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Identification of Hotspots in Protein-Protein Interactions Based on Recursive Feature Elimination

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Intelligent Computing Theories and Application (ICIC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10954))

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Abstract

The study of protein-protein interactions and protein structure through computational methods is critical to understand protein function. Hot spot residues play an important role in bioinformatics to reveal life activities. However, conventional hot spots prediction methods may face great challenges. This paper proposes a hot spot prediction method based on feature selection method SVM-RFE to improve the training performance. SMOTE based oversampling is used to adds new samples to avoid an overfitting classifier. SVM-RFE is then invoked to obtained optimal feature subset. Finally, a feature-based SVM is created to predict the hot spots. Experimental results indicate that the performance of hot spots prediction has been significantly improved compared with the previous methods.

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Acknowledgment

The authors thank the members of Machine Learning and Artificial Intelligence Laboratory, School of Computer Science and Technology, Wuhan University of Science and Technology, for their helpful discussion within seminars. This work was supported in part by National Natural Science Foundation of China (No. 61502356, 61273225), by Hubei Province Natural Science Foundation of China (No. 2018CFB526).

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Authors and Affiliations

  1. Hubei Key Laboratory of Intelligent Information Processing and Real-Time Industrial System, School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430065, China

    Xiaoli Lin & Xiaolong Zhang

  2. Information and Engineering Department of City College, Wuhan University of Science and Technology, Wuhan, 430083, China

    Xiaoli Lin & Fengli Zhou

Authors
  1. Xiaoli Lin
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  2. Xiaolong Zhang
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  3. Fengli Zhou
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Corresponding author

Correspondence to Xiaolong Zhang .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Polytechnic of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

  4. Indian Institute of Technology Kanpur, Kanpur, India

    Phalguni Gupta

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Lin, X., Zhang, X., Zhou, F. (2018). Identification of Hotspots in Protein-Protein Interactions Based on Recursive Feature Elimination. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10954. Springer, Cham. https://doi.org/10.1007/978-3-319-95930-6_56

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  • DOI: https://doi.org/10.1007/978-3-319-95930-6_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95929-0

  • Online ISBN: 978-3-319-95930-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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