes, France.|INRIA Grenoble Rhône-Alpes, France.|INRIA Grenoble Rhône-Alpes, France.|INRIA Grenoble Rhône-Alpes, France.|INRIA Grenoble Rhône-Alpes, France.|INRIA Grenoble Rhône-Alpes, France.|INRIA Grenoble Rhône-Alpes, France.|INRIA Grenoble Rhône-Alpes, France.', 'France|France|France|France|France|France|France|France', 61, 'Algorithms|Alternative Splicing|Genome|Humans|Models, Statistical|Polymorphism, Single Nucleotide|Reference Standards|Sequence Analysis, RNA|Tandem Repeat Sequences|Transcriptome', 'Journal Article', '10.1186/1471-2105-13-S6-S5', '22537044', 'In this paper, we address the problem of identifying and quantifying polymorphisms in RNA-seq data when no reference genome is available, without assembling the full transcripts. Based on the fundamental idea that each polymorphism corresponds to a recognisable pattern in a De Bruijn graph constructed from the RNA-seq reads, we propose a general model for all polymorphisms in such graphs. We then introduce an exact algorithm, called KISSPLICE, to extract alternative splicing events.'),
(94921, 2012, 'bmc', 'An improved approach for accurate and efficient calling of structural variations with low-coverage sequence data', 'Zhang, Jin|Wang, Jiayin|Wu, Yufeng', 'Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA. jinzhang@engr.uconn.edu|Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA. jinzhang@engr.uconn.edu|Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA. jinzhang@engr.uconn.edu', 'United States|United States|United States', 0, 'Chromosome Aberrations|Chromosome Breakage|Chromosome Structures|Gene Deletion|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Mutagenesis, Insertional|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-13-S6-S6', '22537045', 'Recent advances in sequencing technologies make it possible to comprehensively study structural variations (SVs) using sequence data of large-scale populations. Currently, more efforts have been taken to develop methods that call SVs with exact breakpoints. Among these approaches, split-read mapping methods can be applied on low-coverage sequence data. With increasing amount of data generated, more efficient split-read mapping methods are still needed. Also, since sequence errors can not be avoided for the current sequencing technologies, more accurate split-read mapping methods are still needed to better handle sequence errors.'),
(94922, 2012, 'bmc', 'PAIR: polymorphic Alu insertion recognition', 'Sveinbjörnsson, Jón Ingi|Halldórsson, Bjarni V', 'School of Science and Engineering, Reykjavik University, Reykjavík, 101, Iceland. jonis06@ru.is|School of Science and Engineering, Reykjavik University, Reykjavík, 101, Iceland. jonis06@ru.is', 'Iceland|Iceland', 0, 'Adult|Algorithms|Alu Elements|Child|Chromosomes, Human, Pair 22|Computer Simulation|Humans|Polymorphism, Genetic', 'Journal Article', '10.1186/1471-2105-13-S6-S7', '22537046', 'Alu polymorphisms are some of the most common polymorphisms in the genome, yet few methods have been developed for their detection.'),
(94923, 2012, 'bmc', 'High-resolution genetic mapping with pooled sequencing', 'Edwards, Matthew D|Gifford, David K', 'Computer Science and Artificial Intelligence Laboratory, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.|Computer Science and Artificial Intelligence Laboratory, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.', 'United States|United States', 0, 'Animals|Bayes Theorem|Case-Control Studies|Chromosome Mapping|Gene Frequency|Genetic Markers|Genotype|Humans|Models, Animal|Models, Statistical|Multilocus Sequence Typing|Phenotype|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-13-S6-S8', '22537047', 'Modern genetics has been transformed by high-throughput sequencing. New experimental designs in model organisms involve analyzing many individuals, pooled and sequenced in groups for increased efficiency. However, the uncertainty from pooling and the challenge of noisy sequencing data demand advanced computational methods.'),
(94924, 2012, 'bmc', 'A context-based approach to identify the most likely mapping for RNA-seq experiments', 'Bonfert, Thomas|Csaba, Gergely|Zimmer, Ralf|Friedel, Caroline C', 'Institute for Informatics, Ludwig-Maximilians-University Munich, Amalienstr, 17, 80333 Munich, Germany.|Institute for Informatics, Ludwig-Maximilians-University Munich, Amalienstr, 17, 80333 Munich, Germany.|Institute for Informatics, Ludwig-Maximilians-University Munich, Amalienstr, 17, 80333 Munich, Germany.|Institute for Informatics, Ludwig-Maximilians-University Munich, Amalienstr, 17, 80333 Munich, Germany.', 'Germany|Germany|Germany|Germany', 8, 'Algorithms|Animals|Genome|Humans|Mice|RNA Splicing|RNA, Messenger|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1186/1471-2105-13-S6-S9', '22537048', 'Sequencing of mRNA (RNA-seq) by next generation sequencing technologies is widely used for analyzing the transcriptomic state of a cell. Here, one of the main challenges is the mapping of a sequenced read to its transcriptomic origin. As a simple alignment to the genome will fail to identify reads crossing splice junctions and a transcriptome alignment will miss novel splice sites, several approaches have been developed for this purpose. Most of these approaches have two drawbacks. First, each read is assigned to a location independent on whether the corresponding gene is expressed or not, i.e. information from other reads is not taken into account. Second, in case of multiple possible mappings, the mapping with the fewest mismatches is usually chosen which may lead to wrong assignments due to sequencing errors.'),
(94925, 2012, 'bmc', 'Predicting the outer membrane proteome of Pasteurella multocida based on consensus prediction enhanced by results integration and manual confirmation', 'E-komon, Teerasak|Burchmore, Richard|Herzyk, Pawel|Davies, Robert', 'Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir Graeme Davies Building, Glasgow G12 8QQ, UK.|Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir Graeme Davies Building, Glasgow G12 8QQ, UK.|Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir Graeme Davies Building, Glasgow G12 8QQ, UK.|Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Sir Graeme Davies Building, Glasgow G12 8QQ, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 16, 'Algorithms|Bacterial Outer Membrane Proteins|Computational Biology|Pasteurella multocida|Protein Structure, Tertiary|Proteome', 'Journal Article', '10.1186/1471-2105-13-63', '22540951', 'Outer membrane proteins (OMPs) of Pasteurella multocida have various functions related to virulence and pathogenesis and represent important targets for vaccine development. Various bioinformatic algorithms can predict outer membrane localization and discriminate OMPs by structure or function. The designation of a confident prediction framework by integrating different predictors followed by consensus prediction, results integration and manual confirmation will improve the prediction of the outer membrane proteome.'),
(94926, 2012, 'bmc', 'Comprehensive comparison of graph based multiple protein sequence alignment strategies', 'Plyusnin, Ilya|Holm, Liisa', 'Institute of Biotechnology, University of Helsinki, P,O, Box 56, Viikinkaari 5, Helsinki, Finland. Ilja.Pljusnin@gmail.com|Institute of Biotechnology, University of Helsinki, P,O, Box 56, Viikinkaari 5, Helsinki, Finland. Ilja.Pljusnin@gmail.com', 'Finland|Finland', 4, 'Algorithms|Amino Acid Motifs|Proteins|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-13-64', '22540977', 'Alignment of protein sequences (MPSA) is the starting point for a multitude of applications in molecular biology. Here, we present a novel MPSA program based on the SeqAn sequence alignment library. Our implementation has a strict modular structure, which allows to swap different components of the alignment process and, thus, to investigate their contribution to the alignment quality and computation time. We systematically varied information sources, guiding trees, score transformations and iterative refinement options, and evaluated the resulting alignments on BAliBASE and SABmark.'),
(94927, 2012, 'bmc', 'The MULTICOM toolbox for protein structure prediction', 'Cheng, Jianlin|Li, Jilong|Wang, Zheng|Eickholt, Jesse|Deng, Xin', 'Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211, USA. chengji@missouri.edu|Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211, USA. chengji@missouri.edu|Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211, USA. chengji@missouri.edu|Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211, USA. chengji@missouri.edu|Department of Computer Science, University of Missouri-Columbia, Columbia, MO 65211, USA. chengji@missouri.edu', 'United States|United States|United States|United States|United States', 0, 'Computational Biology|Markov Chains|Models, Molecular|Protein Folding|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-13-65', '22545707', 'As genome sequencing is becoming routine in biomedical research, the total number of protein sequences is increasing exponentially, recently reaching over 108 million. However, only a tiny portion of these proteins (i.e. ~75,000 or < 0.07%) have solved tertiary structures determined by experimental techniques. The gap between protein sequence and structure continues to enlarge rapidly as the throughput of genome sequencing techniques is much higher than that of protein structure determination techniques. Computational software tools for predicting protein structure and structural features from protein sequences are crucial to make use of this vast repository of protein resources.'),
(94928, 2012, 'bmc', 'T3DB: an integrated database for bacterial type III secretion system', 'Wang, Yejun|Huang, He|Sun, Mingan|Zhang, Qing|Guo, Dianjing', 'School of Life Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.|School of Life Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.|School of Life Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.|School of Life Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.|School of Life Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 0, 'Bacteria|Bacterial Secretion Systems|Databases, Genetic|Genes, Bacterial|Molecular Chaperones|Molecular Sequence Annotation|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-66', '22545727', 'Type III Secretion System (T3SS), which plays important roles in pathogenesis or symbiosis, is widely expressed in a variety of gram negative bacteria. However, lack of unique nomenclature for T3SS genes has hindered T3SS related research. It is necessary to set up a knowledgebase integrating T3SS-related research data to facilitate the communication between different research groups interested in different bacteria.'),
(94929, 2012, 'bmc', 'Fitting hidden Markov models of protein domains to a target species: application to Plasmodium falciparum', 'Terrapon, Nicolas|Gascuel, Olivier|Marxc3xa9chal, Eric|Brxc3xa9hxc3xa9lin, Laurent', 'Mxc3xa9thodes et Algorithmes pour la Bioinformatique, LIRMM, Universitxc3xa9 Montpellier 2, France.|Mxc3xa9thodes et Algorithmes pour la Bioinformatique, LIRMM, Universitxc3xa9 Montpellier 2, France.|Mxc3xa9thodes et Algorithmes pour la Bioinformatique, LIRMM, Universitxc3xa9 Montpellier 2, France.|Mxc3xa9thodes et Algorithmes pour la Bioinformatique, LIRMM, Universitxc3xa9 Montpellier 2, France.', 'France|France|France|France', 0, 'Algorithms|Amino Acid Motifs|Databases, Protein|Markov Chains|Molecular Sequence Annotation|Plasmodium falciparum|Proteins|Proteome|Proteomics|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-13-67', '22548871', 'Hidden Markov Models (HMMs) are a powerful tool for protein domain identification. The Pfam database notably provides a large collection of HMMs which are widely used for the annotation of proteins in new sequenced organisms. In Pfam, each domain family is represented by a curated multiple sequence alignment from which a profile HMM is built. In spite of their high specificity, HMMs may lack sensitivity when searching for domains in divergent organisms. This is particularly the case for species with a biased amino-acid composition, such as P. falciparum, the main causal agent of human malaria. In this context, fitting HMMs to the specificities of the target proteome can help identify additional domains.'),
(94930, 2012, 'bmc', 'Accelerated maximum likelihood parameter estimation for stochastic biochemical systems', 'Daigle, Bernie J|Roh, Min K|Petzold, Linda R|Niemi, Jarad', 'Department of Computer Science, University of California Santa Barbara, 93106, USA.|Department of Computer Science, University of California Santa Barbara, 93106, USA.|Department of Computer Science, University of California Santa Barbara, 93106, USA.|Department of Computer Science, University of California Santa Barbara, 93106, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Biochemical Phenomena|Cell Polarity|Computer Simulation|GTP-Binding Proteins|Kinetics|Likelihood Functions|Models, Biological|Monte Carlo Method|Probability|Saccharomyces cerevisiae|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-13-68', '22548918', 'A prerequisite for the mechanistic simulation of a biochemical system is detailed knowledge of its kinetic parameters. Despite recent experimental advances, the estimation of unknown parameter values from observed data is still a bottleneck for obtaining accurate simulation results. Many methods exist for parameter estimation in deterministic biochemical systems, methods for discrete stochastic systems are less well developed. Given the probabilistic nature of stochastic biochemical models, a natural approach is to choose parameter values that maximize the probability of the observed data with respect to the unknown parameters, a.k.a. the maximum likelihood parameter estimates (MLEs). MLE computation for all but the simplest models requires the simulation of many system trajectories that are consistent with experimental data. For models with unknown parameters, this presents a computational challenge, as the generation of consistent trajectories can be an extremely rare occurrence.'),
(94931, 2012, 'bmc', 'Prognostic gene signatures for patient stratification in breast cancer: accuracy, stability and interpretability of gene selection approaches using prior knowledge on protein-protein interactions', 'Cun, Yupeng|Fröhlich, Holger Fröhlichholger', 'Algorithmic Bioinformatics, Bonn-Aachen International Center for IT, Dahlmannstraße, Bonn, Germany.|Algorithmic Bioinformatics, Bonn-Aachen International Center for IT, Dahlmannstraße, Bonn, Germany.', 'Germany|Germany', 30, 'Adult|Algorithms|Biomarkers|Breast Neoplasms|Female|Forecasting|Gene Expression Profiling|Genes, Neoplasm|Humans|Prognosis|Protein Interaction Mapping|Reproducibility of Results|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-13-69', '22548963', 'Stratification of patients according to their clinical prognosis is a desirable goal in cancer treatment in order to achieve a better personalized medicine. Reliable predictions on the basis of gene signatures could support medical doctors on selecting the right therapeutic strategy. However, during the last years the low reproducibility of many published gene signatures has been criticized. It has been suggested that incorporation of network or pathway information into prognostic biomarker discovery could improve prediction performance. In the meanwhile a large number of different approaches have been suggested for the same purpose.'),
