Gene networks from microarray time series data

Lorenz Wernisch, Birkbeck College, London

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.