4.7 Article

Efficiently Detecting Protein Complexes from Protein Interaction Networks via Alternating Direction Method of Multipliers

出版社

IEEE COMPUTER SOC
DOI: 10.1109/TCBB.2018.2844256

关键词

Protein complex; protein interaction network; alternating direction method of multipliers; efficiency

资金

  1. National Natural Science Foundation of China [61602352, 61772493, 61702387]
  2. Hubei Natural Science Foundation [2016CFB173, 2017CFB302]
  3. Pioneer Hundred Talents Program of the Chinese Academy of Sciences
  4. Key Technical Innovation Project of Hubei [2017AAA122]

向作者/读者索取更多资源

Protein complexes are crucial in improving our understanding of the mechanisms employed by proteins. Various computational algorithms have thus been proposed to detect protein complexes from protein interaction networks. However, given massive protein interactome data obtained by high-throughput technologies, existing algorithms, especially those with additionally consideration of biological information of proteins, either have low efficiency in performing their tasks or suffer from limited effectiveness. For addressing this issue, this work proposes to detect protein complexes from a protein interaction network with high efficiency and effectiveness. To do so, the original detection task is first formulated into an optimization problem according to the intuitive properties of protein complexes. After that, the framework of alternating direction method of multipliers is applied to decompose this optimization problem into several subtasks, which can be subsequently solved in a separate and parallel manner. An algorithm for implementing this solution is then developed. Experimental results on five large protein interaction networks demonstrated that compared to state-of-the-art protein complex detection algorithms, our algorithm outperformed them in terms of both effectiveness and efficiency. Moreover, as number of parallel processes increases, one can expect an even higher computational efficiency for the proposed algorithm with no compromise on effectiveness.

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