Inferring gene regulatory networks from classified microarray data: Initial results

Using a method of selecting genes on the basis of their utility for classification [2], we apply optimal gene network inference to the 24 most highly-ranked genes in a leukemia data set [1]. In order to have confidence in the resulting Bayesian gene networks, we first validate the network inference methodology on synthetic data and establish that the methodology has very high specificity, i.e. if an edge is inferred then it is highly likely to be correct. However, we are unable to confidently predict directed edges in the network.