Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function.
Genome Biol
; 9 Suppl 1: S7, 2008.
Article
em En
| MEDLINE
| ID: mdl-18613951
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.
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Saccharomyces cerevisiae
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Algoritmos
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Proteínas de Saccharomyces cerevisiae
Idioma:
En
Ano de publicação:
2008
Tipo de documento:
Article