Gene networks from microarray time series data
Several approaches to the reconstruction of gene regulatory networks
have been suggested in the past few years, among others dynamic
Bayesian networks and linear state space models. I will discuss the
underlying principles of such models and evaluate their applicability
to a set of Affymetrix gene chip data on genes involved in the
circadian clock in Arabidopsis thaliana. I will present some intuition
why Bayesian approaches, incorporating an automated complexity control
in network and parameter estimation, might be particularly suitable
for such task.
Vincent Moulton
© 2005, CBL
Computational Biology Laboratory,
School of Computing Sciences,
University of East Anglia,
Norwich, NR4 7TJ, UK.