Thu, 21 Aug 2008 13:56:49 BST CiteULike: neils's user-computer http://www.citeulike.org/user/neils/tag/user-computer CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/neils/article/2054457 <i>Bioinformatics, Vol. 21, No. 20. (Oct 2005), pp. 3940-3941.</i><br /><br />SUMMARY: ROCR is a package for evaluating and visualizing the performance of scoring classifiers in the statistical language R. It features over 25 performance measures that can be freely combined to create two-dimensional performance curves. Standard methods for investigating trade-offs between specific performance measures are available within a uniform framework, including receiver operating characteristic (ROC) graphs, precision/recall plots, lift charts and cost curves. ROCR integrates tightly with R's powerful graphics capabilities, thus allowing for highly adjustable plots. Being equipped with only three commands and reasonable default values for optional parameters, ROCR combines flexibility with ease of usage. AVAILABILITY: http://rocr.bioinf.mpi-sb.mpg.de. ROCR can be used under the terms of the GNU General Public License. Running within R, it is platform-independent. CONTACT: tobias.sing@mpi-sb.mpg.de. ROCR: visualizing classifier performance in R. Tobias Sing Oliver Sander Niko Beerenwinkel Thomas Lengauer Bioinformatics, Vol. 21, No. 20. (Oct 2005), pp. 3940-3941. 2007-12-04T03:22:10-00:00 2005 Bioinformatics 21 20 3940 3941 article-nar article-predikin automated computer curve data graphics interface interpretation languages pattern programming recognition roc software statistics user-computer validation http://www.citeulike.org/user/neils/article/2054443 <i>Nucleic Acids Res, Vol. 34, No. Database issue. (Jan 2006), pp. D257-D260.</i><br /><br />The Simple Modular Architecture Research Tool (SMART) is an online resource (http://smart.embl.de/) used for protein domain identification and the analysis of protein domain architectures. Many new features were implemented to make SMART more accessible to scientists from different fields. The new 'Genomic' mode in SMART makes it easy to analyze domain architectures in completely sequenced genomes. Domain annotation has been updated with a detailed taxonomic breakdown and a prediction of the catalytic activity for 50 SMART domains is now available, based on the presence of essential amino acids. Furthermore, intrinsically disordered protein regions can be identified and displayed. The network context is now displayed in the results page for more than 350 000 proteins, enabling easy analyses of domain interactions. SMART 5: domains in the context of genomes and networks. Ivica Letunic Richard Copley Birgit Pils Stefan Pinkert Jörg Schultz Peer Bork Nucleic Acids Res, Vol. 34, No. Database issue. (Jan 2006), pp. D257-D260. 2007-12-04T03:22:10-00:00 2006 Nucleic Acids Res 34 Database issue D257 D260 alignment analysis article-nar article-pka-pkg article-predikin biological catalysis catalytic complex database domain genomics interface internet models multiprotein protein sequence structure tertiary user-computer http://www.citeulike.org/user/neils/article/2054424 <i>Nucleic Acids Res, Vol. 34, No. Database issue. (Jan 2006), pp. D247-D251.</i><br /><br />Pfam is a database of protein families that currently contains 7973 entries (release 18.0). A recent development in Pfam has enabled the grouping of related families into clans. Pfam clans are described in detail, together with the new associated web pages. Improvements to the range of Pfam web tools and the first set of Pfam web services that allow programmatic access to the database and associated tools are also presented. Pfam is available on the web in the UK (http://www.sanger.ac.uk/Software/Pfam/), the USA (http://pfam.wustl.edu/), France (http://pfam.jouy.inra.fr/) and Sweden (http://pfam.cgb.ki.se/). Pfam: clans, web tools and services. Robert Finn Jaina Mistry Benjamin Böckler Sam Jones Volker Hollich Timo Lassmann Simon Moxon Mhairi Marshall Ajay Khanna Richard Durbin Sean Eddy Erik Sonnhammer Alex Bateman Nucleic Acids Res, Vol. 34, No. Database issue. (Jan 2006), pp. D247-D251. 2007-12-04T03:22:09-00:00 2006 Nucleic Acids Res 34 Database issue D247 D251 alignment article-predikin chain computer database graphics interface internet markov protein sequence software structure tertiary user-computer http://www.citeulike.org/user/neils/article/2054418 <i>Nucleic Acids Res, Vol. 34, No. Web Server issue. (Jul 2006), pp. W362-W365.</i><br /><br />ScanProsite--http://www.expasy.org/tools/scanprosite/--is a new and improved version of the web-based tool for detecting PROSITE signature matches in protein sequences. For a number of PROSITE profiles, the tool now makes use of ProRules--context-dependent annotation templates--to detect functional and structural intra-domain residues. The detection of those features enhances the power of function prediction based on profiles. Both user-defined sequences and sequences from the UniProt Knowledgebase can be matched against custom patterns, or against PROSITE signatures. To improve response times, matches of sequences from UniProtKB against PROSITE signatures are now retrieved from a pre-computed match database. Several output modes are available including simple text views and a rich mode providing an interactive match and feature viewer with a graphical representation of results. ScanProsite: detection of PROSITE signature matches and ProRule-associated functional and structural residues in proteins. Edouard de Castro Christian Sigrist Alexandre Gattiker Virginie Bulliard Petra Elisabeth Gasteiger Amos Bairoch Nicolas Hulo Nucleic Acids Res, Vol. 34, No. Web Server issue. (Jul 2006), pp. W362-W365. 