An efficient algorithm for global alignment of protein-protein interaction networks

Abstract

Global alignment of two protein-protein interaction networks is an essentially important task in bioinformatics/computational biology field of study. It is a challenging and widely studied research topic in recent years. Accurately aligned networks allow us to identify functional modules of proteins and/or orthologous proteins from which unknown functions of a protein can be inferred. We here introduce a novel efficient heuristic global network alignment algorithm called FASTAn, which includes two phases: the first to construct an initial alignment and the second to improve such alignment by exerting a repeated local optimization procedure. The experimental results demonstrated that FASTAn outperformed SPINAL, the state-of-the-art global network alignment method in terms of both commonly used objective scores and the running time.