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A new computational strategy for identifying essential proteins based on network topological properties and biological information

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  • Chao Qin
  • Yongqi Sun
  • Yadong Dong

Abstract

Essential proteins are the proteins that are indispensable to the survival and development of an organism. Deleting a single essential protein will cause lethality or infertility. Identifying and analysing essential proteins are key to understanding the molecular mechanisms of living cells. There are two types of methods for predicting essential proteins: experimental methods, which require considerable time and resources, and computational methods, which overcome the shortcomings of experimental methods. However, the prediction accuracy of computational methods for essential proteins requires further improvement. In this paper, we propose a new computational strategy named CoTB for identifying essential proteins based on a combination of topological properties, subcellular localization information and orthologous protein information. First, we introduce several topological properties of the protein-protein interaction (PPI) network. Second, we propose new methods for measuring orthologous information and subcellular localization and a new computational strategy that uses a random forest prediction model to obtain a probability score for the proteins being essential. Finally, we conduct experiments on four different Saccharomyces cerevisiae datasets. The experimental results demonstrate that our strategy for identifying essential proteins outperforms traditional computational methods and the most recently developed method, SON. In particular, our strategy improves the prediction accuracy to 89, 78, 79, and 85 percent on the YDIP, YMIPS, YMBD and YHQ datasets at the top 100 level, respectively.

Suggested Citation

  • 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.
  • Handle: RePEc:plo:pone00:0182031
    DOI: 10.1371/journal.pone.0182031
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    References listed on IDEAS

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    1. Chao Qin & Yongqi Sun & Yadong Dong, 2016. "A New Method for Identifying Essential Proteins Based on Network Topology Properties and Protein Complexes," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-30, August.
    2. Jiawei Luo & Yi Qi, 2015. "Identification of Essential Proteins Based on a New Combination of Local Interaction Density and Protein Complexes," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-27, June.
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    Cited by:

    1. 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).

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