BioinformaticsBioinformaticsPeer-reviewed journal article
MOSAIC: a chemical-genetic interaction data repository and web resource for exploring chemical modes of action
Justin NelsoniD, Scott W. SimpkinsiD, Hamid SafizadehiD, Sheena Claire LiiD, Jeff S. PiotrowskiiD, Hiroyuki HiranoiD, Yoko YashirodaiD, Hiroyuki OsadaiD, Minoru YoshidaiD, Charles M. BooneiD, Chad L. MyersiD
Abstract
SummaryChemical-genomic approaches that map interactions between small molecules and genetic perturbations offer a promising strategy for functional annotation of uncharacterized bioactive compounds. We recently developed a new high-throughput platform for mapping chemical-genetic (CG) interactions in yeast that can be scaled to screen large compound collections, and we applied this system to generate CG interaction profiles for more than 13,000 compounds. When integrated with the existing global yeast genetic interaction network, CG interaction profiles can enable mode-of-action prediction for previously uncharacterized compounds as well as discover unexpected secondary effects for known drugs. To facilitate future analysis of these valuable data, we developed a public database and web interface named MOSAIC. The website provides a convenient interface for querying compounds, bioprocesses (GO terms), and genes for CG information including direct CG interactions, bioprocesses, and gene-level target predictions. MOSAIC also provides access to chemical structure information of screened molecules, chemical-genomic profiles, and the ability to search for compounds sharing structural and functional similarity. This resource will be of interest to chemical biologists for discovering new small molecule probes with specific modes-of-action as well as computational biologists interested in analyzing CG interaction networks.\n\nAvailabilityMOSAIC is available at http://mosaic.cs.umn.edu.\n\nContactchadm@umn.edu, charlie.boone@utoronto.ca, yoshidam@riken.jp, or hisyo@riken.jp
- organism: yeast
- research focus: database / resource
- research focus: benchmarking
- approach: experimental assay
- Citations
- 17
- FWCI
- 2.05
- Field percentile
- top 12%
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