On the use of machine learning methods for modern drug discovery

Article type: Other

Authors: Soto, Axel J.

Affiliations: Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada. E-mail: soto@cs.dal.ca

Abstract: Machine learning techniques provide a strong basis for enhancing the process of drug discovery within the pharmaceutical industry. During the last decade, chemoinformatics – briefly defined as informatics applied on chemical data – has gained much importance due to the economical benefits obtained from the application of in silico (i.e., computer-based) models. Prediction of candidate compounds for medicinal use is a hard task due to the complex and usually unknown relationships between structure and biological properties. This short article aims at summarizing the main contributions of a PhD thesis [PhD thesis, Universidad Nacional del Sur, Argentina, 2010] and, at the same time, at encouraging research on this challenging area.

Keywords: Chemoinformatics, machine learning

DOI: 10.3233/AIC-2010-0487

Journal: AI Communications, vol. 24, no. 1, pp. 99-100, 2011