Thursday, 4th September, 2014, 11.00-12.00

Illuminating biology through navigating big data in drug discovery.

Methods like phenotypic screening, next generation sequencing and high content screening have become standard in drug discovery. All these methods yield a huge amount of data, which need to be processed and analyzed in order to be able to extract biologically relevant conclusions out of them. This novel, richer, more complicated data landscape means we need state-of-the-art in silico approaches to increase the probability of a lead compound to be disease relevant. This requires data analytics approaches informing on relevant assays, compound subset design to probe the biology, visualisation of complex biological data, and target/MOA hypotheses generation.

Speaker: Elisabet Gregori Puigjané; In silico Lead Discovery Group at the Novartis Institutes of Biomedical Research

Room Xipre (seminar 173.06-183.01), PRBB.