Perturbation Theory and its Application to Complex Biological Networks --A quantification of systematic features of biological networks
- Series
- Dissertation Defense
- Time
- Tuesday, April 24, 2012 - 11:00 for 2 hours
- Location
- Skiles 006
- Speaker
- Yao Li – School of Mathematics, Georgia Tech
The primary objective of this thesis is to make a quantitative study of
complex biological networks. Our fundamental motivation is to obtain the
statistical dependency between modules by injecting external noise. To
accomplish this, a
deep study of stochastic dynamical systems would be essential. The first
part is about the stochastic dynamical system theory. The classical
estimation of invariant measures of Fokker-Planck equations is improved by
the level set method. Further, we develop a discrete Fokker-Planck-type
equation to study the discrete stochastic dynamical systems. In the second
part, we quantify systematic measures including degeneracy, complexity and
robustness. We also provide a series of results on their properties and the
connection between them. Then we apply our theory to the JAK-STAT signaling
pathway network.