Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
2008-12-16
pubmed:abstractText
Function prediction by sequence-similarity based methods identifies only approximately 50% of the proteins deduced from newly sequenced genomes. We have developed an approach to annotate the 'leftover proteins' i.e., those which cannot be assigned function using sequence similarity. Our method (MOPS) is pan-taxonomic, predicting fine-grained molecular function (rather than a broad functional category) with high performance. In addition, we developed a validation scheme that assesses predictions using domain-specific knowledge.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0929-8665
pubmed:author
pubmed:issnType
Print
pubmed:volume
15
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1107-16
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Function prediction of hypothetical proteins without sequence similarity to proteins of known function.
pubmed:affiliation
Center Robert Cedergren for Bioinformatics and Genomics, Département de Biochimie, Université de Montréal, 2900 Edouard-Montpetit, Montréal, Québec, H3T 1J4, Canada. sivakumar.kannan@umontreal.ca
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't