Protein acetylation sites with complex-valued polynomial model

Abstract

Protein acetylation refers to a process of adding acetyl groups (CH3CO-) to lysine residues on protein chains. As one of the most commonly used protein post-translational modifications, lysine acetylation plays an important role in different organisms. In our study, we developed a human-specific method which uses a cascade classifier of complex-valued polynomial model (CVPM), combined with sequence and structural feature descriptors to solve the problem of imbalance between positive and negative samples. Complex-valued gene expression programming and differential evolution are utilized to search the optimal CVPM model. We also made a systematic and comprehensive analysis of the acetylation data and the prediction results. The performances of our proposed method are 79.15% in S_p, 78.17% in S_n, 78.66% in ACC 78.76% in F1, and 0.5733 in MCC, which performs better than other state-of-the-art methods.

Graphical abstract

Keywords

protein acetylation / complex-valued polynomial model / machine learning

Wenzheng Bao received the PhD degree in Computer Science from Tongji University, China in 2018. He is an associate professor, the master’s tutor of School of Information Engineering, Xuzhou University of Technology, China. His research interests include bioinformatics and machine learning

Bin Yang received the PhD degree in Computer Science from Shandong University, China in 2014. He is a professor, the master’s tutor of School of Information Science and Engineering, Zaozhuang University, China. His research interests include bioinformatics and machine learning

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 61902337), Xuzhou Science and Technology Plan Project (KC21047), Jiangsu Provincial Natural Science Foundation (No. SBK2019040953), Natural Science Fund for Colleges and Universities in Jiangsu Province (No. 19KJB520016) and Young Talents of Science and Technology in Jiangsu, the Key Research Program of the Science Foundation of Shandong Province (ZR2020KE001), the talent project of “Qingtan Scholar” of Zaozhuang University, the PhD research startup foundation of Zaozhuang University (No.2014BS13), and Zaozhuang University Foundation (No. 2015YY02).

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