Adaptive Large Neighborhood Search Enhances Global Protein-Protein Network Alignment

• Main Authors: Vu, Thi Ngoc Anh, Nguyen, Trong Dong, Nguyen, Vu Hoang Vuong, Dang, Thanh Hai, Do, Duc Dong
• 格式: Article
• 語言: English
• 出版: H. : ĐHQGHN 2019
• 主題: Heuristic; Protein-protein interaction networks; network alignment; neighborhood search
• 在線閱讀: http://repository.vnu.edu.vn/handle/VNU_123/64780
• 機構: Vietnam National University, Hanoi

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