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Systematic analysis of genome-wide fitness data in yeast reveals novel gene function and drug action

Maureen E Hillenmeyer12, Elke Ericson34, Ronald W Davis25, Corey Nislow46, Daphne Koller7* and Guri Giaever34*

Author Affiliations

1 Biomedical Informatics, 251 Campus Drive, MSOB, x-215, Stanford University, Stanford, CA 94305, USA

2 Stanford Genome Technology Center, 855 California Avenue, Palo Alto, CA 94304, USA

3 Department of Pharmaceutical Sciences, 144 College Street, University of Toronto, Toronto, Ontario, M5S3M2, Canada

4 Department of Molecular Genetics, 1 King's College Circle, University of Toronto, Toronto, Ontario M5S1A8, Canada

5 Department of Biochemistry, Beckman Center B400, 279 W. Campus Drive, Stanford University, Stanford, CA 94305, USA

6 Banting and Best Department of Medical Research, 112 College Street, University of Toronto, Toronto, Ontario MSG1L6, Canada

7 Department of Computer Science, 353 Serra Mall, Stanford University, Stanford, CA 94305, USA

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Genome Biology 2010, 11:R30  doi:10.1186/gb-2010-11-3-r30

Published: 12 March 2010

Abstract

We systematically analyzed the relationships between gene fitness profiles (co-fitness) and drug inhibition profiles (co-inhibition) from several hundred chemogenomic screens in yeast. Co-fitness predicted gene functions distinct from those derived from other assays and identified conditionally dependent protein complexes. Co-inhibitory compounds were weakly correlated by structure and therapeutic class. We developed an algorithm predicting protein targets of chemical compounds and verified its accuracy with experimental testing. Fitness data provide a novel, systems-level perspective on the cell.