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Updated: Jul 3, 2026
Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae
Published on: April 5, 2015
Combining guilt-by-association and guilt-by-profiling to predict Saccharomyces cerevisiae gene function
Weidong Tian1, Lan V Zhang, Murat Taşan
1Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Longwood Avenue, Boston, Massachusetts 02115, USA.
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.
