Among the main interests in many biological studies are the structure of gene regulatory network, and in particular differences in the regulatory interactions between different conditions. However, since the number of available samples is always very small and estimating the network structure is extremely hard, most current algorithms have to assume that the gene regulation does not change between conditions. We propose a new Bayesian network algorithm which (i) utilizes all the samples for estimating regulatory relations that remain the same across conditions, and (ii) explicitly searches for regulatory relationships that are active only in one of the conditions. The result is an easily interpretable map of changes in regulation in several conditions.

This work was supported in part by the IST Programme of the European Community, under the PASCAL Network of Excellence, IST-2002-506778. Part of the work was done at the Department of Computer Science, University of Helsinki, under a grant from the University's Research Funds. This publication only reflects the authors views. All rights are reserved because of other commitments.