(94932, 2012, 'bmc', 'A unified computational model for revealing and predicting subtle subtypes of cancers', 'Ren, Xianwen|Wang, Yong|Wang, Jiguang|Zhang, Xiang-Sun', 'MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.|MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.|MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.|MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.', 'China|China|China|China', 0, 'Algorithms|Breast Neoplasms|Cluster Analysis|Computational Biology|Computer Simulation|Female|Gene Expression Profiling|Humans|Leukemia|Neoplasms|Software', 'Journal Article', '10.1186/1471-2105-13-70', '22548981', 'Gene expression profiling technologies have gradually become a community standard tool for clinical applications. For example, gene expression data has been analyzed to reveal novel disease subtypes (class discovery) and assign particular samples to well-defined classes (class prediction). In the past decade, many effective methods have been proposed for individual applications. However, there is still a pressing need for a unified framework that can reveal the complicated relationships between samples.'),
(94933, 2012, 'bmc', 'Cancer bioinformatics: a new approach to systems clinical medicine', 'Wu, Duojiao|Rice, Catherine M|Wang, Xiangdong', 'MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.|MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.|MOH Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.', 'China|China|China', 0, 'Biomarkers, Tumor|Computational Biology|Humans|Neoplasms|Systems Biology', 'Editorial', '10.1186/1471-2105-13-71', '22549015', '-'),
(94934, 2012, 'bmc', 'Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis', 'Ueki, Masao|Tamiya, Gen', 'Advanced Molecular Epidemiology Research Institute, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, Yamagata, Japan. uekimrsd@nifty.com|Advanced Molecular Epidemiology Research Institute, Faculty of Medicine, Yamagata University, 2-2-2 Iida-Nishi, Yamagata, Yamagata, Japan. uekimrsd@nifty.com', 'Japan|Japan', 0, 'Algorithms|Artificial Intelligence|Computer Simulation|Gene Expression|Genetic Predisposition to Disease|Genome, Human|Genome-Wide Association Study|Humans|Logistic Models|Models, Genetic|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1186/1471-2105-13-72', '22554139', 'Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs) is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS) however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed.'),
(94935, 2012, 'bmc', 'A Bayesian variable selection procedure to rank overlapping gene sets', 'Skarman, Axel|Shariati, Mohammad|Jans, Luc|Jiang, Li|Sørensen, Peter', 'Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Tjele DK-8830, Denmark.|Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Tjele DK-8830, Denmark.|Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Tjele DK-8830, Denmark.|Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Tjele DK-8830, Denmark.|Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Tjele DK-8830, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 5, 'Analysis of Variance|Animals|Bayes Theorem|Cattle|Escherichia coli Infections|Female|Gene Expression Profiling|Gene Regulatory Networks|Genes, Overlapping|Linear Models|Mastitis, Bovine', 'Journal Article', '10.1186/1471-2105-13-73', '22554182', 'Genome-wide expression profiling using microarrays or sequence-based technologies allows us to identify genes and genetic pathways whose expression patterns influence complex traits. Different methods to prioritize gene sets, such as the genes in a given molecular pathway, have been described. In many cases, these methods test one gene set at a time, and therefore do not consider overlaps among the pathways. Here, we present a Bayesian variable selection method to prioritize gene sets that overcomes this limitation by considering all gene sets simultaneously. We applied Bayesian variable selection to differential expression to prioritize the molecular and genetic pathways involved in the responses to Escherichia coli infection in Danish Holstein cows.'),
(94936, 2012, 'bmc', 'Inferring high-confidence human protein-protein interactions', 'Yu, Xueping|Wallqvist, Anders|Reifman, Jaques', 'Biotechnology High-Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Ft. Detrick, MD 21702, USA.|Biotechnology High-Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Ft. Detrick, MD 21702, USA.|Biotechnology High-Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Ft. Detrick, MD 21702, USA.', 'United States|United States|United States', 25, 'Databases, Protein|Genetic Predisposition to Disease|Humans|Multiprotein Complexes|Polymorphism, Single Nucleotide|Protein Interaction Mapping|Protein Interaction Maps|Proteins|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-13-79', '22558947', 'As numerous experimental factors drive the acquisition, identification, and interpretation of protein-protein interactions (PPIs), aggregated assemblies of human PPI data invariably contain experiment-dependent noise. Ascertaining the reliability of PPIs collected from these diverse studies and scoring them to infer high-confidence networks is a non-trivial task. Moreover, a large number of PPIs share the same number of reported occurrences, making it impossible to distinguish the reliability of these PPIs and rank-order them. For example, for the data analyzed here, we found that the majority (>83%) of currently available human PPIs have been reported only once.'),
(94937, 2012, 'bmc', 'Matching of array CGH and gene expression microarray features for the purpose of integrative genomic analyses', 'van Wieringen, Wessel N|Unger, Kristian|Leday, Gwenaël G R|Krijgsman, Oscar|de Menezes, Renée X|Ylstra, Bauke|van de Wiel, Mark A', 'Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl|Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl|Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl|Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl|Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl|Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl|Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands. w.vanwieringen@vumc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Comparative Genomic Hybridization|DNA Copy Number Variations|Gene Expression|Gene Expression Profiling|Genomics|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-13-80', '22559006', 'An increasing number of genomic studies interrogating more than one molecular level is published. Bioinformatics follows biological practice, and recent years have seen a surge in methodology for the integrative analysis of genomic data. Often such analyses require knowledge of which elements of one platform link to those of another. Although important, many integrative analyses do not or insufficiently detail the matching of the platforms.'),
(94938, 2012, 'bmc', 'False discovery rate control in two-stage designs', 'Zehetmayer, Sonja|Posch, Martin', 'Center for Medical Statistics, Informatics, and Complex Systems, Medical University of Vienna, Austria. sonja.zehetmayer@meduniwien.ac.at|Center for Medical Statistics, Informatics, and Complex Systems, Medical University of Vienna, Austria. sonja.zehetmayer@meduniwien.ac.at', 'Austria|Austria', 0, 'Data Interpretation, Statistical|False Positive Reactions|Research Design|Sample Size', 'Journal Article', '10.1186/1471-2105-13-81', '22559038', 'For gene expression or gene association studies with a large number of hypotheses the number of measurements per marker in a conventional single-stage design is often low due to limited resources. Two-stage designs have been proposed where in a first stage promising hypotheses are identified and further investigated in the second stage with larger sample sizes. For two types of two-stage designs proposed in the literature we derive multiple testing procedures controlling the False Discovery Rate (FDR) demonstrating FDR control by simulations: designs where a fixed number of top-ranked hypotheses are selected and designs where the selection in the interim analysis is based on an FDR threshold. In contrast to earlier approaches which use only the second-stage data in the hypothesis tests (pilot approach), the proposed testing procedures are based on the pooled data from both stages (integrated approach).'),
(94939, 2012, 'bmc', 'Readjoiner: a fast and memory efficient string graph-based sequence assembler', 'Gonnella, Giorgio|Kurtz, Stefan', 'Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany.|Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany.', 'Germany|Germany', 37, 'Algorithms|Computer Simulation|Genome, Human|Humans|Models, Genetic|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1186/1471-2105-13-82', '22559072', 'Ongoing improvements in throughput of the next-generation sequencing technologies challenge the current generation of de novo sequence assemblers. Most recent sequence assemblers are based on the construction of a de Bruijn graph. An alternative framework of growing interest is the assembly string graph, not necessitating a division of the reads into k-mers, but requiring fast algorithms for the computation of suffix-prefix matches among all pairs of reads.'),
(94940, 2012, 'bmc', 'Metaprotein expression modeling for label-free quantitative proteomics', 'Lucas, Joseph E|Thompson, J Will|Dubois, Laura G|McCarthy, Jeanette|Tillmann, Hans|Thompson, Alexander|Shire, Norah|Hendrickson, Ron|Dieguez, Francisco|Goldman, Phyllis|Schwarz, Kathleen|Patel, Keyur|McHutchison, John|Moseley, M Arthur', 'Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.edu|Institute for Genome Sciences and Policy, Duke University, Durham, NC, USA. joe@stat.duke.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|United States|United States', 5, 'Female|Hepatitis C, Chronic|Humans|Male|Models, Statistical|Peptides|Proteins|Proteome|Proteomics|Reproducibility of Results|Tandem Mass Spectrometry', 'Journal Article', '10.1186/1471-2105-13-74', '22559859', 'Label-free quantitative proteomics holds a great deal of promise for the future study of both medicine and biology. However, the data generated is extremely intricate in its correlation structure, and its proper analysis is complex. There are issues with missing identifications. There are high levels of correlation between many, but not all, of the peptides derived from the same protein. Additionally, there may be systematic shifts in the sensitivity of the machine between experiments or even through time within the duration of a single experiment.'),
(94941, 2012, 'bmc', 'Quantitatively integrating molecular structure and bioactivity profile evidence into drug-target relationship analysis', 'Xu, Tianlei|Zhu, Ruixin|Liu, Qi|Cao, Zhiwei', 'Department of Bioinformatics, Tongji University, 200092, Shanghai, China. qiliu@tongji.edu.cn|Department of Bioinformatics, Tongji University, 200092, Shanghai, China. qiliu@tongji.edu.cn|Department of Bioinformatics, Tongji University, 200092, Shanghai, China. qiliu@tongji.edu.cn|Department of Bioinformatics, Tongji University, 200092, Shanghai, China. qiliu@tongji.edu.cn', 'China|China|China|China', 0, 'Algorithms|Cluster Analysis|Computer Simulation|Drug Design|Drug Evaluation, Preclinical|Gene Expression|Molecular Structure|Pharmaceutical Preparations|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-13-75', '22559876', 'Public resources of chemical compound are in a rapid growth both in quantity and the types of data-representation. To comprehensively understand the relationship between the intrinsic features of chemical compounds and protein targets is an essential task to evaluate potential protein-binding function for virtual drug screening. In previous studies, correlations were proposed between bioactivity profiles and target networks, especially when chemical structures were similar. With the lack of effective quantitative methods to uncover such correlation, it is demanding and necessary for us to integrate the information from multiple data sources to produce an comprehensive assessment of the similarity between small molecules, as well as quantitatively uncover the relationship between compounds and their targets by such integrated schema.'),
(94942, 2012, 'bmc', 'EpiFire: An open source C++ library and application for contact network epidemiology', 'Hladish, Thomas|Melamud, Eugene|Barrera, Luis Alberto|Galvani, Alison|Meyers, Lauren Ancel', 'Section of Integrative Biology, University of Texas at Austin, 78712, USA. tjhladish@utexas.edu|Section of Integrative Biology, University of Texas at Austin, 78712, USA. tjhladish@utexas.edu|Section of Integrative Biology, University of Texas at Austin, 78712, USA. tjhladish@utexas.edu|Section of Integrative Biology, University of Texas at Austin, 78712, USA. tjhladish@utexas.edu|Section of Integrative Biology, University of Texas at Austin, 78712, USA. tjhladish@utexas.edu', 'United States|United States|United States|United States|United States', 16, 'Computer Simulation|Contact Tracing|Disease Transmission, Infectious|Humans|Models, Statistical|Software', 'Evaluation Studies', '10.1186/1471-2105-13-76', '22559915', 'Contact network models have become increasingly common in epidemiology, but we lack a flexible programming framework for the generation and analysis of epidemiological contact networks and for the simulation of disease transmission through such networks.'),
(94943, 2012, 'bmc', 'Tavaxy: integrating Taverna and Galaxy workflows with cloud computing support', 'Abouelhoda, Mohamed|Issa, Shadi Alaa|Ghanem, Moustafa', 'Center for Informatics Sciences, Nile University, Giza, Egypt. mabouelhoda@yahoo.com|Center for Informatics Sciences, Nile University, Giza, Egypt. mabouelhoda@yahoo.com|Center for Informatics Sciences, Nile University, Giza, Egypt. mabouelhoda@yahoo.com', 'Egypt|Egypt|Egypt', 0, 'Computational Biology|Internet|Metagenomics|Sequence Analysis|Software|Systems Integration|User-Computer Interface|Workflow', 'Journal Article', '10.1186/1471-2105-13-77', '22559942', 'Over the past decade the workflow system paradigm has evolved as an efficient and user-friendly approach for developing complex bioinformatics applications. Two popular workflow systems that have gained acceptance by the bioinformatics community are Taverna and Galaxy. Each system has a large user-base and supports an ever-growing repository of application workflows. However, workflows developed for one system cannot be imported and executed easily on the other. The lack of interoperability is due to differences in the models of computation, workflow languages, and architectures of both systems. This lack of interoperability limits sharing of workflows between the user communities and leads to duplication of development efforts.'),
