Abstract

Signaling pathways play central roles in responding to stimuli or transmitting signals from outside to inside of cells, which in turn regulate a series of complex biological processes that are vital for the function of cells. Unfortunately, the structure and function of most pathways are not complete or even not available. In the past decade, the availability of large amounts of high-throughput ‘omics’ data enables it possible to infer signaling pathways with computational methodologies that can help guide experiments in lab with low cost within short time. In this review, we present the latest progress being made in computational methodologies that are proposed for identifying signaling pathways from molecular interaction networks.

Keywords: Data integration, graph model, heuristic method, molecular interaction networks, optimization model, signaling pathway, protein interactions, global optimal, biological systems, integer linear programming