Mickael Goujon

TL;DR: The mission of the Universal Protein Resource (UniProt) is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequences and functional annotation.

TL;DR: A new framework aimed at both novice as well as expert users that exposes novel methods of obtaining annotations and visualizing sequence analysis results through one uniform and consistent interface is presented.

TL;DR: The EB-eye can be accessed over the web or programmatically using a SOAP Web Services interface and its search and retrieval capabilities can be exploited in workflows and analytical pipe-lines.

Abstract: Summary: Iterative similarity searches with PSI-BLAST position-specific score matrices (PSSMs) find many more homologs than single searches, but PSSMs can be contaminated when homologous alignments are extended into unrelated protein domains—homologous over-extension (HOE). PSI-Search combines an optimal Smith–Waterman local alignment sequence search, using SSEARCH, with the PSI-BLAST profile construction strategy. An optional sequence boundary-masking procedure, which prevents alignments from being extended after they are initially included, can reduce HOE errors in the PSSM profile. Preventing HOE improves selectivity for both PSI-BLAST and PSI-Search, but PSI-Search has ~4-fold better selectivity than PSI-BLAST and similar sensitivity at 50% and 60% family coverage. PSI-Search is also produces 2-for 4-fold fewer false-positives than JackHMMER, but is ~5% less sensitive. Availability and implementation: PSI-Search is available from the authors as a standalone implementation written in Perl for Linux-compatible platforms. It is also available through a web interface ( www.ebi.ac.uk/Tools/sss/psisearch) and SOAP and REST Web Services (www.ebi.ac.uk/Tools/webservices). Contact:pearson@virginia.edu; rodrigo.lopez@ebi.ac.uk

TL;DR: An enzyme portal is developed to provide this wealth of information on enzymes from multiple in-house resources addressing particular data classes: protein sequence and structure, reactions, pathways and small molecules.