(94944, 2012, 'bmc', 'Evolving stochastic context--free grammars for RNA secondary structure prediction', 'Wj Anderson, James|Tataru, Paula|Staines, Joe|Hein, Jotun|Lyngsø, Rune', 'Center for Informatics Sciences, Nile University, Giza, Egypt. mabouelhoda@yahoo.com|Center for Informatics Sciences, Nile University, Giza, Egypt. mabouelhoda@yahoo.com|Center for Informatics Sciences, Nile University, Giza, Egypt. mabouelhoda@yahoo.com|Center for Informatics Sciences, Nile University, Giza, Egypt. mabouelhoda@yahoo.com|Center for Informatics Sciences, Nile University, Giza, Egypt. mabouelhoda@yahoo.com', 'Egypt|Egypt|Egypt|Egypt|Egypt', 19, 'Algorithms|Computational Biology|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-13-78', '22559985', 'Stochastic Context-Free Grammars (SCFGs) were applied successfully to RNA secondary structure prediction in the early 90s, and used in combination with comparative methods in the late 90s. The set of SCFGs potentially useful for RNA secondary structure prediction is very large, but a few intuitively designed grammars have remained dominant. In this paper we investigate two automatic search techniques for effective grammars - exhaustive search for very compact grammars and an evolutionary algorithm to find larger grammars. We also examine whether grammar ambiguity is as problematic to structure prediction as has been previously suggested.'),
(94945, 2012, 'bmc', 'Detecting long tandem duplications in genomic sequences', 'Audemard, Eric|Schiex, Thomas|Faraut, Thomas', 'Unitxc3xa9 de Biomxc3xa9trie et Intelligence Artificielle, UR 875, INRA, Toulouse, France. Eric.Audemard@gmail.com|Unitxc3xa9 de Biomxc3xa9trie et Intelligence Artificielle, UR 875, INRA, Toulouse, France. Eric.Audemard@gmail.com|Unitxc3xa9 de Biomxc3xa9trie et Intelligence Artificielle, UR 875, INRA, Toulouse, France. Eric.Audemard@gmail.com', 'France|France|France', 5, 'Algorithms|Arabidopsis|Evolution, Molecular|Gene Duplication|Genome, Plant|Software', 'Journal Article', '10.1186/1471-2105-13-83', '22568762', 'Detecting duplication segments within completely sequenced genomes provides valuable information to address genome evolution and in particular the important question of the emergence of novel functions. The usual approach to gene duplication detection, based on all-pairs protein gene comparisons, provides only a restricted view of duplication.'),
(94946, 2012, 'bmc', 'Augmented annotation and orthologue analysis for Oryctolagus cuniculus: Better Bunny', 'Craig, Douglas B|Kannan, Sujatha|Dombkowski, Alan A', 'Department of Pediatrics, Wayne State University School of Medicine, Detroit, MI, USA.|Department of Pediatrics, Wayne State University School of Medicine, Detroit, MI, USA.|Department of Pediatrics, Wayne State University School of Medicine, Detroit, MI, USA.', 'United States|United States|United States', 16, 'Animals|Computational Biology|Databases, Genetic|Genome|Internet|Microarray Analysis|Molecular Sequence Annotation|Rabbits|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-84', '22568790', 'The rabbit is an important model organism used in a wide range of biomedical research. However, the rabbit genome is still sparsely annotated, thus prohibiting extensive functional analysis of gene sets derived from whole-genome experiments. We developed a web-based application that provides augmented annotation and orthologue analysis for rabbit genes. Importantly, the application allows comprehensive functional analysis through the use of orthologous relationships.'),
(94947, 2012, 'bmc', 'PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods', 'Francisco, Alexandre P|Vaz, Cátia|Monteiro, Pedro T|Melo-Cristino, José|Ramirez, Mário|Carriço, Joäo A', 'KDBIO, INESC-ID, , R, Alves Redol 9, 1000-029 Lisboa, Portugal.|KDBIO, INESC-ID, , R, Alves Redol 9, 1000-029 Lisboa, Portugal.|KDBIO, INESC-ID, , R, Alves Redol 9, 1000-029 Lisboa, Portugal.|KDBIO, INESC-ID, , R, Alves Redol 9, 1000-029 Lisboa, Portugal.|KDBIO, INESC-ID, , R, Alves Redol 9, 1000-029 Lisboa, Portugal.|KDBIO, INESC-ID, , R, Alves Redol 9, 1000-029 Lisboa, Portugal.', 'Portugal|Portugal|Portugal|Portugal|Portugal|Portugal', 277, 'Algorithms|Minisatellite Repeats|Multilocus Sequence Typing|Phylogeny|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software|Streptococcus pneumoniae', 'Journal Article', '10.1186/1471-2105-13-87', '22568821', 'With the decrease of DNA sequencing costs, sequence-based typing methods are rapidly becoming the gold standard for epidemiological surveillance. These methods provide reproducible and comparable results needed for a global scale bacterial population analysis, while retaining their usefulness for local epidemiological surveys. Online databases that collect the generated allelic profiles and associated epidemiological data are available but this wealth of data remains underused and are frequently poorly annotated since no user-friendly tool exists to analyze and explore it.'),
(94948, 2012, 'bmc', 'DIPSBC--data integration platform for systems biology collaborations', 'Dreher, Felix|Kreitler, Thomas|Hardt, Christopher|Kamburov, Atanas|Yildirimman, Reha|Schellander, Karl|Lehrach, Hans|Lange, Bodo M H|Herwig, Ralf', 'Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. dreher@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. dreher@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. dreher@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. dreher@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. dreher@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. dreher@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. dreher@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. dreher@molgen.mpg.de|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. dreher@molgen.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Computational Biology|Cooperative Behavior|Gene Expression Profiling|Genomics|Protein Interaction Maps|Proteomics|Systems Biology|Systems Integration', 'Journal Article', '10.1186/1471-2105-13-85', '22568834', 'Modern biomedical research is often organized in collaborations involving labs worldwide. In particular in systems biology, complex molecular systems are analyzed that require the generation and interpretation of heterogeneous data for their explanation, for example ranging from gene expression studies and mass spectrometry measurements to experimental techniques for detecting molecular interactions and functional assays. XML has become the most prominent format for representing and exchanging these data. However, besides the development of standards there is still a fundamental lack of data integration systems that are able to utilize these exchange formats, organize the data in an integrative way and link it with applications for data interpretation and analysis.'),
(94949, 2012, 'bmc', 'DNA methylation arrays as surrogate measures of cell mixture distribution', 'Houseman, Eugene Andres|Accomando, William P|Koestler, Devin C|Christensen, Brock C|Marsit, Carmen J|Nelson, Heather H|Wiencke, John K|Kelsey, Karl T', 'College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA. andres.houseman@oregonstate.edu|College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA. andres.houseman@oregonstate.edu|College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA. andres.houseman@oregonstate.edu|College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA. andres.houseman@oregonstate.edu|College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA. andres.houseman@oregonstate.edu|College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA. andres.houseman@oregonstate.edu|College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA. andres.houseman@oregonstate.edu|College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA. andres.houseman@oregonstate.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 1268, 'Computer Simulation|DNA Methylation|Data Interpretation, Statistical|Down Syndrome|Epigenesis, Genetic|Female|Gene Expression Profiling|Head and Neck Neoplasms|Humans|Leukocyte Count|Leukocytes|Obesity|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms', 'Journal Article', '10.1186/1471-2105-13-86', '22568884', 'There has been a long-standing need in biomedical research for a method that quantifies the normally mixed composition of leukocytes beyond what is possible by simple histological or flow cytometric assessments. The latter is restricted by the labile nature of protein epitopes, requirements for cell processing, and timely cell analysis. In a diverse array of diseases and following numerous immune-toxic exposures, leukocyte composition will critically inform the underlying immuno-biology to most chronic medical conditions. Emerging research demonstrates that DNA methylation is responsible for cellular differentiation, and when measured in whole peripheral blood, serves to distinguish cancer cases from controls.'),
(94950, 2012, 'bmc', 'SparSNP: fast and memory-efficient analysis of all SNPs for phenotype prediction', 'Abraham, Gad|Kowalczyk, Adam|Zobel, Justin|Inouye, Michael', 'NICTA Victoria Research Lab, Department of Computing and Information Systems, The University of Melbourne, Parkville 3010, Victoria, Australia. gabraham@csse.unimelb.edu.au|NICTA Victoria Research Lab, Department of Computing and Information Systems, The University of Melbourne, Parkville 3010, Victoria, Australia. gabraham@csse.unimelb.edu.au|NICTA Victoria Research Lab, Department of Computing and Information Systems, The University of Melbourne, Parkville 3010, Victoria, Australia. gabraham@csse.unimelb.edu.au|NICTA Victoria Research Lab, Department of Computing and Information Systems, The University of Melbourne, Parkville 3010, Victoria, Australia. gabraham@csse.unimelb.edu.au', 'Australia|Australia|Australia|Australia', 0, 'Celiac Disease|Computational Biology|Genomics|Humans|Linear Models|Phenotype|Polymorphism, Single Nucleotide|Software', 'Comparative Study', '10.1186/1471-2105-13-88', '22574887', 'A central goal of genomics is to predict phenotypic variation from genetic variation. Fitting predictive models to genome-wide and whole genome single nucleotide polymorphism (SNP) profiles allows us to estimate the predictive power of the SNPs and potentially develop diagnostic models for disease. However, many current datasets cannot be analysed with standard tools due to their large size.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94951, 2012, 'bmc', 'Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art', 'Walia, Rasna R|Caragea, Cornelia|Lewis, Benjamin A|Towfic, Fadi|Terribilini, Michael|El-Manzalawy, Yasser|Dobbs, Drena|Honavar, Vasant', 'Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA, USA. rwalia@iastate.edu|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA, USA. rwalia@iastate.edu|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA, USA. rwalia@iastate.edu|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA, USA. rwalia@iastate.edu|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA, USA. rwalia@iastate.edu|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA, USA. rwalia@iastate.edu|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA, USA. rwalia@iastate.edu|Bioinformatics and Computational Biology Program, Iowa State University, Ames, IA, USA. rwalia@iastate.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acids|Artificial Intelligence|Bayes Theorem|Humans|Position-Specific Scoring Matrices|Protein Conformation|RNA|RNA-Binding Proteins|Sequence Analysis, Protein|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-13-89', '22574904', 'RNA molecules play diverse functional and structural roles in cells. They function as messengers for transferring genetic information from DNA to proteins, as the primary genetic material in many viruses, as catalysts (ribozymes) important for protein synthesis and RNA processing, and as essential and ubiquitous regulators of gene expression in living organisms. Many of these functions depend on precisely orchestrated interactions between RNA molecules and specific proteins in cells. Understanding the molecular mechanisms by which proteins recognize and bind RNA is essential for comprehending the functional implications of these interactions, but the recognition code that mediates interactions between proteins and RNA is not yet understood. Success in deciphering this code would dramatically impact the development of new therapeutic strategies for intervening in devastating diseases such as AIDS and cancer. Because of the high cost of experimental determination of protein-RNA interfaces, there is an increasing reliance on statistical machine learning methods for training predictors of RNA-binding residues in proteins. However, because of differences in the choice of datasets, performance measures, and data representations used, it has been difficult to obtain an accurate assessment of the current state of the art in protein-RNA interface prediction.'),
(94952, 2012, 'bmc', 'Deterministic global optimization algorithm based on outer approximation for the parameter estimation of nonlinear dynamic biological systems', 'Miró, Anton|Pozo, Carlos|Guillén-Gosálbez, Gonzalo|Egea, Jose A|Jiménez, Laureano', 'Departament dEnginyeria Química, Universitat Rovira i Virgili, Tarragona, Spain.|Departament dEnginyeria Química, Universitat Rovira i Virgili, Tarragona, Spain.|Departament dEnginyeria Química, Universitat Rovira i Virgili, Tarragona, Spain.|Departament dEnginyeria Química, Universitat Rovira i Virgili, Tarragona, Spain.|Departament dEnginyeria Química, Universitat Rovira i Virgili, Tarragona, Spain.', 'Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Computer Simulation|HIV|HIV Protease|HIV Protease Inhibitors|Humans|Isomerism|Models, Biological|Monoterpenes|Nonlinear Dynamics', 'Journal Article', '10.1186/1471-2105-13-90', '22574924', 'The estimation of parameter values for mathematical models of biological systems is an optimization problem that is particularly challenging due to the nonlinearities involved. One major difficulty is the existence of multiple minima in which standard optimization methods may fall during the search. Deterministic global optimization methods overcome this limitation, ensuring convergence to the global optimum within a desired tolerance. Global optimization techniques are usually classified into stochastic and deterministic. The former typically lead to lower CPU times but offer no guarantee of convergence to the global minimum in a finite number of iterations. In contrast, deterministic methods provide solutions of a given quality (i.e., optimality gap), but tend to lead to large computational burdens.'),
