PMID:18613951

Tian, W, Zhang, LV, Taşan, M, Gibbons, FD, King, OD, Park, J, Wunderlich, Z, Cherry, JM and Roth, FP (2008) Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function.Genome Biol. 9 Suppl 1:S7

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.

Links

PubMed Online version:10.1186/gb-2008-9-s1-s7

Significance

Annotations

Gene product	Qualifier	GO ID	GO term name	Evidence Code	with/from	Aspect	Notes	Status
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See also

References

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