Medical & Biological Engineering & Computing

, Volume 57, Issue 12, pp 2553–2565 | Cite as

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

  • Xiaoli Ruan
  • Dongming ZhouEmail author
  • Rencan Nie
  • Ruichao Hou
  • Zicheng Cao
Original Article


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.

Graphical abstract

Framework of the proposed prediction model


Position-specific scoring matrix Jackknife test Support vector machine Isometric mapping Apoptosis proteins 



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).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© International Federation for Medical and Biological Engineering 2019

Authors and Affiliations

  • Xiaoli Ruan
    • 1
  • Dongming Zhou
    • 1
    Email author
  • Rencan Nie
    • 1
  • Ruichao Hou
    • 1
  • Zicheng Cao
    • 2
  1. 1.Information CollegeYunnan UniversityKunmingChina
  2. 2.School of Public HealthSun Yat-sen UniversityShenzhenChina

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