Mining Chemical Activity Status from High-Throughput Screening Assays.

ABSTRACT: High-throughput screening (HTS) experiments provide a valuable resource that reports biological activity of numerous chemical compounds relative to their molecular targets. Building computational models that accurately predict such activity status (active vs. inactive) in specific assays is a challenging task given the large volume of data and frequently small proportion of active compounds relative to the inactive ones. We developed a method, DRAMOTE, to predict activity status of chemical compounds in HTP activity assays. For a class of HTP assays, our method achieves considerably better results than the current state-of-the-art-solutions. We achieved this by modification of a minority oversampling technique. To demonstrate that DRAMOTE is performing better than the other methods, we per

SUBMITTER: Soufan O 

PROVIDER: S-EPMC4682830 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature