Disease module identification - algorithms and application to glioma

28^th June 2013, 11:00 ALT
Dr. Shan He
School of Computer Science
University of Birmingham

Abstract

Network medicine is an emerging approach to human complex disease which aims to understand the molecular complexity of a particular disease using complex network theory. One of the fundamental concepts in network medicine is disease module, which is defined as a group of interacting biological network components, e.g., proteins that collectively contribute to the development of disease after genetic/environmental perturbations. The disease module can serve as biomarkers for diagnosis and prognosis with better accuracy and reproducibility than traditional biomarkers that derived without network information. More importantly, disease module enables us to isolate a small biological sub-network from a vast biological network for better insights into the molecular mechanisms of disease, which ultimately will lead to novel therapeutic targets. In this talk, I will introduce two novel algorithms recently developed in my group for the identification of disease modules. As a case study, disease modules of glioma, a kind of brain tumour, identified by the two algorithms will be presented.