2007-12-04T03:22:09-00:00 2006 Nucleic Acids Res 34 Web Server issue W362 W365 amino-acid analysis article-predikin database homology interface internet protein sequence software structure tertiary user-computer http://www.citeulike.org/user/neils/article/2053696 <i>Nucleic Acids Res, Vol. 33, No. Database issue. (Jan 2005), pp. D284-D288.</i><br /><br />PANTHER is a large collection of protein families that have been subdivided into functionally related subfamilies, using human expertise. These subfamilies model the divergence of specific functions within protein families, allowing more accurate association with function (ontology terms and pathways), as well as inference of amino acids important for functional specificity. Hidden Markov models (HMMs) are built for each family and subfamily for classifying additional protein sequences. The latest version, 5.0, contains 6683 protein families, divided into 31,705 subfamilies, covering approximately 90% of mammalian protein-coding genes. PANTHER 5.0 includes a number of significant improvements over previous versions, most notably (i) representation of pathways (primarily signaling pathways) and association with subfamilies and individual protein sequences; (ii) an improved methodology for defining the PANTHER families and subfamilies, and for building the HMMs; (iii) resources for scoring sequences against PANTHER HMMs both over the web and locally; and (iv) a number of new web resources to facilitate analysis of large gene lists, including data generated from high-throughput expression experiments. Efforts are underway to add PANTHER to the InterPro suite of databases, and to make PANTHER consistent with the PIRSF database. PANTHER is now publicly available without restriction at http://panther.appliedbiosystems.com. The PANTHER database of protein families, subfamilies, functions and pathways. Huaiyu Mi Betty Ulitsky Rozina Loo Anish Kejariwal Jody Vandergriff Steven Rabkin Nan Guo Anushya Muruganujan Olivier Doremieux Michael Campbell Hiroaki Kitano Paul Thomas Nucleic Acids Res, Vol. 33, No. Database issue. (Jan 2005), pp. D284-D288. 2007-12-04T01:53:36-00:00 2005 Nucleic Acids Res 33 Database issue D284 D288 article-nar article-pka-pkg database interface panther user-computer http://www.citeulike.org/user/neils/article/2053695 <i>Nucleic Acids Res, Vol. 35, No. Database issue. (Jan 2007), pp. D599-D603.</i><br /><br />Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web-accessible, public resource 'AgBase' (www.agbase.msstate.edu). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteogenomic mapping. Proteogenomic data are available from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The 'GO Consortium' gene association file contains the most rigorous GO annotations based solely on experimental data. The 'Community' gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted annotations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely available on request. A suite of tools for analyzing functional genomics datasets using the GO is available online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations. AgBase: a unified resource for functional analysis in agriculture. Fiona Mccarthy Susan Bridges Nan Wang Bryce Magee Paul Williams Dawn Luthe Shane Burgess Nucleic Acids Res, Vol. 35, No. Database issue. (Jan 2007), pp. D599-D603. 2007-12-04T01:53:36-00:00 2007 Nucleic Acids Res 35 Database issue D599 D603 agriculture animal article-pka-pkg crops database domestic genetics genomics integration interface internet protein proteomics system user-computer http://www.citeulike.org/user/neils/article/2053690 <i>Nucleic Acids Res, Vol. 34, No. Database issue. (Jan 2006), pp. D322-D326.</i><br /><br />The Gene Ontology (GO) project (http://www.geneontology.org) develops and uses a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://song.sourceforge.net/). The GO Consortium continues to improve to the vocabulary content, reflecting the impact of several novel mechanisms of incorporating community input. A growing number of model organism databases and genome annotation groups contribute annotation sets using GO terms to GO's public repository. Updates to the AmiGO browser have improved access to contributed genome annotations. As the GO project continues to grow, the use of the GO vocabularies is becoming more varied as well as more widespread. The GO project provides an ontological annotation system that enables biologists to infer knowledge from large amounts of data. The Gene Ontology (GO) project in 2006. gene Consortium Nucleic Acids Res, Vol. 34, No. Database issue. (Jan 2006), pp. D322-D326. 2007-12-04T01:53:36-00:00 2006 Nucleic Acids Res 34 Database issue D322 D326 analysis article-pka-pkg control controlled database expression gene genetics interface internet management quality sequence software system user-computer vocabulary