Approximation algorithms for orienting mixed graphs

Graph orientation is a fundamental problem in graph theory that has recently arisen in the study of signaling-regulatory pathways in protein networks. Given a graph and a list of source–target vertex pairs, one wishes to assign directions to the edges so as to maximize the number of pairs that admit a directed source-to-target path. When the input graph is undirected, a sub-logarithmic approximation is known for this problem. However, the approximability of the biologically-relevant variant, in which the input graph has both directed and undirected edges, was left open. Here we give the first approximation algorithms to this problem. Our algorithms provide a sub-linear guarantee in the general case, and logarithmic guarantees for structured instances.

Authors

• Michael Elberfeld
• Danny Segev
• Colin R. Davidson
• Dana Silverbush
• Roded Sharan

Keywords

• Protein–protein interaction network
• Mixed graph
• Graph orientation
• Approximation algorithm