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Classification of Protein Modification Sites with Machine Learning

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Intelligent Computing Theories and Application (ICIC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12464))

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Abstract

Lysine malonylation is a newly discovered type of protein post-translational modification, which plays an essential role in many biological activities. A good knowledge of malonylation sites can serve as guidance in solving a large number of biological problems, such as disease diagnosis and drug discovery. There have already been several experimental approaches to identify modification sites, but they are relatively expensive. In this work, we propose three novel machine learning models and utilizes several effective feature description methods. The model is trained based on the cross validation method named Split to Equal Validation (SEV). The experiments show that our model outperforms the others considerably.

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Acknowledgments

This work was supported by the grants of the National Science Foundation of China, Nos. 61902337, 61702445, and the grant from the Ph.D. Programs Foundation of Ministry of Education of China (No. 20120072110040). The Shandong Provincial Natural Science Foundation, China (No. ZR2018LF005).

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Authors and Affiliations

  1. School of Information Science and Engineering, University of Jinan, Jinan, 250024, China

    Jin Sun, Yi Cao & Yuehui Chen

  2. School of Information and Electrical Engineering, Xuzhou University of Technology, Xuzhou, 221018, China

    Wenzheng Bao

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  1. Jin Sun
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  3. Yi Cao
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  4. Yuehui Chen
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Contributions

Data Availability

To data used to support the findings of this study are available from the corresponding author upon request.

Author Contribution Statement

W.B. conceived the method. Z.L designed the method. B.Y. designed the website of this algorithm. Y.Z. conducted the experiments and W.B. wrote the main manuscript text. All authors reviewed the manuscript.

Corresponding author

Correspondence to Yuehui Chen .

Editor information

Editors and Affiliations

  1. Institute of Machine Learning and Systems Biology, Tongji University, Shanghai, China

    De-Shuang Huang

  2. School of Electrical Engineering, University of Ulsan, Ulsan, Korea (Republic of)

    Kang-Hyun Jo

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Sun, J., Bao, W., Cao, Y., Chen, Y. (2020). Classification of Protein Modification Sites with Machine Learning. In: Huang, DS., Jo, KH. (eds) Intelligent Computing Theories and Application. ICIC 2020. Lecture Notes in Computer Science(), vol 12464. Springer, Cham. https://doi.org/10.1007/978-3-030-60802-6_38

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  • DOI: https://doi.org/10.1007/978-3-030-60802-6_38

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