Comparative Analysis of Biological Networks Using Markov Models

Dr. Byung-Jun Yoon ., Texas A&M University

Aug 10, 2011 2:00 PM





Recent advances in high-throughput experimental techniques for measuring molecular interactions have enabled the systematic study of biological interactions on a global scale. Comparative analysis of genome-scale interaction networks can lead to important insights into the functional organization of cells and their regulatory mechanisms. In this talk, we will review the concept of comparative network analysis, discuss their significance in biomedical research, and review mathematical models and algorithms that can be used for comparing biological networks. Especially, we will focus on Markov models such as the hidden Markov model (HMM) and the Markov chain - which have been widely used across various fields in science and engineering, and show how these models can be used for efficient comparative analysis of large-scale networks.


This page is maintained by Yumi Yi (
Last update: Oct 31, 2011