Assistant Professor of Applied Physics and Applied Mathematics Chris Wiggins will discuss "Machine Learning Approaches to Systems Biology" on Wednesday, April 13, from 2 p.m. to 3 p.m., in the CEPSR Interschool Lab, 7th floor.
Systems biology, the study of collective phenomena in molecular biology, is both informed and constrained by an unprecedented volume of biological data and decades of prior biological knowledge. Wiggins will illustrate how these data, along with tools from machine learning and information theory, can be exploited for studying the inference, organization and origin of biological networks. These include supervised learning approaches for integration of sequence and DNA micro-array data, information theoretic approaches to network organization and discriminative classification for rendering network origins.
Hosted by Distributed Network Analysis (DNA) Lab, this event is free and open to the public.