Deep learning-based multi-functional therapeutic peptides prediction with a multi-label focal dice loss function.

Journal: Bioinformatics (Oxford, England)
Published Date: Jun 1, 2023

Abstract

MOTIVATION: With the great number of peptide sequences produced in the postgenomic era, it is highly desirable to identify the various functions of therapeutic peptides quickly. Furthermore, it is a great challenge to predict accurate multi-functional therapeutic peptides (MFTP) via sequence-based computational tools.

Authors

  • Henghui Fan
    Information Materials and Intelligent Sensing Laboratory of Anhui Province and Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China.
  • Wenhui Yan
    Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, 111 Jiulong Road, Hefei, Anhui 230601, China.
  • Lihua Wang
    Division of Physical Biology & Bioimaging Center, Shanghai Synchrotron Radiation Facility, CAS Key Laboratory of Interfacial Physics and Technology, Shanghai Institute of Applied Physics, Chinese Academy of Sciences, Shanghai 201800, China.
  • Jie Liu
    School of Bioscience and Bioengineering, South China University of Technology, Guangzhou, China.
  • Yannan Bin
    Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Institutes of Physical Science and Information Technology, Anhui University, Hefei, Anhui 230601, China.
  • Junfeng Xia

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