March 10, 2006
Groebner Models the Fruit Fly
One goal of systems biology is to
predict and modify the behavior of
biological networks by modeling their responses to certain types of
perturbations. The construction of mathematical models from these
responses, referred to as reverse engineering, is an important step in
elucidating the structure and dynamics of such networks. In this
talk a
discrete modeling approach to reverse engineer networks from
experimental
time series data will be introduced. The method, rooted in
computational
algebra, uses algorithmic tools from Groebner basis theory. This
allows
one to compactly describe the space of discrete models for a given data
set in terms of a system of polynomial functions over a finite field.
One can then select minimal models from this space which fit the data
set.
The effectiveness of the algorithm will be demonstrated on a segment
polarity network in the fruit fly, as well as on simulated biochemical
networks.