Nature-Inspired Meta-Heuristic Algorithms for Detecting Protein Complexes in Protein-Protein Interaction Networks: A Survey

In cells, various proteins interact to form protein-protein interaction networks. Protein complexes serve as the fundamental units that enable essential functions in biological organisms. Directly detecting protein complexes in protein-protein interaction networks using biology-based methods is costly and time-consuming. In recent years, different computational methods have emerged for identifying or predicting protein complexes within these networks. Following a comprehensive analysis of the issue, the optimization algorithm based on meta-heuristic methods has been completely executed for this specific type of challenge, which started in 2004. This paper provides a systematic survey of such meta-heuristic algorithms. Specifically, 34 related methods published between 2004 and 2024 are collected and summarized, focusing on how to model problems and design optimization algorithms, which are the key components of this survey. Our observations and analyses have revealed several limitations in existing studies and suggested potential avenues for future research.

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Journal
IEEE Transactions on Computational Biology and Bioinformatics
Published
2025-08-25
DOI
https://doi.org/10.1109/tcbbio.2025.3602120
Primary Topic
Bioinformatics and Genomic Networks
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article
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0.00
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article

Nature-Inspired Meta-Heuristic Algorithms for Detecting Protein Complexes in Protein-Protein Interaction Networks: A Survey

Jianyong Sun, Haotian Zhang, Wei Zheng
IEEE Transactions on Computational Biology and Bioinformatics
Bioinformatics and Genomic Networks
article

Nature-Inspired Meta-Heuristic Algorithms for Detecting Protein Complexes in Protein-Protein Interaction Networks: A Survey

Jianyong Sun, Haotian Zhang, Wei Zheng
article en

Abstract

In cells, various proteins interact to form protein-protein interaction networks. Protein complexes serve as the fundamental units that enable essential functions in biological organisms. Directly detecting protein complexes in protein-protein interaction networks using biology-based methods is costly and time-consuming. In recent years, different computational methods have emerged for identifying or predicting protein complexes within these networks. Following a comprehensive analysis of the issue, the optimization algorithm based on meta-heuristic methods has been completely executed for this specific type of challenge, which started in 2004. This paper provides a systematic survey of such meta-heuristic algorithms. Specifically, 34 related methods published between 2004 and 2024 are collected and summarized, focusing on how to model problems and design optimization algorithms, which are the key components of this survey. Our observations and analyses have revealed several limitations in existing studies and suggested potential avenues for future research.

IEEE Transactions on Computational Biology and BioinformaticsVol. 22(6)
Shanxi University (CN), Xi'an Jiaotong University (CN)
Openalex Percentile: Top 80%
Bioinformatics and Genomic Networks
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Nature-Inspired Meta-Heuristic Algorithms for Detecting Protein Complexes in Protein-Protein Interaction Networks: A Survey — Jianyong Sun, Haotian Zhang, et al. · IEEE Transactions on Computational Biology and Bioinformatics (2025) | TGRS Research Map | TGRS