@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 {38529, title = {TIGRFAMs and Genome Properties in 2013}, journal = {Nucleic acids researchNucleic Acids Research}, volume = {41}, year = {2013}, note = {http://www.ncbi.nlm.nih.gov/pubmed/23197656?dopt=Abstract}, type = {10.1093/nar/gks1234}, abstract = {TIGRFAMs, available online at http://www.jcvi.org/tigrfams is a database of protein family definitions. Each entry features a seed alignment of trusted representative sequences, a hidden Markov model (HMM) built from that alignment, cutoff scores that let automated annotation pipelines decide which proteins are members, and annotations for transfer onto member proteins. Most TIGRFAMs models are designated equivalog, meaning they assign a specific name to proteins conserved in function from a common ancestral sequence. Models describing more functionally heterogeneous families are designated subfamily or domain, and assign less specific but more widely applicable annotations. The Genome Properties database, available at http://www.jcvi.org/genome-properties, specifies how computed evidence, including TIGRFAMs HMM results, should be used to judge whether an enzymatic pathway, a protein complex or another type of molecular subsystem is encoded in a genome. TIGRFAMs and Genome Properties content are developed in concert because subsystems reconstruction for large numbers of genomes guides selection of seed alignment sequences and cutoff values during protein family construction. Both databases specialize heavily in bacterial and archaeal subsystems. At present, 4284 models appear in TIGRFAMs, while 628 systems are described by Genome Properties. Content derives both from subsystem discovery work and from biocuration of the scientific literature.}, keywords = {Databases, Protein, Genome, Archaeal, Genome, Bacterial, Genomics, Internet, Markov chains, Molecular Sequence Annotation, Proteins, sequence alignment}, author = {Haft, Daniel H. and J. Selengut and Richter, Roland A. and Harkins, Derek and Basu, Malay K. and Beck, Erin} } @article {49764, title = {TIGRFAMs and Genome Properties in 2013.}, journal = {Nucleic Acids Res}, volume = {41}, year = {2013}, month = {2013 Jan}, pages = {D387-95}, abstract = {

TIGRFAMs, available online at http://www.jcvi.org/tigrfams is a database of protein family definitions. Each entry features a seed alignment of trusted representative sequences, a hidden Markov model (HMM) built from that alignment, cutoff scores that let automated annotation pipelines decide which proteins are members, and annotations for transfer onto member proteins. Most TIGRFAMs models are designated equivalog, meaning they assign a specific name to proteins conserved in function from a common ancestral sequence. Models describing more functionally heterogeneous families are designated subfamily or domain, and assign less specific but more widely applicable annotations. The Genome Properties database, available at http://www.jcvi.org/genome-properties, specifies how computed evidence, including TIGRFAMs HMM results, should be used to judge whether an enzymatic pathway, a protein complex or another type of molecular subsystem is encoded in a genome. TIGRFAMs and Genome Properties content are developed in concert because subsystems reconstruction for large numbers of genomes guides selection of seed alignment sequences and cutoff values during protein family construction. Both databases specialize heavily in bacterial and archaeal subsystems. At present, 4284 models appear in TIGRFAMs, while 628 systems are described by Genome Properties. Content derives both from subsystem discovery work and from biocuration of the scientific literature.

}, keywords = {Databases, Protein, Genome, Archaeal, Genome, Bacterial, Genomics, Internet, Markov chains, Molecular Sequence Annotation, Proteins, sequence alignment}, issn = {1362-4962}, doi = {10.1093/nar/gks1234}, author = {Haft, Daniel H and Selengut, Jeremy D and Richter, Roland A and Harkins, Derek and Basu, Malay K and Beck, Erin} } @proceedings {38176, title = {Computing the Tree of Life: Leveraging the Power of Desktop and Service Grids}, year = {2011}, month = {2011}, type = {10.1109/IPDPS.2011.344}, abstract = {The trend in life sciences research, particularly in molecular evolutionary systematics, is toward larger data sets and ever-more detailed evolutionary models, which can generate substantial computational loads. Over the past several years we have developed a grid computing system aimed at providing researchers the computational power needed to complete such analyses in a timely manner. Our grid system, known as The Lattice Project, was the first to combine two models of grid computing - the service model, which mainly federates large institutional HPC resources, and the desktop model, which harnesses the power of PCs volunteered by the general public. Recently we have developed a "science portal" style web interface that makes it easier than ever for phylogenetic analyses to be completed using GARLI, a popular program that uses a maximum likelihood method to infer the evolutionary history of organisms on the basis of genetic sequence data. This paper describes our approach to scheduling thousands of GARLI jobs with diverse requirements to heterogeneous grid resources, which include volunteer computers running BOINC software. A key component of this system provides a priori GARLI runtime estimates using machine learning with random forests.}, keywords = {(artificial, (mathematics), analysis, BOINC, COMPUTATION, computational, computing, data, Estimation, evolutionary, GARLI, genetic, Grid, GRIDS, handling, heterogeneous, History, HPC, information, intelligence), interface, interfaces, Internet, jobs, lattice, learning, life, likelihood, load, machine, maximum, method, model, molecular, phylogenetic, portal, Portals, power, project, resource, Science, sequence, service, services, sets, software, substantial, system, systematics, tree, TREES, user, Web}, author = {Adam L. Bazinet and Michael P. Cummings} } @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} }