Before revision:  We formulate the inference of condition specific network structures that incorporates relevant prior knowledge as a convex optimization problem, and develop an efficient learning algorithm to jointly infer the biological networks as well as their changes. We test the proposed method on simulation data sets and demonstrate the effectiveness of this method .
After revision:  We formulate the inference of condition specific network structures that incorporates relevant prior knowledge as a convex optimization problem, and develop an efficient learning algorithm to jointly infer the conserved biological network and the significant rewiring across different conditions. We used a novel sampling scheme to estimate the expected error rate due to random knowledge and based on which, developed a strategy that fully exploits the benefit of this data-knowledge integrated approach. We demonstrated and validated the principle and performance of our method using synthetic datasets .