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Inferring essential proteins from centrality in interconnected multilayer networks

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  • Jin, Haiyan
  • Zhang, ChenXing
  • Ma, Mengzhou
  • Gong, Qianhua
  • Yu, Liang
  • Guo, Xingli
  • Gao, Lin
  • Wang, Bingbo

Abstract

Computational tool for inferring essential genes and their coding essential proteins based on its topological features in biological network is crucial for insights into vital and disease mechanism of organisms. The problem of how to quantify this correspondence via network centralities in an incomplete protein interaction network (PIN), such as that of human, remains open. Here we develop Random Walk Occupation (RWO) augmented method in interconnected multilayer network model to disclose topological characteristics of essential proteins. The peculiar non-hub essential proteins can be revealed in yeast–human interconnected networks. Statistically RWO augmented method performs well, and improves the prediction results in incomplete human PIN and maintains noticeable performance in well-tested yeast PIN. Biologically, the detected non-hub essential proteins really participate in some vital biological function. Overall, we present a systematic method for deeper understanding and effective identification of essential proteins.

Suggested Citation

  • Jin, Haiyan & Zhang, ChenXing & Ma, Mengzhou & Gong, Qianhua & Yu, Liang & Guo, Xingli & Gao, Lin & Wang, Bingbo, 2020. "Inferring essential proteins from centrality in interconnected multilayer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    • Handle: RePEc:eee:phsmap:v:557:y:2020:i:c:s0378437120304428
    DOI: 10.1016/j.physa.2020.124853
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    References listed on IDEAS

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    2. Chao Qin & Yongqi Sun & Yadong Dong, 2017. "A new computational strategy for identifying essential proteins based on network topological properties and biological information," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-24, July.
    3. Guri Giaever & Angela M. Chu & Li Ni & Carla Connelly & Linda Riles & Steeve Véronneau & Sally Dow & Ankuta Lucau-Danila & Keith Anderson & Bruno André & Adam P. Arkin & Anna Astromoff & Mohamed El Ba, 2002. "Functional profiling of the Saccharomyces cerevisiae genome," Nature, Nature, vol. 418(6896), pages 387-391, July.
    4. Manlio De Domenico & Albert Solé-Ribalta & Elisa Omodei & Sergio Gómez & Alex Arenas, 2015. "Ranking in interconnected multilayer networks reveals versatile nodes," Nature Communications, Nature, vol. 6(1), pages 1-6, November.
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