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Prediction of apoptosis protein subcellular location based on position-specific scoring matrix and isometric mapping algorithm

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Abstract

Apoptosis proteins are related to many diseases. Obtaining the subcellular localization information of apoptosis proteins is helpful to understand the mechanism of diseases and to develop new drugs. At present, the researchers mainly focus on the primary protein sequences, so there is still room for improvement in the prediction accuracy of the subcellular localization of apoptosis proteins. In this paper, a new method named ERT-ECT-PSSM-IS is proposed to predict apoptosis proteins based on the position-specific scoring matrix (PSSM). First, the local and global features of different directions are extracted by evolutionary row transformation (ERT) and cross-covariance of evolutionary column transformation (ECT) based on PSSM (ERT-ECT-PSSM). Second, an improved isometric mapping algorithm (I-SMA) is used to eliminate redundant features. Finally, we adopt a support vector machine (SVM) to classify our results, and the prediction accuracy is evaluated by jackknife cross-validation tests. The experimental results show that the proposed method not only extracts more abundant feature expression but also has better predictive performance and robustness for the subcellular localization of apoptosis proteins in ZD98, ZW225, and CL317 databases.

Framework of the proposed prediction model

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Acknowledgments

The authors thank the editors and the anonymous reviewers for their careful works and valuable suggestions for this study. This research was financially supported by the National Natural Science Foundation of China (grant nos. 61463052, 61365001), and the 10th Research Innovation Project of Yunnan University of China (no. 2018Z081), and Yunnan Province University Key Laboratory Construction Plan Funding, China (no. 2019Y0003).

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Authors and Affiliations

  1. Information College, Yunnan University, Kunming, 650504, China

    Xiaoli Ruan, Dongming Zhou, Rencan Nie & Ruichao Hou

  2. School of Public Health, Sun Yat-sen University, Shenzhen, 510080, China

    Zicheng Cao

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  1. Xiaoli Ruan
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Correspondence to Dongming Zhou.

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Ruan, X., Zhou, D., Nie, R. et al. Prediction of apoptosis protein subcellular location based on position-specific scoring matrix and isometric mapping algorithm. Med Biol Eng Comput 57, 2553–2565 (2019). https://doi.org/10.1007/s11517-019-02045-3

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