CL-ACP: a parallel combination of CNN and LSTM anticancer peptide recognition model.

Journal: BMC bioinformatics
Published Date: Oct 20, 2021

Abstract

BACKGROUND: Anticancer peptides are defence substances with innate immune functions that can selectively act on cancer cells without harming normal cells and many studies have been conducted to identify anticancer peptides. In this paper, we introduce the anticancer peptide secondary structures as additional features and propose an effective computational model, CL-ACP, that uses a combined network and attention mechanism to predict anticancer peptides.

Authors

  • Huiqing Wang
    College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China.
  • Jian Zhao
    Key Laboratory of Intelligent Rehabilitation and Barrier-Free for the Disabled (Changchun University), Ministry of Education, Changchun University, Changchun 130012, China.
  • Hong Zhao
    Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, China.
  • Haolin Li
    College of Information and Computer, Taiyuan University of Technology, Taiyuan, 030024, China.
  • Juan Wang
    Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China.

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