Linked Life Data

11932249

Source:http://linkedlifedata.com/resource/pubmed/id/11932249

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2002-4-4
pubmed:abstractText
A heuristic algorithm for associating Gene Ontology (GO) defined molecular functions to protein domains as listed in the ProDom and CDD databases is described. The algorithm generates rules for function-domain associations based on the intersection of functions assigned to gene products by the GO consortium that contain ProDom and/or CDD domains at varying levels of sequence similarity. The hierarchical nature of GO molecular functions is incorporated into rule generation. Manual review of a subset of the rules generated indicates an accuracy rate of 87% for ProDom rules and 84% for CDD rules. The utility of these associations is that novel sequences can be assigned a putative function if sufficient similarity exists to a ProDom or CDD domain for which one or more GO functions has been associated. Although functional assignments are increasingly being made for gene products from model organisms, it is likely that the needs of investigators will continue to outpace the efforts of curators, particularly for nonmodel organisms. A comparison with other methods in terms of coverage and agreement was performed, indicating the utility of the approach. The domain-function associations and function assignments are available from our website http://www.cbil.upenn.edu/GO.
pubmed:grant
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-10222410, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-10322433, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-10592233, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-10592234, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-10592242, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-10704826, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-10731133, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-11119305, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-11125043, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-11217851, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-11483584, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-11591640, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-8188249, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-9254694, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-9847184, http://linkedlifedata.com/resource/pubmed/commentcorrection/11932249-9847197
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1088-9051
pubmed:author
pubmed:issnType
Print
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
648-55
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Predicting gene ontology functions from ProDom and CDD protein domains.
pubmed:affiliation
Center for Bioinformatics, Computational Biology and Informatics Laboratory, University of Pennsylvania, Philadelphia, PA 19104, USA. jschug@pcbi.upenn.edu
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S.