GMAlign: A new network aligner for revealing large conserved functional components

The alignment of protein-protein interaction (PPI) networks is an effective approach to uncover the functionally conserved sub-structure between networks. A wealth of approaches have been developed for global PPI network alignment in recent years. However, due to the computational intractability caused by its NP-completeness, global PPI network alignment remains challenging in finding large conserved components stably for various PPI network pairs. In this paper, we introduce a novel global network aligner based on graph matching method called GMAlign. We assess the outperformance of GMAlign over the state-of-the-art network aligners on various PPI network pairs from the largest BioGRID dataset. It is shown that GMAlign not only can produce larger size alignment, but also can find bigger and denser common connected subgraphs robustly for the first time. Moreover, we shows that GMAlign can produce both structurally and functionally meaningful results in detecting large conserved biological pathways between species. The GMAlign software, datasets and supplementary experimental results can be downloaded at https://github.com/yzlwhu/GMAlign.