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Systematic analysis of genome-wide fitness data in yeast reveals novel gene function and drug action |
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| Authors: | Maureen E Hillenmeyer Elke Ericson Ronald W Davis Corey Nislow Daphne Koller Guri Giaever |
| Affiliation: | (1) Biomedical Informatics, Stanford University, 251 Campus Drive, MSOB, x-215, Stanford, CA 94305, USA;(2) Stanford Genome Technology Center, 855 California Avenue, Palo Alto, CA 94304, USA;(3) Department of Pharmaceutical Sciences, Univerity of Toronto, 144 College Street, Toronto, Ontario, M5S3M2, Canada;(4) Department of Molecular Genetics, University of Toronto, 1 King's College Circle, Toronto, Ontario, M5S1A8, Canada;(5) Department of Biochemistry, Stanford University, Beckman Center B400, 279 W. Campus Drive, Stanford, CA 94305, USA;(6) Banting and Best Department of Medical Research, University of Toronto, 112 College Street, Toronto, Ontario, MSG1L6, Canada;(7) Department of Computer Science, Stanford University, 353 Serra Mall, Stanford, CA 94305, USA |
| 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. |
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