Directed Acyclic Graphs (DAGs) are a powerful tool to model the network of dependencies among variables. They provide a basis for causal discovery, and have been widely used in many fields, especially biology. Unfortunately, structure learning is quite non-trivial for DAG. One major difficulty is that some DAGs are unidentifiable with observational data only, and undirected edges cannot be resolved to directed edges.