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| Content Provider | PubMed Central |
|---|---|
| Author | Baryshnikova, Anastasia Costanzo, Michael Kim, Yungil Ding, Huiming Koh, Judice Toufighi, Kiana Youn, Ji-young Ou, Jiongwen Luis, Bryan-joseph San Bandyopadhyay, Sunayan Hibbs, Matthew Hess, David Gingras, Anne-claude Bader, Gary D. Troyanskaya, Olga G. Brown, Grant W. Andrews, Brenda Boone, Charles Myers, Chad L. |
| Copyright Year | 2010 |
| Abstract | Global quantitative analysis of genetic interactions is a powerful approach for deciphering the roles of genes and mapping functional relationships among pathways. Using colony size as a proxy for fitness, we developed a method for measuring fitness-based genetic interactions from high-density arrays of yeast double mutants generated by synthetic genetic array (SGA) analysis. We identified several experimental sources of systematic variation and developed normalization strategies to obtain accurate single- and double-mutant fitness measurements, which rival the accuracy of other high-resolution studies. We applied the SGA score to examine the relationship between physical and genetic interaction networks, and we found that positive genetic interactions connect across functionally distinct protein complexes revealing a network of genetic suppression among loss-of-function alleles. |
| Related Links | http://dx.doi.org/10.1038/nmeth.1534 |
| Ending Page | 1024 |
| Page Count | 8 |
| Starting Page | 1017 |
| File Format | |
| ISSN | 15487091 |
| e-ISSN | 15487105 |
| Journal | Nature methods |
| Issue Number | 12 |
| Volume Number | 7 |
| Language | English |
| Publisher Date | 2010-11-01 |
| Access Restriction | Open |
| Subject Keyword | Biotechnology Cell Biology Biochemistry Molecular Biology Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Cell Biology Biochemistry Molecular Biology Biotechnology |
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