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.