Fig. 1

Overall Model. Step 1: A Gaussian mixture model (GMM) is used to soft-cluster gene expression (GE) data. Step 2: A heuristic is proposed to quantitatively extend the sparse protein-protein interactions by using transitive linkages. A novel way is then proposed to score protein interactions by combining topological properties of extended protein-protein interaction network (PPIN) and GE correlations. Step 3: A Gaussian Hidden Markov Model (GHMM) is used to identify gene regulatory pathways and refine interaction scores, both of which are then used as structural priors to constrain the model of GRN. Step 4: Lastly, the GRN from GE is refined using a Bayesian Gaussian Mixture (BGM) model by including the structural priors derived from Step 3