Learning Causal Protein-Signaling Networks
Ping He, Zhi Geng, Wei Yan, Zhihai Liu – Pekin University, China
Bayesian network is widely used in causal studies. But learning causal relationships from
experimental data under different conditions is a challenge. We propose an approach for
structural learning from multiple data bases with external interventions. Our approach
is a constraint-based method with three stages, using conditional independence tests to
construct the causal network. We show the results of both simulation and real data. Finally,
we discuss the advantages and disadvantages of our approach and a Bayesian approach.