This article is part of the supplement: Selected articles from the Eleventh Asia Pacific Bioinformatics Conference (APBC 2013): Genomics
FitSearch: a robust way to interpret a yeast fitness profile in terms of drug's mode-of-action
- Equal contributors
1 Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-Gu, Daejeon, 305-701, Republic of Korea
2 Bioinformatics Lab, Healthcare group, SK telecom, 9-1, Sunae-dong, Pundang-gu, Sungnam-si, Kyunggi-do, 463-784, Republic of Korea
3 Department of Biological Science, Seoul National University, 599 Gwanakro, Gwanak-gu, Seoul, 151-747, Republic of Korea
4 Department of Applied Biology, Gyeongsang National University, 501 Jinju-daero, Jinju, Gyeongnam, 660-701, Republic of Korea
5 USDA-ARS, Root Disease and Biological Control Research Unit, 367 Johnson Hall, Washington State University, Pullman, Washington 99164-6430, USA
Citation and License
BMC Genomics 2013, 14(Suppl 1):S6 doi:10.1186/1471-2164-14-S1-S6Published: 21 January 2013
Yeast deletion-mutant collections have been successfully used to infer the mode-of-action of drugs especially by profiling chemical-genetic and genetic-genetic interactions on a genome-wide scale. Although tens of thousands of those profiles are publicly available, a lack of an accurate method for mining such data has been a major bottleneck for more widespread use of these useful resources.
For general usage of those public resources, we designed FitRankDB as a general repository of fitness profiles, and developed a new search algorithm, FitSearch, for identifying the profiles that have a high similarity score with statistical significance for a given fitness profile. We demonstrated that our new repository and algorithm are highly beneficial to researchers who attempting to make hypotheses based on unknown modes-of-action of bioactive compounds, regardless of the types of experiments that have been performed using yeast deletion-mutant collection in various types of different measurement platforms, especially non-chip-based platforms.
We showed that our new database and algorithm are useful when attempting to construct a hypothesis regarding the unknown function of a bioactive compound through small-scale experiments with a yeast deletion collection in a platform independent manner. The FitRankDB and FitSearch enhance the ease of searching public yeast fitness profiles and obtaining insights into unknown mechanisms of action of drugs. FitSearch is freely available at http://fitsearch.kaist.ac.kr webcite.