Using weighted entropy to rank chemicals in quantitative high-throughput screening experiments.

ABSTRACT: Quantitative high-throughput screening (qHTS) experiments can simultaneously produce concentration-response profiles for thousands of chemicals. In a typical qHTS study, a large chemical library is subjected to a primary screen to identify candidate hits for secondary screening, validation studies, or prediction modeling. Different algorithms, usually based on the Hill equation logistic model, have been used to classify compounds as active or inactive (or inconclusive). However, observed concentration-response activity relationships may not adequately fit a sigmoidal curve. Furthermore, it is unclear how to prioritize chemicals for follow-up studies given the large uncertainties that often accompany parameter estimates from nonlinear models. Weighted Shannon entropy can address these conce

SUBMITTER: Shockley KR 

PROVIDER: S-EPMC4029130 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature