@article {49606, title = {Orchestrating high-throughput genomic analysis with Bioconductor.}, volume = {12}, year = {2015}, month = {2015 Feb}, pages = {115-21}, abstract = {

Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors.

}, keywords = {Computational Biology, Gene Expression Profiling, Genomics, High-Throughput Screening Assays, Programming Languages, software, User-Computer Interface}, issn = {1548-7105}, doi = {10.1038/nmeth.3252}, author = {Huber, Wolfgang and Carey, Vincent J and Gentleman, Robert and Anders, Simon and Carlson, Marc and Carvalho, Benilton S and Bravo, H{\'e}ctor Corrada and Davis, Sean and Gatto, Laurent and Girke, Thomas and Gottardo, Raphael and Hahne, Florian and Hansen, Kasper D and Irizarry, Rafael A and Lawrence, Michael and Love, Michael I and MacDonald, James and Obenchain, Valerie and Ole{\'s}, Andrzej K and Pag{\`e}s, Herv{\'e} and Reyes, Alejandro and Shannon, Paul and Smyth, Gordon K and Tenenbaum, Dan and Waldron, Levi and Morgan, Martin} } @article {49602, title = {Epiviz: interactive visual analytics for functional genomics data.}, volume = {11}, year = {2014}, month = {2014 Sep}, pages = {938-40}, abstract = {

Visualization is an integral aspect of genomics data analysis. Algorithmic-statistical analysis and interactive visualization are most effective when used iteratively. Epiviz (http://epiviz.cbcb.umd.edu/), a web-based genome browser, and the Epivizr Bioconductor package allow interactive, extensible and reproducible visualization within a state-of-the-art data-analysis platform.

}, keywords = {algorithms, Chromosome mapping, Data Mining, database management systems, Databases, Genetic, Genomics, Internet, software, User-Computer Interface}, issn = {1548-7105}, doi = {10.1038/nmeth.3038}, author = {Chelaru, Florin and Smith, Llewellyn and Goldstein, Naomi and Bravo, H{\'e}ctor Corrada} } @article {49765, title = {InterPro in 2011: new developments in the family and domain prediction database.}, journal = {Nucleic Acids Res}, volume = {40}, year = {2012}, month = {2012 Jan}, pages = {D306-12}, abstract = {

InterPro (http://www.ebi.ac.uk/interpro/) is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.

}, keywords = {Databases, Protein, Protein Structure, Tertiary, Proteins, Sequence Analysis, Protein, software, Terminology as Topic, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkr948}, author = {Hunter, Sarah and Jones, Philip and Mitchell, Alex and Apweiler, Rolf and Attwood, Teresa K and Bateman, Alex and Bernard, Thomas and Binns, David and Bork, Peer and Burge, Sarah and de Castro, Edouard and Coggill, Penny and Corbett, Matthew and Das, Ujjwal and Daugherty, Louise and Duquenne, Lauranne and Finn, Robert D and Fraser, Matthew and Gough, Julian and Haft, Daniel and Hulo, Nicolas and Kahn, Daniel and Kelly, Elizabeth and Letunic, Ivica and Lonsdale, David and Lopez, Rodrigo and Madera, Martin and Maslen, John and McAnulla, Craig and McDowall, Jennifer and McMenamin, Conor and Mi, Huaiyu and Mutowo-Muellenet, Prudence and Mulder, Nicola and Natale, Darren and Orengo, Christine and Pesseat, Sebastien and Punta, Marco and Quinn, Antony F and Rivoire, Catherine and Sangrador-Vegas, Amaia and Selengut, Jeremy D and Sigrist, Christian J A and Scheremetjew, Maxim and Tate, John and Thimmajanarthanan, Manjulapramila and Thomas, Paul D and Wu, Cathy H and Yeats, Corin and Yong, Siew-Yit} } @article {38352, title = {InterPro in 2011: new developments in the family and domain prediction database}, journal = {Nucleic acids researchNucleic Acids Research}, volume = {40}, year = {2012}, note = {http://www.ncbi.nlm.nih.gov/pubmed/22096229?dopt=Abstract}, type = {10.1093/nar/gkr948}, abstract = {InterPro (http://www.ebi.ac.uk/interpro/) is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.}, keywords = {Databases, Protein, Protein Structure, Tertiary, Proteins, Sequence Analysis, Protein, software, Terminology as Topic, User-Computer Interface}, author = {Hunter, Sarah and Jones, Philip and Mitchell, Alex and Apweiler, Rolf and Attwood, Teresa K. and Bateman, Alex and Bernard, Thomas and Binns, David and Bork, Peer and Burge, Sarah and de Castro, Edouard and Coggill, Penny and Corbett, Matthew and Das, Ujjwal and Daugherty, Louise and Duquenne, Lauranne and Finn, Robert D. and Fraser, Matthew and Gough, Julian and Haft, Daniel and Hulo, Nicolas and Kahn, Daniel and Kelly, Elizabeth and Letunic, Ivica and Lonsdale, David and Lopez, Rodrigo and Madera, Martin and Maslen, John and McAnulla, Craig and McDowall, Jennifer and McMenamin, Conor and Mi, Huaiyu and Mutowo-Muellenet, Prudence and Mulder, Nicola and Natale, Darren and Orengo, Christine and Pesseat, Sebastien and Punta, Marco and Quinn, Antony F. and Rivoire, Catherine and Sangrador-Vegas, Amaia and J. Selengut and Sigrist, Christian J. A. and Scheremetjew, Maxim and Tate, John and Thimmajanarthanan, Manjulapramila and Thomas, Paul D. and Wu, Cathy H. and Yeats, Corin and Yong, Siew-Yit} } @article {49783, title = {New developments in the InterPro database.}, journal = {Nucleic Acids Res}, volume = {35}, year = {2007}, month = {2007 Jan}, pages = {D224-8}, abstract = {