(94953, 2012, 'bmc', 'GeVaDSs - decision support system for novel Genetic Vaccine development process', 'Blazewicz, Jacek|Borowski, Marcin|Chaara, Wahiba|Kedziora, Pawel|Klatzmann, David|Lukasiak, Piotr|Six, Adrien|Wojciechowski, Pawel', 'Institute of Computing Science, Poznaxc5x84 University of Technology, 60-965 Poznaxc5x84, Poland. Pawel.Wojciechowski@cs.put.poznan.pl|Institute of Computing Science, Poznaxc5x84 University of Technology, 60-965 Poznaxc5x84, Poland. Pawel.Wojciechowski@cs.put.poznan.pl|Institute of Computing Science, Poznaxc5x84 University of Technology, 60-965 Poznaxc5x84, Poland. Pawel.Wojciechowski@cs.put.poznan.pl|Institute of Computing Science, Poznaxc5x84 University of Technology, 60-965 Poznaxc5x84, Poland. Pawel.Wojciechowski@cs.put.poznan.pl|Institute of Computing Science, Poznaxc5x84 University of Technology, 60-965 Poznaxc5x84, Poland. Pawel.Wojciechowski@cs.put.poznan.pl|Institute of Computing Science, Poznaxc5x84 University of Technology, 60-965 Poznaxc5x84, Poland. Pawel.Wojciechowski@cs.put.poznan.pl|Institute of Computing Science, Poznaxc5x84 University of Technology, 60-965 Poznaxc5x84, Poland. Pawel.Wojciechowski@cs.put.poznan.pl|Institute of Computing Science, Poznaxc5x84 University of Technology, 60-965 Poznaxc5x84, Poland. Pawel.Wojciechowski@cs.put.poznan.pl', 'Poland|Poland|Poland|Poland|Poland|Poland|Poland|Poland', 4, 'B-Lymphocytes|Decision Support Techniques|Drug Design|Drug Evaluation|Europe|Humans|Information Storage and Retrieval|Software|T-Lymphocytes|Vaccination|Vaccines, DNA', 'Journal Article', '10.1186/1471-2105-13-91', '22574945', 'The lack of a uniform way for qualitative and quantitative evaluation of vaccine candidates under development led us to set up a standardized scheme for vaccine efficacy and safety evaluation. We developed and implemented molecular and immunology methods, and designed support tools for immunization data storage and analyses. Such collection can create a unique opportunity for immunologists to analyse data delivered from their laboratories.'),
(94954, 2012, 'bmc', 'A comparative evaluation of sequence classification programs', 'Bazinet, Adam L|Cummings, Michael P', 'Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20874, USA. adam.bazinet@umiacs.umd.edu|Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20874, USA. adam.bazinet@umiacs.umd.edu', 'United States|United States', 68, 'Algorithms|Computational Biology|Genomics|Metagenomics|Phylogeny|Sequence Alignment|Software', 'Comparative Study', '10.1186/1471-2105-13-92', '22574964', 'A fundamental problem in modern genomics is to taxonomically or functionally classify DNA sequence fragments derived from environmental sampling (i.e., metagenomics). Several different methods have been proposed for doing this effectively and efficiently, and many have been implemented in software. In addition to varying their basic algorithmic approach to classification, some methods screen sequence reads for barcoding genes like 16S rRNA, or various types of protein-coding genes. Due to the sheer number and complexity of methods, it can be difficult for a researcher to choose one that is well-suited for a particular analysis.'),
(94955, 2012, 'bmc', 'An in silico platform for the design of heterologous pathways in nonnative metabolite production', 'Chatsurachai, Sunisa|Furusawa, Chikara|Shimizu, Hiroshi', 'Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan.|Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan.|Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan.', 'Japan|Japan|Japan', 15, 'Algorithms|Computer Simulation|Corynebacterium glutamicum|Escherichia coli|Metabolic Networks and Pathways|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-13-93', '22578364', 'Microorganisms are used as cell factories to produce valuable compounds in pharmaceuticals, biofuels, and other industrial processes. Incorporating heterologous metabolic pathways into well-characterized hosts is a major strategy for obtaining these target metabolites and improving productivity. However, selecting appropriate heterologous metabolic pathways for a host microorganism remains difficult owing to the complexity of metabolic networks. Hence, metabolic network design could benefit greatly from the availability of an in silico platform for heterologous pathway searching.'),
(94956, 2012, 'bmc', 'Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology', 'Hill, Steven M|Neve, Richard M|Bayani, Nora|Kuo, Wen-Lin|Ziyad, Safiyyah|Spellman, Paul T|Gray, Joe W|Mukherjee, Sach', 'The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands. steven.hill@warwick.ac.uk|The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands. steven.hill@warwick.ac.uk|The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands. steven.hill@warwick.ac.uk|The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands. steven.hill@warwick.ac.uk|The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands. steven.hill@warwick.ac.uk|The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands. steven.hill@warwick.ac.uk|The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands. steven.hill@warwick.ac.uk|The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands. steven.hill@warwick.ac.uk', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Antineoplastic Agents|Bayes Theorem|Biomarkers, Pharmacological|Computer Simulation|Humans|Likelihood Functions|Models, Biological|Neoplasms|Probability|Research Design', 'Journal Article', '10.1186/1471-2105-13-94', '22578440', 'An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data.'),
(94957, 2012, 'bmc', '3DMolNavi: a web-based retrieval and navigation tool for flexible molecular shape comparison', 'Liu, Yu-Shen|Wang, Meng|Paul, Jean-Claude|Ramani, Karthik', 'School of Software, Tsinghua University, Beijing 100084, China. liuyushen@tsinghua.edu.cn|School of Software, Tsinghua University, Beijing 100084, China. liuyushen@tsinghua.edu.cn|School of Software, Tsinghua University, Beijing 100084, China. liuyushen@tsinghua.edu.cn|School of Software, Tsinghua University, Beijing 100084, China. liuyushen@tsinghua.edu.cn', 'China|China|China|China', 5, 'Algorithms|Databases, Protein|Information Storage and Retrieval|Internet|Molecular Conformation|Software|User-Computer Interface', 'Comparative Study', '10.1186/1471-2105-13-95', '22583488', 'Many molecules of interest are flexible and undergo significant shape deformation as part of their function, but most existing methods of molecular shape comparison treat them as rigid shapes, which may lead to incorrect measure of the shape similarity of flexible molecules. Currently, there still is a limited effort in retrieval and navigation for flexible molecular shape comparison, which would improve data retrieval by helping users locate the desirable molecule in a convenient way.'),
(94958, 2012, 'bmc', 'SIS: a program to generate draft genome sequence scaffolds for prokaryotes', 'Dias, Zanoni|Dias, Ulisses|Setubal, João C', 'Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, SP, Brazil. setubal@iq.usp.br.|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, SP, Brazil. setubal@iq.usp.br.|Departamento de Bioquímica, Instituto de Química, Universidade de São Paulo, São Paulo, SP, Brazil. setubal@iq.usp.br.', 'Brazil|Brazil|Brazil', 24, 'Algorithms|Chromosome Mapping|Computational Biology|Genome|Genomics|Prokaryotic Cells|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-13-96', '22583530', 'Decreasing costs of DNA sequencing have made prokaryotic draft genome sequences increasingly common. A contig scaffold is an ordering of contigs in the correct orientation. A scaffold can help genome comparisons and guide gap closure efforts. One popular technique for obtaining contig scaffolds is to map contigs onto a reference genome. However, rearrangements that may exist between the query and reference genomes may result in incorrect scaffolds, if these rearrangements are not taken into account. Large-scale inversions are common rearrangement events in prokaryotic genomes. Even in draft genomes it is possible to detect the presence of inversions given sufficient sequencing coverage and a sufficiently close reference genome.'),
(94959, 2012, 'bmc', 'Exploration of multivariate analysis in microbial coding sequence modeling', 'Mehmood, Tahir|Bohlin, Jon|Kristoffersen, Anja Bråthen|Sæbø, Solve|Warringer, Jonas|Snipen, Lars', 'Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Aas, Norway. tahir.mehmood@umb.no|Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Aas, Norway. tahir.mehmood@umb.no|Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Aas, Norway. tahir.mehmood@umb.no|Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Aas, Norway. tahir.mehmood@umb.no|Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Aas, Norway. tahir.mehmood@umb.no|Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Aas, Norway. tahir.mehmood@umb.no', 'Norway|Norway|Norway|Norway|Norway|Norway', 4, 'Algorithms|Archaea|Bacteria|Codon|Genes, Overlapping|Genomics|Markov Chains|Models, Genetic|Multivariate Analysis|Open Reading Frames|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-13-97', '22583558', 'Gene finding is a complicated procedure that encapsulates algorithms for coding sequence modeling, identification of promoter regions, issues concerning overlapping genes and more. In the present study we focus on coding sequence modeling algorithms, that is, algorithms for identification and prediction of the actual coding sequences from genomic DNA. In this respect, we promote a novel multivariate method known as Canonical Powered Partial Least Squares (CPPLS) as an alternative to the commonly used Interpolated Markov model (IMM). Comparisons between the methods were performed on DNA, codon and protein sequences with highly conserved genes taken from several species with different genomic properties.'),
(94960, 2012, 'bmc', 'The partitioned LASSO-patternsearch algorithm with application to gene expression data', 'Shi, Weiliang|Wahba, Grace|Irizarry, Rafael A|Bravo, Hector Corrada|Wright, Stephen J', 'Sanofi-Aventis, Cambridge, Massachusetts, USA. weiliang.shi@sanofi.com|Sanofi-Aventis, Cambridge, Massachusetts, USA. weiliang.shi@sanofi.com|Sanofi-Aventis, Cambridge, Massachusetts, USA. weiliang.shi@sanofi.com|Sanofi-Aventis, Cambridge, Massachusetts, USA. weiliang.shi@sanofi.com|Sanofi-Aventis, Cambridge, Massachusetts, USA. weiliang.shi@sanofi.com', 'United States|United States|United States|United States|United States', 6, 'Algorithms|Breast Neoplasms|Computer Simulation|Female|Gene Expression|Gene Expression Profiling|Genomics|Humans|Models, Genetic', 'Journal Article', '10.1186/1471-2105-13-98', '22587526', 'In systems biology, the task of reverse engineering gene pathways from data has been limited not just by the curse of dimensionality (the interaction space is huge) but also by systematic error in the data. The gene expression barcode reduces spurious association driven by batch effects and probe effects. The binary nature of the resulting expression calls lends itself perfectly to modern regularization approaches that thrive in high-dimensional settings.'),
(94961, 2012, 'bmc', 'Handling the data management needs of high-throughput sequencing data: SpeedGene, a compression algorithm for the efficient storage of genetic data', 'Qiao, Dandi|Yip, Wai-Ki|Lange, Christoph', 'Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA. dqiao@hsph.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA. dqiao@hsph.harvard.edu|Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA. dqiao@hsph.harvard.edu', 'United States|United States|United States', 12, 'Algorithms|Computational Biology|Data Compression|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1186/1471-2105-13-100', '22591016', 'As Next-Generation Sequencing data becomes available, existing hardware environments do not provide sufficient storage space and computational power to store and process the data due to their enormous size. This is and will be a frequent problem that is encountered everyday by researchers who are working on genetic data. There are some options available for compressing and storing such data, such as general-purpose compression software, PBAT/PLINK binary format, etc. However, these currently available methods either do not offer sufficient compression rates, or require a great amount of CPU time for decompression and loading every time the data is accessed.'),
(94962, 2012, 'bmc', 'MELTING, a flexible platform to predict the melting temperatures of nucleic acids', 'Dumousseau, Marine|Rodriguez, Nicolas|Juty, Nick|Le Novère, Nicolas', 'EMBL-EBI, Wellcome-Trust Genome Campus, Hinxton, UK.|EMBL-EBI, Wellcome-Trust Genome Campus, Hinxton, UK.|EMBL-EBI, Wellcome-Trust Genome Campus, Hinxton, UK.|EMBL-EBI, Wellcome-Trust Genome Campus, Hinxton, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 20, 'DNA|Nucleic Acid Denaturation|Nucleic Acid Hybridization|Nucleic Acids|RNA|Software|Temperature|Thermodynamics|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-101', '22591039', 'Computing accurate nucleic acid melting temperatures has become a crucial step for the efficiency and the optimisation of numerous molecular biology techniques such as in situ hybridization, PCR, antigene targeting, and microarrays. MELTING is a free open source software which computes the enthalpy, entropy and melting temperature of nucleic acids. MELTING 4.2 was able to handle several types of hybridization such as DNA/DNA, RNA/RNA, DNA/RNA and provided corrections to melting temperatures due to the presence of sodium. The program can use either an approximative approach or a more accurate Nearest-Neighbor approach.'),
(94963, 2012, 'bmc', 'MetaMapp: mapping and visualizing metabolomic data by integrating information from biochemical pathways and chemical and mass spectral similarity', 'Barupal, Dinesh K|Haldiya, Pradeep K|Wohlgemuth, Gert|Kind, Tobias|Kothari, Shanker L|Pinkerton, Kent E|Fiehn, Oliver', 'UC Davis Genome Center, Metabolomics, Davis, CA 95616, USA.|UC Davis Genome Center, Metabolomics, Davis, CA 95616, USA.|UC Davis Genome Center, Metabolomics, Davis, CA 95616, USA.|UC Davis Genome Center, Metabolomics, Davis, CA 95616, USA.|UC Davis Genome Center, Metabolomics, Davis, CA 95616, USA.|UC Davis Genome Center, Metabolomics, Davis, CA 95616, USA.|UC Davis Genome Center, Metabolomics, Davis, CA 95616, USA.', 'United States|United States|United States|United States|United States|United States|United States', 117, 'Animals|Databases, Chemical|Female|Gas Chromatography-Mass Spectrometry|Genome|Lung|Maternal Exposure|Metabolic Networks and Pathways|Metabolome|Metabolomics|Pregnancy|Rats|Rats, Sprague-Dawley|Tobacco Smoke Pollution', 'Journal Article', '10.1186/1471-2105-13-99', '22591066', 'Exposure to environmental tobacco smoke (ETS) leads to higher rates of pulmonary diseases and infections in children. To study the biochemical changes that may precede lung diseases, metabolomic effects on fetal and maternal lungs and plasma from rats exposed to ETS were compared to filtered air control animals. Genome- reconstructed metabolic pathways may be used to map and interpret dysregulation in metabolic networks. However, mass spectrometry-based non-targeted metabolomics datasets often comprise many metabolites for which links to enzymatic reactions have not yet been reported. Hence, network visualizations that rely on current biochemical databases are incomplete and also fail to visualize novel, structurally unidentified metabolites.'),
(94964, 2012, 'bmc', 'Workflows for microarray data processing in the Kepler environment', 'Stropp, Thomas|McPhillips, Timothy|Ludäscher, Bertram|Bieda, Mark', 'Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada.|Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada.|Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada.|Department of Biochemistry and Molecular Biology, University of Calgary, Calgary, AB, Canada.', 'Canada|Canada|Canada|Canada', 10, 'Chromatin Immunoprecipitation|Computational Biology|Computer Graphics|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface|Workflow', 'Journal Article', '10.1186/1471-2105-13-102', '22594911', 'Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services.'),
