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


CONCLUSIONS
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.
Tian
Weidong
W
Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Longwood Avenue, Boston, Massachusetts 02115, USA.
Zhang
Lan V
LV
Taşan
Murat
M
Gibbons
Francis D
FD
King
Oliver D
OD
Park
Julie
J
Wunderlich
Zeba
Z
Cherry
J Michael
JM
Roth
Frederick P
FP
D000465:Algorithms; D019295:Computational Biology; D005800:Genes, Fungal; D053858:Metabolic Networks and Pathways; D012441:Saccharomyces cerevisiae / Q000235:genetics* / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics* / Q000378:metabolism; D012984:Software
D029701:Saccharomyces cerevisiae Proteins