InterPro is an integrated resource for protein families, domains and functional sites, which integrates the following protein signature databases: PROSITE, PRINTS, ProDom, Pfam, SMART, TIGRFAMs, PIRSF, SUPERFAMILY, Gene3D and PANTHER. The latter two new member databases have been integrated since the last publication in this journal. There have been several new developments in InterPro, including an additional reading field, new database links, extensions to the web interface and additional match XML files. InterPro has always provided matches to UniProtKB proteins on the website and in the match XML file on the FTP site. Additional matches to proteins in UniParc (UniProt archive) are now available for download in the new match XML files only. The latest InterPro release (13.0) contains more than 13 000 entries, covering over 78\% of all proteins in UniProtKB. The database is available for text- and sequence-based searches via a webserver (http://www.ebi.ac.uk/interpro), and for download by anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro). The InterProScan search tool is now also available via a web service at http://www.ebi.ac.uk/Tools/webservices/WSInterProScan.html.

}, keywords = {Databases, Protein, Internet, Protein Structure, Tertiary, Proteins, Sequence Analysis, Protein, Systems Integration, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkl841}, author = {Mulder, Nicola J and Apweiler, Rolf and Attwood, Teresa K and Bairoch, Amos and Bateman, Alex and Binns, David and Bork, Peer and Buillard, Virginie and Cerutti, Lorenzo and Copley, Richard and Courcelle, Emmanuel and Das, Ujjwal and Daugherty, Louise and Dibley, Mark and Finn, Robert and Fleischmann, Wolfgang and Gough, Julian and Haft, Daniel and Hulo, Nicolas and Hunter, Sarah and Kahn, Daniel and Kanapin, Alexander and Kejariwal, Anish and Labarga, Alberto and Langendijk-Genevaux, Petra S and Lonsdale, David and Lopez, Rodrigo and Letunic, Ivica and Madera, Martin and Maslen, John and McAnulla, Craig and McDowall, Jennifer and Mistry, Jaina and Mitchell, Alex and Nikolskaya, Anastasia N and Orchard, Sandra and Orengo, Christine and Petryszak, Robert and Selengut, Jeremy D and Sigrist, Christian J A and Thomas, Paul D and Valentin, Franck and Wilson, Derek and Wu, Cathy H and Yeats, Corin} } @article {49679, title = {SplicePort--an interactive splice-site analysis tool.}, journal = {Nucleic Acids Res}, volume = {35}, year = {2007}, month = {2007 Jul}, pages = {W285-91}, abstract = {

SplicePort is a web-based tool for splice-site analysis that allows the user to make splice-site predictions for submitted sequences. In addition, the user can also browse the rich catalog of features that underlies these predictions, and which we have found capable of providing high classification accuracy on human splice sites. Feature selection is optimized for human splice sites, but the selected features are likely to be predictive for other mammals as well. With our interactive feature browsing and visualization tool, the user can view and explore subsets of features used in splice-site prediction (either the features that account for the classification of a specific input sequence or the complete collection of features). Selected feature sets can be searched, ranked or displayed easily. The user can group features into clusters and frequency plot WebLogos can be generated for each cluster. The user can browse the identified clusters and their contributing elements, looking for new interesting signals, or can validate previously observed signals. The SplicePort web server can be accessed at http://www.cs.umd.edu/projects/SplicePort and http://www.spliceport.org.

