Open AccessThe SBASE domain sequence resource, release 12: prediction of protein domain-architecture using support vector machines
Author(s) -
Kristian Vlahoviček
Publication year - 2004
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gki112
Subject(s) - similarity (geometry) , biology , domain (mathematical analysis) , sequence (biology) , support vector machine , computational biology , protein domain , function (biology) , protein sequencing , sequence alignment , structural similarity , architecture domain , resource (disambiguation) , data mining , pattern recognition (psychology) , peptide sequence , artificial intelligence , computer science , genetics , gene , mathematics , software , mathematical analysis , biochemistry , image (mathematics) , computer network , software architecture , enterprise architecture framework , programming language
SBASE (http://www.icgeb.trieste.it/sbase) is an online resource designed to facilitate the detection of domain homologies based on sequence database search. The present release of the SBASE A library of protein domain sequences contains 972,397 protein sequence segments annotated by structure, function, ligand-binding or cellular topology, clustered into 8547 domain groups. SBASE B contains 169,916 domain sequences clustered into 2526 less well-characterized groups. Domain prediction is based on an evaluation of database search results in comparison with a 'similarity network' of inter-sequence similarity scores, using support vector machines trained on similarity search results of known domains.
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