A big data approach with artificial neural network and molecular similarity for chemical data mining and endocrine disruption prediction.

Journal: Indian journal of pharmacology
Published Date:

Abstract

CONTEXT: Chemical toxicity prediction at early stage drug discovery phase has been researched for years, and newest methods are always investigated. Research data comprising chemical physicochemical properties, toxicity, assay, and activity details create massive data which are becoming difficult to manage. Identifying the desired featured chemical with the desired biological activity from millions of chemicals is a challenging task.

Authors

  • Renjith Paulose
    Research and Development Centre, Bharathiar University, Coimbatore, Tamil Nadu, India.
  • Kalirajan Jegatheesan
    Center for Research and PG Studies in Botany and Biotechnology, Thiagarajar College (Autonomous), Madurai, Tamil Nadu, India.
  • Gopal Samy Balakrishnan
    Department of Biotechnology, Liatris Biosciences LLP, Kottayam, Kerala, India.