Adaptive Large Neighborhood Search Enhances Global Protein-Protein Network Alignment - Vu, Thi Ngoc Anh (H. : ĐHQGHN, 2019)
Aligning protein-protein interaction networks from different species is a useful mechanism for figuring out orthologous proteins, predicting/verifying protein unknown functions or constructing evolutionary relationships. The network alignment problem is proved to be NP-hard, requiring exponential-time algorithms, which is not feasible for the fast growth of biological data. In this paper, we present a novel global protein-protein interaction network alignment algorithm, which is enhanced with an extended large neighborhood search heuristics. Evaluated on benchmark datasets of yeast, fly, human and worm, the proposed algorithm outperforms state-of-the-art algorithms. Furthermore, the complexity of ours is polynomial, thus being scalable to large biological networks in practice