Abstract
Inference of gene regulation nechanism from time series of gene expression patterns, which can be determined by recently developed DNA microarray technology, is getting important. We have been studying algorithms for inferring genetic network architecture from gene expression patterns, using the Boolean network model. In the Boolean network model, each gene is assumed to take 0 (not-expressed) or 1 (expressed) as its state value, and each regulation rule is given as a Boolean function. We developed algorithms for inferring Boolean networks from gene expression patterns. We also developed algorithms for inferring network architecture under more realistic models.