(94965, 2012, 'bmc', 'rCUR: an R package for CUR matrix decomposition', 'Bodor, András|Csabai, István|Mahoney, Michael W|Solymosi, Norbert', 'Department of the Physics of Complex Systems, Eötvös Loránd University, Pázmány Péter sétány 1/A, 1117, Budapest, Hungary.|Department of the Physics of Complex Systems, Eötvös Loránd University, Pázmány Péter sétány 1/A, 1117, Budapest, Hungary.|Department of the Physics of Complex Systems, Eötvös Loránd University, Pázmány Péter sétány 1/A, 1117, Budapest, Hungary.|Department of the Physics of Complex Systems, Eötvös Loránd University, Pázmány Péter sétány 1/A, 1117, Budapest, Hungary.', 'Hungary|Hungary|Hungary|Hungary', 16, 'Algorithms|Data Interpretation, Statistical|Genetic Phenomena|Hematopoiesis|Humans|Internet|Neoplasms|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-13-103', '22594948', 'Many methods for dimensionality reduction of large data sets such as those generated in microarray studies boil down to the Singular Value Decomposition (SVD). Although singular vectors associated with the largest singular values have strong optimality properties and can often be quite useful as a tool to summarize the data, they are linear combinations of up to all of the data points, and thus it is typically quite hard to interpret those vectors in terms of the application domain from which the data are drawn. Recently, an alternative dimensionality reduction paradigm, CUR matrix decompositions, has been proposed to address this problem and has been applied to genetic and internet data. CUR decompositions are low-rank matrix decompositions that are explicitly expressed in terms of a small number of actual columns and/or actual rows of the data matrix. Since they are constructed from actual data elements, CUR decompositions are interpretable by practitioners of the field from which the data are drawn.'),
(94966, 2012, 'bmc', 'Introduction: Advanced intelligent computing theories and their applications in bioinformatics', 'Gromiha, M Michael|Huang, De-Shuang', 'Department of the Physics of Complex Systems, Eötvös Loránd University, Pázmány Péter sétány 1/A, 1117, Budapest, Hungary.|Department of the Physics of Complex Systems, Eötvös Loránd University, Pázmány Péter sétány 1/A, 1117, Budapest, Hungary.', 'Hungary|Hungary', 1, 'Algorithms|Artificial Intelligence|Computational Biology|Gene Expression Profiling|Proteins', 'Introductory Journal Article', '10.1186/1471-2105-13-S7-I1', '22594994', '-'),
(94967, 2012, 'bmc', 'Relationship between amino acid properties and functional parameters in olfactory receptors and discrimination of mutants with enhanced specificity', 'Gromiha, M Michael|Harini, K|Sowdhamini, R|Fukui, Kazuhiko', 'Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India. gromiha@iitm.ac.in|Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India. gromiha@iitm.ac.in|Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India. gromiha@iitm.ac.in|Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India. gromiha@iitm.ac.in', 'India|India|India|India', 9, 'Amino Acid Substitution|Animals|Goldfish|Humans|Ligands|Mice|Molecular Conformation|Mutation|Odorants|Receptors, Odorant|Regression Analysis|Signal Transduction', 'Journal Article', '10.1186/1471-2105-13-S7-S1', '22594995', 'Olfactory receptors are key components in signal transduction. Mutations in olfactory receptors alter the odor response, which is a fundamental response of organisms to their immediate environment. Understanding the relationship between odorant response and mutations in olfactory receptors is an important problem in bioinformatics and computational biology. In this work, we have systematically analyzed the relationship between various physical, chemical, energetic and conformational properties of amino acid residues, and the change of odor response/compounds potency/half maximal effective concentration (EC50) due to amino acid substitutions.'),
(94968, 2012, 'bmc', 'Modeling the interactions of Alzheimer-related genes from the whole brain microarray data and diffusion tensor images of human brain', 'Park, Byungkyu|Lee, Wook|Han, Kyungsook', 'Institute for Information and Electronics Research, Inha University, Incheon, South Korea.|Institute for Information and Electronics Research, Inha University, Incheon, South Korea.|Institute for Information and Electronics Research, Inha University, Incheon, South Korea.', '-|-|-', 0, 'Alzheimer Disease|Brain|Hippocampus|Humans|Magnetic Resonance Imaging|Male|Nerve Tissue Proteins|Young Adult', 'Journal Article', '10.1186/1471-2105-13-S7-S10', '22594996', 'In recent years the genome-wide microarray-based gene expression profiles and diffusion tensor images (DTI) in human brain have been made available with accompanying anatomic and histology data. The challenge is to integrate various types of data to investigate the interactions of genes that are associated with specific neurological disorder.'),
(94969, 2012, 'bmc', 'Pattern-driven neighborhood search for biclustering of microarray data', 'Ayadi, Wassim|Elloumi, Mourad|Hao, Jin-Kao', 'LERIA, Université dAngers, 2 Boulevard Lavoisier, 49045 Angers Cedex 01, France.|LERIA, Université dAngers, 2 Boulevard Lavoisier, 49045 Angers Cedex 01, France.|LERIA, Université dAngers, 2 Boulevard Lavoisier, 49045 Angers Cedex 01, France.', 'France|France|France', 20, 'Algorithms|Cell Cycle|Cluster Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-13-S7-S11', '22594997', 'Biclustering aims at finding subgroups of genes that show highly correlated behaviors across a subgroup of conditions. Biclustering is a very useful tool for mining microarray data and has various practical applications. From a computational point of view, biclustering is a highly combinatorial search problem and can be solved with optimization methods.'),
(94970, 2012, 'bmc', 'Genovar: a detection and visualization tool for genomic variants', 'Jung, Kwang Su|Moon, Sanghoon|Kim, Young Jin|Kim, Bong-Jo|Park, Kiejung', 'Division of Bio-Medical Informatics, Center for Genome Science, Korea National Institute of Health, Osong, 363-951, Korea.|Division of Bio-Medical Informatics, Center for Genome Science, Korea National Institute of Health, Osong, 363-951, Korea.|Division of Bio-Medical Informatics, Center for Genome Science, Korea National Institute of Health, Osong, 363-951, Korea.|Division of Bio-Medical Informatics, Center for Genome Science, Korea National Institute of Health, Osong, 363-951, Korea.|Division of Bio-Medical Informatics, Center for Genome Science, Korea National Institute of Health, Osong, 363-951, Korea.', '-|-|-|-|-', 0, 'Chromosomes, Human|Comparative Genomic Hybridization|DNA Copy Number Variations|Genetic Predisposition to Disease|Genomics|Humans|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1186/1471-2105-13-S7-S12', '22594998', 'Along with single nucleotide polymorphisms (SNPs), copy number variation (CNV) is considered an important source of genetic variation associated with disease susceptibility. Despite the importance of CNV, the tools currently available for its analysis often produce false positive results due to limitations such as low resolution of array platforms, platform specificity, and the type of CNV. To resolve this problem, spurious signals must be separated from true signals by visual inspection. None of the previously reported CNV analysis tools support this function and the simultaneous visualization of comparative genomic hybridization arrays (aCGH) and sequence alignment. The purpose of the present study was to develop a useful program for the efficient detection and visualization of CNV regions that enables the manual exclusion of erroneous signals.'),
(94971, 2012, 'bmc', 'ProDis-ContSHC: learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval', 'Wang, Jingyan|Gao, Xin|Wang, Quanquan|Li, Yongping', 'King Abdullah University of Science and Technology (KAUST), Mathematical and Computer Sciences and Engineering Division, Thuwal, 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Mathematical and Computer Sciences and Engineering Division, Thuwal, 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Mathematical and Computer Sciences and Engineering Division, Thuwal, 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Mathematical and Computer Sciences and Engineering Division, Thuwal, 23955-6900, Saudi Arabia.', 'Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia', 38, 'Algorithms|Artificial Intelligence|Databases, Protein|Models, Chemical|Proteins', 'Journal Article', '10.1186/1471-2105-13-S7-S2', '22594999', 'The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. Traditional protein search methods rely on a pairwise dissimilarity/similarity measure for comparing a pair of proteins. This kind of pairwise measures suffer from the limitation of neglecting the distribution of other proteins and thus cannot satisfy the need for high accuracy of the retrieval systems. Recent work in the machine learning community has shown that exploiting the global structure of the database and learning the contextual dissimilarity/similarity measures can improve the retrieval performance significantly. However, most existing contextual dissimilarity/similarity learning algorithms work in an unsupervised manner, which does not utilize the information of the known class labels of proteins in the database.'),
(94972, 2012, 'bmc', 'Assessing and predicting protein interactions by combining manifold embedding with multiple information integration', 'Lei, Ying-Ke|You, Zhu-Hong|Ji, Zhen|Zhu, Lin|Huang, De-Shuang', 'Tongji University, 1239 Siping Road, Shanghai, PR China.|Tongji University, 1239 Siping Road, Shanghai, PR China.|Tongji University, 1239 Siping Road, Shanghai, PR China.|Tongji University, 1239 Siping Road, Shanghai, PR China.|Tongji University, 1239 Siping Road, Shanghai, PR China.', 'China|China|China|China|China', 39, 'Algorithms|Databases, Protein|Logistic Models|Protein Interaction Maps|Proteins|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-13-S7-S3', '22595000', 'Protein-protein interactions (PPIs) play crucial roles in virtually every aspect of cellular function within an organism. Over the last decade, the development of novel high-throughput techniques has resulted in enormous amounts of data and provided valuable resources for studying protein interactions. However, these high-throughput protein interaction data are often associated with high false positive and false negative rates. It is therefore highly desirable to develop scalable methods to identify these errors from the computational perspective.'),
(94973, 2012, 'bmc', 'An overlapping module identification method in protein-protein interaction networks', 'Wang, Xuesong|Li, Lijing|Cheng, Yuhu', 'School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, PR China. wangxuesongcumt@163.com|School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, PR China. wangxuesongcumt@163.com|School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, PR China. wangxuesongcumt@163.com', 'China|China|China', 0, 'Algorithms|Cluster Analysis|Protein Interaction Maps|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-13-S7-S4', '22595001', 'Previous studies have shown modular structures in PPI (protein-protein interaction) networks. More recently, many genome and metagenome investigations have focused on identifying modules in PPI networks. However, most of the existing methods are insufficient when applied to networks with overlapping modular structures. In our study, we describe a novel overlapping module identification method (OMIM) to address this problem.'),
(94974, 2012, 'bmc', 'Prediction of protein-protein interactions between viruses and human by an SVM model', 'Cui, Guangyu|Fang, Chao|Han, Kyungsook', 'School of Computer Science and Engineering, Inha University, Incheon, South Korea.|School of Computer Science and Engineering, Inha University, Incheon, South Korea.|School of Computer Science and Engineering, Inha University, Incheon, South Korea.', '-|-|-', 0, 'Amino Acid Sequence|Hepacivirus|Host-Pathogen Interactions|Humans|Papillomaviridae|Proteins|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-13-S7-S5', '22595002', 'Several computational methods have been developed to predict protein-protein interactions from amino acid sequences, but most of those methods are intended for the interactions within a species rather than for interactions across different species. Methods for predicting interactions between homogeneous proteins are not appropriate for finding those between heterogeneous proteins since they do not distinguish the interactions between proteins of the same species from those of different species.'),
(94975, 2012, 'bmc', 'Inferring a protein interaction map of Mycobacterium tuberculosis based on sequences and interologs', 'Liu, Zhi-Ping|Wang, Jiguang|Qiu, Yu-Qing|Leung, Ross K K|Zhang, Xiang-Sun|Tsui, Stephen K W|Chen, Luonan', 'Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. zpliu@sibs.ac.cn|Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. zpliu@sibs.ac.cn|Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. zpliu@sibs.ac.cn|Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. zpliu@sibs.ac.cn|Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. zpliu@sibs.ac.cn|Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. zpliu@sibs.ac.cn|Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China. zpliu@sibs.ac.cn', 'China|China|China|China|China|China|China', 0, 'Animals|Escherichia coli|Host-Pathogen Interactions|Humans|Mycobacterium tuberculosis|Protein Interaction Maps|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-13-S7-S6', '22595003', 'Mycobacterium tuberculosis is an infectious bacterium posing serious threats to human health. Due to the difficulty in performing molecular biology experiments to detect protein interactions, reconstruction of a protein interaction map of M. tuberculosis by computational methods will provide crucial information to understand the biological processes in the pathogenic microorganism, as well as provide the framework upon which new therapeutic approaches can be developed.'),
(94976, 2012, 'bmc', 'Exploring drug combinations in genetic interaction network', 'Wang, Yin-Ying|Xu, Ke-Jia|Song, Jiangning|Zhao, Xing-Ming', 'Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.', 'China|China|China|China', 29, 'Computational Biology|Drug Combinations|Drug Interactions|Drug Therapy|Humans', 'Journal Article', '10.1186/1471-2105-13-S7-S7', '22595004', 'Drug combination that consists of distinctive agents is an attractive strategy to combat complex diseases and has been widely used clinically with improved therapeutic effects. However, the identification of efficacious drug combinations remains a non-trivial and challenging task due to the huge number of possible combinations among the candidate drugs. As an important factor, the molecular context in which drugs exert their functions can provide crucial insights into the mechanism underlying drug combinations.'),
