Heuristics and metaheuristics for biological network alignment: A review

被引:9
作者
Ma, Lijia [1 ]
Shao, Zengyang [1 ]
Li, Lingling [2 ]
Huang, Jiaxiang [2 ]
Wang, Shiqiang [1 ]
Lin, Qiuzhen [1 ]
Li, Jianqiang [1 ]
Gong, Maoguo [3 ]
Nandi, Asoke K. [1 ,4 ]
机构
[1] Shenzhen Univ, Sch Comp Sci & Software Engn, Shenzhen 518060, Peoples R China
[2] Xidian Univ, Sch Artificial Intelligence, Key Lab Intelligent Percept & Image Understanding, Minist Educ, Xian 710071, Peoples R China
[3] Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China
[4] Brunel Univ London, Dept Elect & Elect Engn, Uxbridge UB8 3PH, Middx, England
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Network alignment; Biological networks; Heuristics; Metaheuristics; Optimization; PROTEIN-INTERACTION NETWORKS; GLOBAL ALIGNMENT; MAXIMIZING ACCURACY; PAIRWISE ALIGNMENT; MEMETIC ALGORITHM; GENETIC ALGORITHM; NEURAL-NETWORKS; OPTIMIZATION; EVOLUTION; YEAST;
D O I
10.1016/j.neucom.2021.08.156
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In recent years, with the emergence of big-data and high-throughput biological analyses, massive biological data have been generated and accessed, and many heuristic and metaheuristic algorithms have been proposed for further analysis and extraction of the potential knowledge of those data. Biological network alignment (BNA) aligns proteins between species to maximally conserve biological and topological structures of proteins. The studies of BNAs are essential for uncovering conserved protein interactions of biological networks with functional homology and understanding the evolutionary process across species. In this paper, we give a comprehensive review for the works in BNAs from a novel taxonomy: heuristic and metaheuristic BNAs. Moreover, we give some comparative analyses of the alignment models, real data sets, evaluation metrics and experimental results in these works. Finally, we provide some conclusions and give some possible future directions for BNAs. (C) 2022 Published by Elsevier B.V.
引用
收藏
页码:426 / 441
页数:16
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