Modeling and Informatics, Merck & Co., Inc., Boston, MA, USA.
Scientific Modeling Platforms, Merck & Co., Inc., Boston, MA, USA.
Drug Discov Today. 2018 Jan;23(1):151-160. doi: 10.1016/j.drudis.2017.09.004. Epub 2017 Sep 14.
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.
越来越多的生物数据正在医药行业和学术机构中积累。然而，数据并不等同于可操作的信息，需要建立适当的数据捕获、协调、集成、挖掘和可视化指南，以充分发挥其潜力。在这里，我们描述了默克公司在化学生物组学领域组织数据的正在进行的努力。我们正在将内部和外部数据源的补充数据整合到一个化学生物组学数据库（化学遗传相互作用企业；CHEMGENIE）中。在这里，我们展示了这个精心管理的数据库如何促进化合物集设计、工具化合物选择、表型筛选中的靶标分解以及预测模型构建。