(94977, 2012, 'bmc', 'Inferring robust gene networks from expression data by a sensitivity-based incremental evolution method', 'Hsiao, Yu-Ting|Lee, Wei-Po', 'Department of Information Management, National Sun Yat-sen University, 70, Lienhai Road, Kaohsiung, Taiwan.|Department of Information Management, National Sun Yat-sen University, 70, Lienhai Road, Kaohsiung, Taiwan.', '-|-', 0, 'Algorithms|Computer Simulation|Escherichia coli|Gene Regulatory Networks|SOS Response (Genetics)', 'Journal Article', '10.1186/1471-2105-13-S7-S8', '22595005', 'Reconstructing gene regulatory networks (GRNs) from expression data is one of the most important challenges in systems biology research. Many computational models and methods have been proposed to automate the process of network reconstruction. Inferring robust networks with desired behaviours remains challenging, however. This problem is related to network dynamics but has yet to be investigated using network modeling.'),
(94978, 2012, 'bmc', 'Comparison of data-merging methods with SVM attribute selection and classification in breast cancer gene expression', 'Bevilacqua, Vitoantonio|Pannarale, Paolo|Abbrescia, Mirko|Cava, Claudia|Paradiso, Angelo|Tommasi, Stefania', 'Department of Electrical and Electronics, Polytechnic of Bari, Via E, Orabona, 4, 70125 Bari, Italy. bevilacqua@poliba.it|Department of Electrical and Electronics, Polytechnic of Bari, Via E, Orabona, 4, 70125 Bari, Italy. bevilacqua@poliba.it|Department of Electrical and Electronics, Polytechnic of Bari, Via E, Orabona, 4, 70125 Bari, Italy. bevilacqua@poliba.it|Department of Electrical and Electronics, Polytechnic of Bari, Via E, Orabona, 4, 70125 Bari, Italy. bevilacqua@poliba.it|Department of Electrical and Electronics, Polytechnic of Bari, Via E, Orabona, 4, 70125 Bari, Italy. bevilacqua@poliba.it|Department of Electrical and Electronics, Polytechnic of Bari, Via E, Orabona, 4, 70125 Bari, Italy. bevilacqua@poliba.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 31, 'Breast Neoplasms|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Neoplasm Metastasis|Oligonucleotide Array Sequence Analysis|Support Vector Machine', 'Comparative Study', '10.1186/1471-2105-13-S7-S9', '22595006', 'DNA microarray data are used to identify genes which could be considered prognostic markers. However, due to the limited sample size of each study, the signatures are unstable in terms of the composing genes and may be limited in terms of performances. It is therefore of great interest to integrate different studies, thus increasing sample size.'),
(94979, 2012, 'bmc', 'Profile-based short linear protein motif discovery', 'Haslam, Niall J|Shields, Denis C', 'Complex and Adaptive Systems Laboratory, University College Dublin, Ireland.|Complex and Adaptive Systems Laboratory, University College Dublin, Ireland.', 'Ireland|Ireland', 0, 'Amino Acid Motifs|Conserved Sequence|Databases, Protein|Humans|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-13-104', '22607209', 'Short linear protein motifs are attracting increasing attention as functionally independent sites, typically 3-10 amino acids in length that are enriched in disordered regions of proteins. Multiple methods have recently been proposed to discover over-represented motifs within a set of proteins based on simple regular expressions. Here, we extend these approaches to profile-based methods, which provide a richer motif representation.'),
(94980, 2012, 'bmc', 'Multiple structure alignment with msTALI', 'Shealy, Paul|Valafar, Homayoun', 'Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA.|Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA.', 'United States|United States', 13, 'Algorithms|Databases, Protein|Protein Structure, Secondary|Proteins|Sequence Alignment|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-13-105', '22607234', 'Multiple structure alignments have received increasing attention in recent years as an alternative to multiple sequence alignments. Although multiple structure alignment algorithms can potentially be applied to a number of problems, they have primarily been used for protein core identification. A method that is capable of solving a variety of problems using structure comparison is still absent. Here we introduce a program msTALI for aligning multiple protein structures. Our algorithm uses several informative features to guide its alignments: torsion angles, backbone Cxcexb1 atom positions, secondary structure, residue type, surface accessibility, and properties of nearby atoms. The algorithm allows the user to weight the types of information used to generate the alignment, which expands its utility to a wide variety of problems.'),
(94981, 2012, 'bmc', 'Natural product-likeness score revisited: an open-source, open-data implementation', 'Jayaseelan, Kalai Vanii|Moreno, Pablo|Truszkowski, Andreas|Ertl, Peter|Steinbeck, Christoph', 'Chemoinformatics and Metabolism, European Bioinformatics Institute (EBI), UK. kalai@ebi.ac.uk|Chemoinformatics and Metabolism, European Bioinformatics Institute (EBI), UK. kalai@ebi.ac.uk|Chemoinformatics and Metabolism, European Bioinformatics Institute (EBI), UK. kalai@ebi.ac.uk|Chemoinformatics and Metabolism, European Bioinformatics Institute (EBI), UK. kalai@ebi.ac.uk|Chemoinformatics and Metabolism, European Bioinformatics Institute (EBI), UK. kalai@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Biological Products|Combinatorial Chemistry Techniques|Computational Biology|Drug Design|Small Molecule Libraries|Software', 'Journal Article', '10.1186/1471-2105-13-106', '22607271', 'Natural product-likeness of a molecule, i.e. similarity of this molecule to the structure space covered by natural products, is a useful criterion in screening compound libraries and in designing new lead compounds. A closed source implementation of a natural product-likeness score, that finds its application in virtual screening, library design and compound selection, has been previously reported by one of us. In this note, we report an open-source and open-data re-implementation of this scoring system, illustrate its efficiency in ranking small molecules for natural product likeness and discuss its potential applications.'),
(94982, 2012, 'bmc', 'Highlights of the 1st IEEE Symposium on Biological Data Visualization', 'Kennedy, Jessie|Roerdink, Jos', 'Institute for Informatics & Digital Innovation, Edinburgh Napier University, UK. J.Kennedy@napier.ac.uk|Institute for Informatics & Digital Innovation, Edinburgh Napier University, UK. J.Kennedy@napier.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Computational Biology|Computer Graphics|Humans|Quantitative Trait Loci|Software', 'Introductory Journal Article', '10.1186/1471-2105-13-S8-S1', '22607328', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94983, 2012, 'bmc', 'iHAT: interactive hierarchical aggregation table for genetic association data', 'Heinrich, Julian|Vehlow, Corinna|Battke, Florian|Jäger, Günter|Weiskopf, Daniel|Nieselt, Kay', 'VISUS, University of Stuttgart, Allmandring 19, Stuttgart, Germany. julian.heinrich@visus.uni-stuttgart.de|VISUS, University of Stuttgart, Allmandring 19, Stuttgart, Germany. julian.heinrich@visus.uni-stuttgart.de|VISUS, University of Stuttgart, Allmandring 19, Stuttgart, Germany. julian.heinrich@visus.uni-stuttgart.de|VISUS, University of Stuttgart, Allmandring 19, Stuttgart, Germany. julian.heinrich@visus.uni-stuttgart.de|VISUS, University of Stuttgart, Allmandring 19, Stuttgart, Germany. julian.heinrich@visus.uni-stuttgart.de|VISUS, University of Stuttgart, Allmandring 19, Stuttgart, Germany. julian.heinrich@visus.uni-stuttgart.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Cluster Analysis|Genome-Wide Association Study|Genotype|Humans|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Software', 'Journal Article', '10.1186/1471-2105-13-S8-S2', '22607364', 'In the search for single-nucleotide polymorphisms which influence the observable phenotype, genome wide association studies have become an important technique for the identification of associations between genotype and phenotype of a diverse set of sequence-based data. We present a methodology for the visual assessment of single-nucleotide polymorphisms using interactive hierarchical aggregation techniques combined with methods known from traditional sequence browsers and cluster heatmaps. Our tool, the interactive Hierarchical Aggregation Table (iHAT), facilitates the visualization of multiple sequence alignments, associated metadata, and hierarchical clusterings. Different color maps and aggregation strategies as well as filtering options support the user in finding correlations between sequences and metadata. Similar to other visualizations such as parallel coordinates or heatmaps, iHAT relies on the human pattern-recognition ability for spotting patterns that might indicate correlation or anticorrelation. We demonstrate iHAT using artificial and real-world datasets for DNA and protein association studies as well as expression Quantitative Trait Locus data.'),
(94984, 2012, 'bmc', 'RuleBender: integrated modeling, simulation and visualization for rule-based intracellular biochemistry', 'Smith, Adam M|Xu, Wen|Sun, Yao|Faeder, James R|Marai, G Elisabeta', 'Department of Computer Science, University of Pittsburgh, PA 15260, USA. ams292@cs.pitt.edu|Department of Computer Science, University of Pittsburgh, PA 15260, USA. ams292@cs.pitt.edu|Department of Computer Science, University of Pittsburgh, PA 15260, USA. ams292@cs.pitt.edu|Department of Computer Science, University of Pittsburgh, PA 15260, USA. ams292@cs.pitt.edu|Department of Computer Science, University of Pittsburgh, PA 15260, USA. ams292@cs.pitt.edu', 'United States|United States|United States|United States|United States', 48, 'Algorithms|Biochemistry|Cells|Computer Systems|Image Processing, Computer-Assisted|Models, Biological|Signal Transduction|Software|Systems Biology', 'Journal Article', '10.1186/1471-2105-13-S8-S3', '22607382', 'Rule-based modeling (RBM) is a powerful and increasingly popular approach to modeling cell signaling networks. However, novel visual tools are needed in order to make RBM accessible to a broad range of users, to make specification of models less error prone, and to improve workflows.'),
(94985, 2012, 'bmc', 'HiTSEE KNIME: a visualization tool for hit selection and analysis in high-throughput screening experiments for the KNIME platform', 'Strobelt, Hendrik|Bertini, Enrico|Braun, Joachim|Deussen, Oliver|Groth, Ulrich|Mayer, Thomas U|Merhof, Dorit', 'Department of Computer Science, Konstanz University, Universitätsstrasse 10, Konstanz, Germany. hendrik@strobelt.com|Department of Computer Science, Konstanz University, Universitätsstrasse 10, Konstanz, Germany. hendrik@strobelt.com|Department of Computer Science, Konstanz University, Universitätsstrasse 10, Konstanz, Germany. hendrik@strobelt.com|Department of Computer Science, Konstanz University, Universitätsstrasse 10, Konstanz, Germany. hendrik@strobelt.com|Department of Computer Science, Konstanz University, Universitätsstrasse 10, Konstanz, Germany. hendrik@strobelt.com|Department of Computer Science, Konstanz University, Universitätsstrasse 10, Konstanz, Germany. hendrik@strobelt.com|Department of Computer Science, Konstanz University, Universitätsstrasse 10, Konstanz, Germany. hendrik@strobelt.com', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Anti-HIV Agents|Computational Biology|HIV|High-Throughput Screening Assays|Humans|Image Processing, Computer-Assisted|Kinesin|Small Molecule Libraries|Software|Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-13-S8-S4', '22607449', 'We present HiTSEE (High-Throughput Screening Exploration Environment), a visualization tool for the analysis of large chemical screens used to examine biochemical processes. The tool supports the investigation of structure-activity relationships (SAR analysis) and, through a flexible interaction mechanism, the navigation of large chemical spaces. Our approach is based on the projection of one or a few molecules of interest and the expansion around their neighborhood and allows for the exploration of large chemical libraries without the need to create an all encompassing overview of the whole library. We describe the requirements we collected during our collaboration with biologists and chemists, the design rationale behind the tool, and two case studies on different datasets. The described integration (HiTSEE KNIME) into the KNIME platform allows additional flexibility in adopting our approach to a wide range of different biochemical problems and enables other research groups to use HiTSEE.'),
(94986, 2012, 'bmc', 'VIPER: a visualisation tool for exploring inheritance inconsistencies in genotyped pedigrees', 'Paterson, Trevor|Graham, Martin|Kennedy, Jessie|Law, Andy', 'The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, Scotland, UK. trevor.paterson@roslin.ed.ac.uk|The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, Scotland, UK. trevor.paterson@roslin.ed.ac.uk|The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, Scotland, UK. trevor.paterson@roslin.ed.ac.uk|The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian, Scotland, UK. trevor.paterson@roslin.ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 7, 'Algorithms|Animals|Animals, Domestic|Computational Biology|Female|Genetic Markers|Genotype|Humans|Male|Pedigree|Software', 'Journal Article', '10.1186/1471-2105-13-S8-S5', '22607476', 'Pedigree genotype datasets are used for analysing genetic inheritance and to map genetic markers and traits. Such datasets consist of hundreds of related animals genotyped for thousands of genetic markers and invariably contain multiple errors in both the pedigree structure and in the associated individual genotype data. These errors manifest as apparent inheritance inconsistencies in the pedigree, and invalidate analyses of marker inheritance patterns across the dataset. Cleaning raw datasets of bad data points (incorrect pedigree relationships, unreliable marker assays, suspect samples, bad genotype results etc.) requires expert exploration of the patterns of exposed inconsistencies in the context of the inheritance pedigree. In order to assist this process we are developing VIPER (Visual Pedigree Explorer), a software tool that integrates an inheritance-checking algorithm with a novel space-efficient pedigree visualisation, so that reported inheritance inconsistencies are overlaid on an interactive, navigable representation of the pedigree structure.'),
(94987, 2012, 'bmc', 'OmicsVis: an interactive tool for visually analyzing metabolomics data', 'Livengood, Philip|Maciejewski, Ross|Chen, Wei|Ebert, David S', 'School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.|School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.|School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.|School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.', 'United States|United States|United States|United States', 0, 'Animals|Dogs|Gas Chromatography-Mass Spectrometry|Humans|Metabolomics|Mice|Neoplasms|Regression Analysis|Software', 'Journal Article', '10.1186/1471-2105-13-S8-S6', '22607515', 'When analyzing metabolomics data, cancer care researchers are searching for differences between known healthy samples and unhealthy samples. By analyzing and understanding these differences, researchers hope to identify cancer biomarkers. Due to the size and complexity of the data produced, however, analysis can still be very slow and time consuming. This is further complicated by the fact that datasets obtained will exhibit incidental differences in intensity and retention time, not related to actual chemical differences in the samples being evaluated. Additionally, automated tools to correct these errors do not always produce reliable results. This work presents a new analytics system that enables interactive comparative visualization and analytics of metabolomics data obtained by two-dimensional gas chromatography-mass spectrometry (GC × GC-MS). The key features of this system are the ability to produce visualizations of multiple GC × GC-MS data sets, and to explore those data sets interactively, allowing a user to discover differences and features in real time. The system provides statistical support in the form of difference, standard deviation, and kernel density estimation calculations to aid users in identifying meaningful differences between samples. These are combined with novel transfer functions and multiform, linked visualizations in order to provide researchers with a powerful new tool for GC × GC-MS exploration and bio-marker discovery.'),
