SIMAP-A comprehensive database of pre-calculated protein sequence similarities, domains, annotations and clusters

Thomas Rattei, Patrick Tischler, Stefan Götz, Marc André Jehl, Jonathan Hoser, Roland Arnold, Ana Conesa, Hans Werner Mewes

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

The prediction of protein function as well as the reconstruction of evolutionary genesis employing sequence comparison at large is still the most powerful tool in sequence analysis. Due to the exponential growth of the number of known protein sequences and the subsequent quadratic growth of the similarity matrix, the computation of the Similarity Matrix of Proteins (SIMAP) becomes a computational intensive task. The SIMAP database provides a comprehensive and up-to-date precalculation of the protein sequence similarity matrix, sequence-based features and sequence clusters. As of September 2009, SIMAP covers 48 million proteins and more than 23 million non-redundant sequences. Novel features of SIMAP include the expansion of the sequence space by including databases such as ENSEMBL as well as the integration of metagenomes based on their consistent processing and annotation. Furthermore, protein function predictions by Blast2GO are precalculated for all sequences in SIMAP and the data access and query functions have been improved. SIMAP assists biologists to query the up-to-date sequence space systematically and facilitates large-scale downstream projects in computational biology. Access to SIMAP is freely provided through the web portal for individuals (http://mips.gsf.de/simap/) and for programmatic access through DAS (http://webclu.bio.wzw.tum.de/das/) and Web-Service (http://mips.gsf.de/webservices/services/SimapService2.0?wsdl).

Original languageEnglish
Article numbergkp949
Pages (from-to)D223-D226
JournalNucleic Acids Research
Volume38
Issue numberSUPPL.1
DOIs
StatePublished - 10 Nov 2009

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