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Genome Biol. 2008;9 Suppl 1:S7. doi: 10.1186/gb-2008-9-s1-s7. Epub 2008 Jun 27.

Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function.

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  • 1Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Longwood Avenue, Boston, Massachusetts 02115, USA.

Abstract

BACKGROUND:

Learning the function of genes is a major goal of computational genomics. Methods for inferring gene function have typically fallen into two categories: 'guilt-by-profiling', which exploits correlation between function and other gene characteristics; and 'guilt-by-association', which transfers function from one gene to another via biological relationships.

RESULTS:

We have developed a strategy ('Funckenstein') that performs guilt-by-profiling and guilt-by-association and combines the results. Using a benchmark set of functional categories and input data for protein-coding genes in Saccharomyces cerevisiae, Funckenstein was compared with a previous combined strategy. Subsequently, we applied Funckenstein to 2,455 Gene Ontology terms. In the process, we developed 2,455 guilt-by-profiling classifiers based on 8,848 gene characteristics and 12 functional linkage graphs based on 23 biological relationships.

CONCLUSION:

Funckenstein outperforms a previous combined strategy using a common benchmark dataset. The combination of 'guilt-by-profiling' and 'guilt-by-association' gave significant improvement over the component classifiers, showing the greatest synergy for the most specific functions. Performance was evaluated by cross-validation and by literature examination of the top-scoring novel predictions. These quantitative predictions should help prioritize experimental study of yeast gene functions.

PMID:
18613951
[PubMed - indexed for MEDLINE]
PMCID:
PMC2447541
Free PMC Article

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