(94988, 2012, 'bmc', 'NetMets: software for quantifying and visualizing errors in biological network segmentation', 'Mayerich, David|Bjornsson, Chris|Taylor, Jonathan|Roysam, Badrinath', 'Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, IL, USA. mayerich@illinois.edu|Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, IL, USA. mayerich@illinois.edu|Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, IL, USA. mayerich@illinois.edu|Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, IL, USA. mayerich@illinois.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Animals|Astrocytes|Brain|Cerebellum|Humans|Image Processing, Computer-Assisted|Mice|Models, Biological|Nerve Net|Neurons|Purkinje Cells|Software', 'Journal Article', '10.1186/1471-2105-13-S8-S7', '22607549', 'One of the major goals in biomedical image processing is accurate segmentation of networks embedded in volumetric data sets. Biological networks are composed of a meshwork of thin filaments that span large volumes of tissue. Examples of these structures include neurons and microvasculature, which can take the form of both hierarchical trees and fully connected networks, depending on the imaging modality and resolution. Network function depends on both the geometric structure and connectivity. Therefore, there is considerable demand for algorithms that segment biological networks embedded in three-dimensional data. While a large number of tracking and segmentation algorithms have been published, most of these do not generalize well across data sets. One of the major reasons for the lack of general-purpose algorithms is the limited availability of metrics that can be used to quantitatively compare their effectiveness against a pre-constructed ground-truth. In this paper, we propose a robust metric for measuring and visualizing the differences between network models. Our algorithm takes into account both geometry and connectivity to measure network similarity. These metrics are then mapped back onto an explicit model for visualization.'),
(94989, 2012, 'bmc', 'An eQTL biological data visualization challenge and approaches from the visualization community', 'Bartlett, Christopher W|Cheong, Soo Yeon|Hou, Liping|Paquette, Jesse|Lum, Pek Yee|Jäger, Günter|Battke, Florian|Vehlow, Corinna|Heinrich, Julian|Nieselt, Kay|Sakai, Ryo|Aerts, Jan|Ray, William C', 'The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org|The Research Institute at Nationwide Childrens Hospital, Columbus, Ohio, USA. christopher.bartlett@nationwidechildrens.org', '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', 10, 'Brain|Computer Simulation|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Quantitative Trait Loci', 'Journal Article', '10.1186/1471-2105-13-S8-S8', '22607587', 'In 2011, the IEEE VisWeek conferences inaugurated a symposium on Biological Data Visualization. Like other domain-oriented Vis symposia, this symposiums purpose was to explore the unique characteristics and requirements of visualization within the domain, and to enhance both the Visualization and Bio/Life-Sciences communities by pushing Biological data sets and domain understanding into the Visualization community, and well-informed Visualization solutions back to the Biological community. Amongst several other activities, the BioVis symposium created a data analysis and visualization contest. Unlike many contests in other venues, where the purpose is primarily to allow entrants to demonstrate tour-de-force programming skills on sample problems with known solutions, the BioVis contest was intended to whet the participants appetites for a tremendously challenging biological domain, and simultaneously produce viable tools for a biological grand challenge domain with no extant solutions. For this purpose expression Quantitative Trait Locus (eQTL) data analysis was selected. In the BioVis 2011 contest, we provided contestants with a synthetic eQTL data set containing real biological variation, as well as a spiked-in gene expression interaction network influenced by single nucleotide polymorphism (SNP) DNA variation and a hypothetical disease model. Contestants were asked to elucidate the pattern of SNPs and interactions that predicted an individuals disease state. 9 teams competed in the contest using a mixture of methods, some analytical and others through visual exploratory methods. Independent panels of visualization and biological experts judged entries. Awards were given for each panels favorite entry, and an overall best entry agreed upon by both panels. Three special mention awards were given for particularly innovative and useful aspects of those entries. And further recognition was given to entries that correctly answered a bonus question about how a proposed gene therapy change to a SNP might change an individuals disease status, which served as a calibration for each approaches applicability to a typical domain question. In the future, BioVis will continue the data analysis and visualization contest, maintaining the philosophy of providing new challenging questions in open-ended and dramatically underserved Bio/Life Sciences domains.'),
(94990, 2012, 'bmc', 'Learning sparse representations for fruit-fly gene expression pattern image annotation and retrieval', 'Yuan, Lei|Woodard, Alexander|Ji, Shuiwang|Jiang, Yuan|Zhou, Zhi-Hua|Kumar, Sudhir|Ye, Jieping', 'Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.|Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.|Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.|Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.|Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.|Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.|Center for Evolutionary Medicine and Informatics, The Biodesign Institute, Arizona State University, Tempe, AZ 85287, USA.', 'United States|United States|United States|United States|United States|United States|United States', 15, 'Animals|Data Mining|Databases, Factual|Drosophila melanogaster|Gene Expression Profiling|Internet|Molecular Sequence Annotation|Pattern Recognition, Automated|Software|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-13-107', '22621237', 'Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.'),
(94991, 2012, 'bmc', 'Extracting semantically enriched events from biomedical literature', 'Miwa, Makoto|Thompson, Paul|McNaught, John|Kell, Douglas B|Ananiadou, Sophia', 'The National Centre for Text Mining, Manchester Interdisciplinary Biocentre, University of Manchester, Manchester, UK. makoto.miwa@manchester.ac.uk|The National Centre for Text Mining, Manchester Interdisciplinary Biocentre, University of Manchester, Manchester, UK. makoto.miwa@manchester.ac.uk|The National Centre for Text Mining, Manchester Interdisciplinary Biocentre, University of Manchester, Manchester, UK. makoto.miwa@manchester.ac.uk|The National Centre for Text Mining, Manchester Interdisciplinary Biocentre, University of Manchester, Manchester, UK. makoto.miwa@manchester.ac.uk|The National Centre for Text Mining, Manchester Interdisciplinary Biocentre, University of Manchester, Manchester, UK. makoto.miwa@manchester.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 37, 'Artificial Intelligence|Computational Biology|Data Mining|MEDLINE|Semantics', 'Journal Article', '10.1186/1471-2105-13-108', '22621266', 'Research into event-based text mining from the biomedical literature has been growing in popularity to facilitate the development of advanced biomedical text mining systems. Such technology permits advanced search, which goes beyond document or sentence-based retrieval. However, existing event-based systems typically ignore additional information within the textual context of events that can determine, amongst other things, whether an event represents a fact, hypothesis, experimental result or analysis of results, whether it describes new or previously reported knowledge, and whether it is speculated or negated. We refer to such contextual information as meta-knowledge. The automatic recognition of such information can permit the training of systems allowing finer-grained searching of events according to the meta-knowledge that is associated with them.'),
(94992, 2012, 'bmc', 'Towards the identification of protein complexes and functional modules by integrating PPI network and gene expression data', 'Li, Min|Wu, Xuehong|Wang, Jianxin|Pan, Yi', 'School of Information Science and Engineering, Central South University, Changsha, China. limin@mail.csu.edu.cn|School of Information Science and Engineering, Central South University, Changsha, China. limin@mail.csu.edu.cn|School of Information Science and Engineering, Central South University, Changsha, China. limin@mail.csu.edu.cn|School of Information Science and Engineering, Central South University, Changsha, China. limin@mail.csu.edu.cn', 'China|China|China|China', 0, 'Algorithms|Cluster Analysis|Computational Biology|Gene Expression|Protein Interaction Mapping|Protein Interaction Maps|Saccharomyces cerevisiae Proteins', 'Comparative Study', '10.1186/1471-2105-13-109', '22621308', 'Identification of protein complexes and functional modules from protein-protein interaction (PPI) networks is crucial to understanding the principles of cellular organization and predicting protein functions. In the past few years, many computational methods have been proposed. However, most of them considered the PPI networks as static graphs and overlooked the dynamics inherent within these networks. Moreover, few of them can distinguish between protein complexes and functional modules.'),
(94993, 2012, 'bmc', 'TreeSnatcher plus: capturing phylogenetic trees from images', 'Laubach, Thomas|von Haeseler, Arndt|Lercher, Martin J', 'Department of Bioinformatics, Heinrich-Heine-University Duesseldorf, Universitaetsstrasse 1, Duesseldorf 40225, Germany. laubach@cs.uni-duesseldorf.de|Department of Bioinformatics, Heinrich-Heine-University Duesseldorf, Universitaetsstrasse 1, Duesseldorf 40225, Germany. laubach@cs.uni-duesseldorf.de|Department of Bioinformatics, Heinrich-Heine-University Duesseldorf, Universitaetsstrasse 1, Duesseldorf 40225, Germany. laubach@cs.uni-duesseldorf.de', 'Germany|Germany|Germany', 10, 'Biological Evolution|Image Processing, Computer-Assisted|Phylogeny|Software', 'Journal Article', '10.1186/1471-2105-13-110', '22624611', 'Figures of phylogenetic trees are widely used to illustrate the result of evolutionary analyses. However, one cannot easily extract a machine-readable representation from such images. Therefore, new software emerges that helps to preserve phylogenies digitally for future research.'),
(94994, 2012, 'bmc', 'MetaDisorder: a meta-server for the prediction of intrinsic disorder in proteins', 'Kozlowski, Lukasz P|Bujnicki, Janusz M', 'Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul, Trojdena 4, 02-109, Warsaw, Poland.|Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, ul, Trojdena 4, 02-109, Warsaw, Poland.', 'Poland|Poland', 199, 'Algorithms|Protein Conformation|Protein Unfolding|Proteins|Software|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-13-111', '22624656', 'Intrinsically unstructured proteins (IUPs) lack a well-defined three-dimensional structure. Some of them may assume a locally stable structure under specific conditions, e.g. upon interaction with another molecule, while others function in a permanently unstructured state. The discovery of IUPs challenged the traditional protein structure paradigm, which stated that a specific well-defined structure defines the function of the protein. As of December 2011, approximately 60 methods for computational prediction of protein disorder from sequence have been made publicly available. They are based on different approaches, such as utilizing evolutionary information, energy functions, and various statistical and machine learning methods.'),
(94995, 2012, 'bmc', 'OLSVis: an animated, interactive visual browser for bio-ontologies', 'Vercruysse, Steven|Venkatesan, Aravind|Kuiper, Martin', 'Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway. vercruys@nt.ntnu.no|Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway. vercruys@nt.ntnu.no|Department of Biology, Norwegian University of Science and Technology, Trondheim, Norway. vercruys@nt.ntnu.no', 'Norway|Norway|Norway', 0, 'Algorithms|Apc8 Subunit, Anaphase-Promoting Complex-Cyclosome|Biology|Cell Cycle Proteins|Humans|Information Storage and Retrieval|Internet|Mitochondria|Proteins|Software|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-13-116', '22646023', 'More than one million terms from biomedical ontologies and controlled vocabularies are available through the Ontology Lookup Service (OLS). Although OLS provides ample possibility for querying and browsing terms, the visualization of parts of the ontology graphs is rather limited and inflexible.'),
(94996, 2012, 'bmc', 'MergeAlign: improving multiple sequence alignment performance by dynamic reconstruction of consensus multiple sequence alignments', 'Collingridge, Peter W|Kelly, Steven', 'Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PBDevon, UK.|Marine Biological Association of the United Kingdom, The Laboratory, Citadel Hill, Plymouth PL1 2PBDevon, UK.', 'United Kingdom|United Kingdom', 46, 'Amino Acid Substitution|Consensus Sequence|Image Processing, Computer-Assisted|Phylogeny|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-13-117', '22646090', 'The generation of multiple sequence alignments (MSAs) is a crucial step for many bioinformatic analyses. Thus improving MSA accuracy and identifying potential errors in MSAs is important for a wide range of post-genomic research. We present a novel method called MergeAlign which constructs consensus MSAs from multiple independent MSAs and assigns an alignment precision score to each column.'),
