| Literature DB >> 28917822 |
Peter S Kutchukian1, Charlie Chang2, Sean J Fox3, Erica Cook4, Richard Barnard5, David Tellers6, Huijun Wang7, Dante Pertusi8, Meir Glick9, Robert P Sheridan10, Iain M Wallace11, Anne Mai Wassermann12.
Abstract
Increasing amounts of biological data are accumulating in the pharmaceutical industry and academic institutions. However, data does not equal actionable information, and guidelines for appropriate data capture, harmonization, integration, mining, and visualization need to be established to fully harness its potential. Here, we describe ongoing efforts at Merck & Co. to structure data in the area of chemogenomics. We are integrating complementary data from both internal and external data sources into one chemogenomics database (Chemical Genetic Interaction Enterprise; CHEMGENIE). Here, we demonstrate how this well-curated database facilitates compound set design, tool compound selection, target deconvolution in phenotypic screening, and predictive model building.Entities:
Mesh:
Year: 2017 PMID: 28917822 DOI: 10.1016/j.drudis.2017.09.004
Source DB: PubMed Journal: Drug Discov Today ISSN: 1359-6446 Impact factor: 7.851