}, keywords = {Base Sequence, Chromosome mapping, Computational Biology, Computer simulation, DNA, Genome, HUMANS, Internet, Models, Genetic, Molecular Sequence Data, Pattern Recognition, Automated, RNA Splice Sites, sequence alignment, Sequence Analysis, DNA, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkm407}, author = {Dogan, Rezarta Islamaj and Getoor, Lise and Wilbur, W John and Mount, Stephen M} } @article {38530, title = {TIGRFAMs and Genome Properties: tools for the assignment of molecular function and biological process in prokaryotic genomes}, journal = {Nucleic acids researchNucleic Acids Research}, volume = {35}, year = {2007}, note = {http://www.ncbi.nlm.nih.gov/pubmed/17151080?dopt=Abstract}, type = {10.1093/nar/gkl1043}, abstract = {TIGRFAMs is a collection of protein family definitions built to aid in high-throughput annotation of specific protein functions. Each family is based on a hidden Markov model (HMM), where both cutoff scores and membership in the seed alignment are chosen so that the HMMs can classify numerous proteins according to their specific molecular functions. Most TIGRFAMs models describe {\textquoteright}equivalog{\textquoteright} families, where both orthology and lateral gene transfer may be part of the evolutionary history, but where a single molecular function has been conserved. The Genome Properties system contains a queriable set of metabolic reconstructions, genome metrics and extractions of information from the scientific literature. Its genome-by-genome assertions of whether or not specific structures, pathways or systems are present provide high-level conceptual descriptions of genomic content. These assertions enable comparative genomics, provide a meaningful biological context to aid in manual annotation, support assignments of Gene Ontology (GO) biological process terms and help validate HMM-based predictions of protein function. The Genome Properties system is particularly useful as a generator of phylogenetic profiles, through which new protein family functions may be discovered. The TIGRFAMs and Genome Properties systems can be accessed at http://www.tigr.org/TIGRFAMs and http://www.tigr.org/Genome_Properties.}, keywords = {Archaeal Proteins, Bacterial Proteins, Databases, Protein, Genome, Bacterial, Genomics, Internet, Phylogeny, software, User-Computer Interface}, author = {J. Selengut and Haft, Daniel H. and Davidsen, Tanja and Ganapathy, Anurhada and Gwinn-Giglio, Michelle and Nelson, William C. and Richter, R. Alexander and White, Owen} } @article {38294, title = {Genome Properties: a system for the investigation of prokaryotic genetic content for microbiology, genome annotation and comparative genomics}, journal = {Bioinformatics (Oxford, England)Bioinformatics (Oxford, England)}, volume = {21}, year = {2005}, note = {http://www.ncbi.nlm.nih.gov/pubmed/15347579?dopt=Abstract}, type = {10.1093/bioinformatics/bti015}, abstract = {MOTIVATION: The presence or absence of metabolic pathways and structures provide a context that makes protein annotation far more reliable. Compiling such information across microbial genomes improves the functional classification of proteins and provides a valuable resource for comparative genomics. RESULTS: We have created a Genome Properties system to present key aspects of prokaryotic biology using standardized computational methods and controlled vocabularies. Properties reflect gene content, phenotype, phylogeny and computational analyses. The results of searches using hidden Markov models allow many properties to be deduced automatically, especially for families of proteins (equivalogs) conserved in function since their last common ancestor. Additional properties are derived from curation, published reports and other forms of evidence. Genome Properties system was applied to 156 complete prokaryotic genomes, and is easily mined to find differences between species, correlations between metabolic features and families of uncharacterized proteins, or relationships among properties. AVAILABILITY: Genome Properties can be found at http://www.tigr.org/Genome_Properties SUPPLEMENTARY INFORMATION: http://www.tigr.org/tigr-scripts/CMR2/genome_properties_references.spl.}, keywords = {Chromosome mapping, database management systems, Databases, Genetic, documentation, Gene Expression Profiling, Gene Expression Regulation, Genomics, Information Storage and Retrieval, Microbiological Techniques, natural language processing, Prokaryotic Cells, Proteome, signal transduction, software, User-Computer Interface, Vocabulary, Controlled}, author = {Haft, Daniel H. and J. Selengut and Brinkac, Lauren M. and Zafar, Nikhat and White, Owen} }