(94997, 2012, 'bmc', 'Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs', 'Khan, Suleiman A|Faisal, Ali|Mpindi, John Patrick|Parkkinen, Juuso A|Kalliokoski, Tuomo|Poso, Antti|Kallioniemi, Olli P|Wennerberg, Krister|Kaski, Samuel', 'Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, PO Box 15400, Espoo, 00076, Finland. suleiman.khan@aalto.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, PO Box 15400, Espoo, 00076, Finland. suleiman.khan@aalto.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, PO Box 15400, Espoo, 00076, Finland. suleiman.khan@aalto.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, PO Box 15400, Espoo, 00076, Finland. suleiman.khan@aalto.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, PO Box 15400, Espoo, 00076, Finland. suleiman.khan@aalto.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, PO Box 15400, Espoo, 00076, Finland. suleiman.khan@aalto.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, PO Box 15400, Espoo, 00076, Finland. suleiman.khan@aalto.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, PO Box 15400, Espoo, 00076, Finland. suleiman.khan@aalto.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University, PO Box 15400, Espoo, 00076, Finland. suleiman.khan@aalto.fi', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Antineoplastic Agents|Biomarkers, Pharmacological|Gene Expression Profiling|Genome, Human|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Structure-Activity Relationship|Systems Biology|Transcriptome', 'Journal Article', '10.1186/1471-2105-13-112', '22646858', 'Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the microarray gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed the biological response profiles into components, each linked to a characteristic chemical descriptor profile.'),
(94998, 2012, 'bmc', 'Molecular ecological network analyses', 'Deng, Ye|Jiang, Yi-Huei|Yang, Yunfeng|He, Zhili|Luo, Feng|Zhou, Jizhong', 'Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA.|Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA.|Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA.|Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA.|Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA.|Institute for Environmental Genomics and Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Computational Biology|Ecology|Ecosystem|Genes, rRNA|Metagenomics|RNA, Ribosomal, 16S|Software|Soil|Soil Microbiology|Temperature', 'Journal Article', '10.1186/1471-2105-13-113', '22646978', 'Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data.'),
(94999, 2012, 'bmc', 'Detection and correction of probe-level artefacts on microarrays', 'Petri, Tobias|Berchtold, Evi|Zimmer, Ralf|Friedel, Caroline C', 'Institute for Informatics, Ludwig-Maximilians-Universität München, Munich, Germany. petri@bio.ifi.lmu.de|Institute for Informatics, Ludwig-Maximilians-Universität München, Munich, Germany. petri@bio.ifi.lmu.de|Institute for Informatics, Ludwig-Maximilians-Universität München, Munich, Germany. petri@bio.ifi.lmu.de|Institute for Informatics, Ludwig-Maximilians-Universität München, Munich, Germany. petri@bio.ifi.lmu.de', 'Germany|Germany|Germany|Germany', 0, 'Artifacts|Data Interpretation, Statistical|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-13-114', '22647057', 'A recent large-scale analysis of Gene Expression Omnibus (GEO) data found frequent evidence for spatial defects in a substantial fraction of Affymetrix microarrays in the GEO. Nevertheless, in contrast to quality assessment, artefact detection is not widely used in standard gene expression analysis pipelines. Furthermore, although approaches have been proposed to detect diverse types of spatial noise on arrays, the correction of these artefacts is mostly left to either summarization methods or the corresponding arrays are completely discarded.'),
(95000, 2012, 'bmc', 'PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data Application and comparative study of selected tools', 'OCallaghan, Sean|De Souza, David P|Isaac, Andrew|Wang, Qiao|Hodkinson, Luke|Olshansky, Moshe|Erwin, Tim|Appelbe, Bill|Tull, Dedreia L|Roessner, Ute|Bacic, Antony|McConville, Malcolm J|Likixc4x87, Vladimir A', 'Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.|Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|', 0, 'Algorithms|Data Interpretation, Statistical|Gas Chromatography-Mass Spectrometry|Software', 'Comparative Study', '10.1186/1471-2105-13-115', '22647087', 'Gas chromatography-mass spectrometry (GC-MS) is a technique frequently used in targeted and non-targeted measurements of metabolites. Most existing software tools for processing of raw instrument GC-MS data tightly integrate data processing methods with graphical user interface facilitating interactive data processing. While interactive processing remains critically important in GC-MS applications, high-throughput studies increasingly dictate the need for command line tools, suitable for scripting of high-throughput, customized processing pipelines.'),
(95001, 2012, 'bmc', 'Predicting protein-ATP binding sites from primary sequence through fusing bi-profile sampling of multi-view features', 'Zhang, Ya-Nan|Yu, Dong-Jun|Li, Shu-Sen|Fan, Yong-Xian|Huang, Yan|Shen, Hong-Bin', 'Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.|Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.|Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.|Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.|Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.|Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.', 'China|China|China|China|China|China', 0, 'Adenosine Triphosphate|Binding Sites|Computational Biology|Databases, Protein|Proteins|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-13-118', '22651691', 'Adenosine-5-triphosphate (ATP) is one of multifunctional nucleotides and plays an important role in cell biology as a coenzyme interacting with proteins. Revealing the binding sites between protein and ATP is significantly important to understand the functionality of the proteins and the mechanisms of protein-ATP complex.'),
(95002, 2012, 'bmc', 'Biomine: predicting links between biological entities using network models of heterogeneous databases', 'Eronen, Lauri|Toivonen, Hannu', 'Biocomputing Platforms Ltd, Innopoli 2, Tekniikantie 14, , FI-02150 Espoo, Finland. lauri.eronen@cs.helsinki.fi|Biocomputing Platforms Ltd, Innopoli 2, Tekniikantie 14, , FI-02150 Espoo, Finland. lauri.eronen@cs.helsinki.fi', 'Finland|Finland', 0, 'Algorithms|Databases, Genetic|Genetic Association Studies|Genetic Predisposition to Disease|Humans|Kruppel-Like Factor 6|Kruppel-Like Transcription Factors|Phosphatidylinositol 3-Kinases|Proteins|Proto-Oncogene Proteins|Software|Stomach Neoplasms', 'Evaluation Studies', '10.1186/1471-2105-13-119', '22672646', 'Biological databases contain large amounts of data concerning the functions and associations of genes and proteins. Integration of data from several such databases into a single repository can aid the discovery of previously unknown connections spanning multiple types of relationships and databases.'),
(95003, 2012, 'bmc', 'On the hypothesis-free testing of metabolite ratios in genome-wide and metabolome-wide association studies', 'Petersen, Ann-Kristin|Krumsiek, Jan|Wxc3xa4gele, Brigitte|Theis, Fabian J|Wichmann, H-Erich|Gieger, Christian|Suhre, Karsten', 'Institute of Genetic Epidemiology, Helmholtz Zentrum Mxc3xbcnchen, Neuherberg, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum Mxc3xbcnchen, Neuherberg, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum Mxc3xbcnchen, Neuherberg, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum Mxc3xbcnchen, Neuherberg, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum Mxc3xbcnchen, Neuherberg, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum Mxc3xbcnchen, Neuherberg, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum Mxc3xbcnchen, Neuherberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 51, 'Computer Simulation|Genome, Human|Genome-Wide Association Study|Humans|Male|Metabolome', 'Journal Article', '10.1186/1471-2105-13-120', '22672667', 'Genome-wide association studies (GWAS) with metabolic traits and metabolome-wide association studies (MWAS) with traits of biomedical relevance are powerful tools to identify the contribution of genetic, environmental and lifestyle factors to the etiology of complex diseases. Hypothesis-free testing of ratios between all possible metabolite pairs in GWAS and MWAS has proven to be an innovative approach in the discovery of new biologically meaningful associations. The p-gain statistic was introduced as an ad-hoc measure to determine whether a ratio between two metabolite concentrations carries more information than the two corresponding metabolite concentrations alone. So far, only a rule of thumb was applied to determine the significance of the p-gain.'),
(95004, 2012, 'bmc', 'Detection of identity by descent using next-generation whole genome sequencing data', 'Su, Shu-Yi|Kasberger, Jay|Baranzini, Sergio|Byerley, William|Liao, Wilson|Oksenberg, Jorge|Sherr, Elliott|Jorgenson, Eric', 'Ernest Gallo Clinic and Research Center, University of California San Francisco, 5858 Horton St., Suite 200, Emeryville, CA 94608, USA. shuyisu@gallo.ucsf.edu|Ernest Gallo Clinic and Research Center, University of California San Francisco, 5858 Horton St., Suite 200, Emeryville, CA 94608, USA. shuyisu@gallo.ucsf.edu|Ernest Gallo Clinic and Research Center, University of California San Francisco, 5858 Horton St., Suite 200, Emeryville, CA 94608, USA. shuyisu@gallo.ucsf.edu|Ernest Gallo Clinic and Research Center, University of California San Francisco, 5858 Horton St., Suite 200, Emeryville, CA 94608, USA. shuyisu@gallo.ucsf.edu|Ernest Gallo Clinic and Research Center, University of California San Francisco, 5858 Horton St., Suite 200, Emeryville, CA 94608, USA. shuyisu@gallo.ucsf.edu|Ernest Gallo Clinic and Research Center, University of California San Francisco, 5858 Horton St., Suite 200, Emeryville, CA 94608, USA. shuyisu@gallo.ucsf.edu|Ernest Gallo Clinic and Research Center, University of California San Francisco, 5858 Horton St., Suite 200, Emeryville, CA 94608, USA. shuyisu@gallo.ucsf.edu|Ernest Gallo Clinic and Research Center, University of California San Francisco, 5858 Horton St., Suite 200, Emeryville, CA 94608, USA. shuyisu@gallo.ucsf.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Genetic Association Studies|Genetic Linkage|Genetics, Population|Genome, Human|Genotype|HapMap Project|High-Throughput Nucleotide Sequencing|Homozygote|Humans|Pedigree|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-13-121', '22672699', 'Identity by descent (IBD) has played a fundamental role in the discovery of genetic loci underlying human diseases. Both pedigree-based and population-based linkage analyses rely on estimating recent IBD, and evidence of ancient IBD can be used to detect population structure in genetic association studies. Various methods for detecting IBD, including those implemented in the soft- ware programs fastIBD and GERMLINE, have been developed in the past several years using population genotype data from microarray platforms. Now, next-generation DNA sequencing data is becoming increasingly available, enabling the comprehensive analysis of genomes, in- cluding identifying rare variants. These sequencing data may provide an opportunity to detect IBD with higher resolution than previously possible, potentially enabling the detection of disease causing loci that were previously undetectable with sparser genetic data.'),
(95005, 2012, 'bmc', 'Web tools for large-scale 3D biological images and atlases', 'Husz, Zsolt L|Burton, Nicholas|Hill, Bill|Milyaev, Nestor|Baldock, Richard A', 'MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, UK.|MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, UK.|MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, UK.|MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, UK.|MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computer Systems|Computers|Data Compression|Humans|Imaging, Three-Dimensional|Internet|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-13-122', '22676296', 'Large-scale volumetric biomedical image data of three or more dimensions are a significant challenge for distributed browsing and visualisation. Many images now exceed 10GB which for most users is too large to handle in terms of computer RAM and network bandwidth. This is aggravated when users need to access tens or hundreds of such images from an archive. Here we solve the problem for 2D section views through archive data delivering compressed tiled images enabling users to browse through very-large volume data in the context of a standard web-browser. The system provides an interactive visualisation for grey-level and colour 3D images including multiple image layers and spatial-data overlay.'),
(95006, 2012, 'bmc', 'Quartet decomposition server: a platform for analyzing phylogenetic trees', 'Mao, Fenglou|Williams, David|Zhaxybayeva, Olga|Poptsova, Maria|Lapierre, Pascal|Gogarten, J Peter|Xu, Ying', 'Department of Biochemistry and Molecular Biology, University of Georgia, 120 Green St, Athens, GA 30622, USA.|Department of Biochemistry and Molecular Biology, University of Georgia, 120 Green St, Athens, GA 30622, USA.|Department of Biochemistry and Molecular Biology, University of Georgia, 120 Green St, Athens, GA 30622, USA.|Department of Biochemistry and Molecular Biology, University of Georgia, 120 Green St, Athens, GA 30622, USA.|Department of Biochemistry and Molecular Biology, University of Georgia, 120 Green St, Athens, GA 30622, USA.|Department of Biochemistry and Molecular Biology, University of Georgia, 120 Green St, Athens, GA 30622, USA.|Department of Biochemistry and Molecular Biology, University of Georgia, 120 Green St, Athens, GA 30622, USA.', 'Georgia|Georgia|Georgia|Georgia|Georgia|Georgia|Georgia', 6, 'Genes, Bacterial|Genomics|Internet|Multigene Family|Phylogeny|Software', 'Journal Article', '10.1186/1471-2105-13-123', '22676320', 'The frequent exchange of genetic material among prokaryotes means that extracting a majority or plurality phylogenetic signal from many gene families, and the identification of gene families that are in significant conflict with the plurality signal is a frequent task in comparative genomics, and especially in phylogenomic analyses. Decomposition of gene trees into embedded quartets (unrooted trees each with four taxa) is a convenient and statistically powerful technique to address this challenging problem. This approach was shown to be useful in several studies of completely sequenced microbial genomes.'),
(95007, 2012, 'bmc', 'BioWord: a sequence manipulation suite for Microsoft Word', 'Anzaldi, Laura J|Muñoz-Fernández, Daniel|Erill, Ivan', 'Department of Biological Sciences, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA.|Department of Biological Sciences, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA.|Department of Biological Sciences, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA.', 'United States|United States|United States', 8, 'Algorithms|Computational Biology|Programming Languages|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-13-124', '22676326', 'The ability to manipulate, edit and process DNA and protein sequences has rapidly become a necessary skill for practicing biologists across a wide swath of disciplines. In spite of this, most everyday sequence manipulation tools are distributed across several programs and web servers, sometimes requiring installation and typically involving frequent switching between applications. To address this problem, here we have developed BioWord, a macro-enabled self-installing template for Microsoft Word documents that integrates an extensive suite of DNA and protein sequence manipulation tools.');
