Machine learning in drug discovery Event as iCalendar

(Seminars, Computer Science, Science Event Tags)

17 November 2017

4 - 5pm

Venue: Medium Chemistry Building 301-G053

Location: City Campus


Speaker : Professor Yu Zong chen


Machine learning methods have been explored as virtual screening tools for finding bioactive compounds, predicting toxicities and pharmacokinetic properties, and for evaluating the draggability of targets. Here, I present our recent research in the development of machine learning models for prospectively predicting the clinical success of drug targets, and for facilitating the discovery of novel dual-target GPCR ligands and multi-target kinase inhibitors. I also discuss recent development in exploring deep learning methods as the next generation virtual screening tools.


Dr Chen is a Professor in the Department of Pharmacy at National University of Singapore. He has over 20 years of experiences in computer aided drug discovery, cheminformatics and bioinformatics. He invented the inverse docking method for target search, developed the therapeutic target database, revealed distribution patterns of the drug-producing species in nature, and were among the pioneers in applying machine learning methods for drug discovery, target discovery and protein function prediction. Previously, Dr Chen served as the head of the Department of Computational Science at National University of Singapore. He obtained his PhD from University of Manchester in the United Kingdom and previously worked in Ionis Pharmaceuticals, University of Toledo, and Purdue University in the United States. Dr Chen authored over 180 papers, one patent and several book chapters.

If you want to meet Professor Chen please contact Jóhannes Reynisson (e-mail: