| pubmed-article:15550167 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:15550167 | lifeskim:mentions | umls-concept:C0025663 | lld:lifeskim |
| pubmed-article:15550167 | lifeskim:mentions | umls-concept:C0017428 | lld:lifeskim |
| pubmed-article:15550167 | lifeskim:mentions | umls-concept:C0681842 | lld:lifeskim |
| pubmed-article:15550167 | lifeskim:mentions | umls-concept:C1516048 | lld:lifeskim |
| pubmed-article:15550167 | lifeskim:mentions | umls-concept:C0205453 | lld:lifeskim |
| pubmed-article:15550167 | lifeskim:mentions | umls-concept:C1706814 | lld:lifeskim |
| pubmed-article:15550167 | lifeskim:mentions | umls-concept:C1527118 | lld:lifeskim |
| pubmed-article:15550167 | pubmed:dateCreated | 2004-12-16 | lld:pubmed |
| pubmed-article:15550167 | pubmed:abstractText | The function of a novel gene product is typically predicted by transitive assignment of annotation from similar sequences. We describe a novel method, GOtcha, for predicting gene product function by annotation with Gene Ontology (GO) terms. GOtcha predicts GO term associations with term-specific probability (P-score) measures of confidence. Term-specific probabilities are a novel feature of GOtcha and allow the identification of conflicts or uncertainty in annotation. | lld:pubmed |
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| pubmed-article:15550167 | pubmed:language | eng | lld:pubmed |
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| pubmed-article:15550167 | pubmed:citationSubset | IM | lld:pubmed |
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| pubmed-article:15550167 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:15550167 | pubmed:month | Nov | lld:pubmed |
| pubmed-article:15550167 | pubmed:issn | 1471-2105 | lld:pubmed |
| pubmed-article:15550167 | pubmed:author | pubmed-author:BerrimanMatth... | lld:pubmed |
| pubmed-article:15550167 | pubmed:author | pubmed-author:MartinDavid... | lld:pubmed |
| pubmed-article:15550167 | pubmed:author | pubmed-author:BartonGeoffre... | lld:pubmed |
| pubmed-article:15550167 | pubmed:issnType | Electronic | lld:pubmed |
| pubmed-article:15550167 | pubmed:day | 18 | lld:pubmed |
| pubmed-article:15550167 | pubmed:volume | 5 | lld:pubmed |
| pubmed-article:15550167 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:15550167 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:15550167 | pubmed:pagination | 178 | lld:pubmed |
| pubmed-article:15550167 | pubmed:dateRevised | 2009-11-18 | lld:pubmed |
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| pubmed-article:15550167 | pubmed:year | 2004 | lld:pubmed |
| pubmed-article:15550167 | pubmed:articleTitle | GOtcha: a new method for prediction of protein function assessed by the annotation of seven genomes. | lld:pubmed |
| pubmed-article:15550167 | pubmed:affiliation | Post-Genomics and Molecular Interactions Centre, School of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk | lld:pubmed |
| pubmed-article:15550167 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:15550167 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
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