DL-PPI: a method on prediction of sequenced protein-protein interaction based on deep learning.

Journal: BMC bioinformatics
Published Date:

Abstract

PURPOSE: Sequenced Protein-Protein Interaction (PPI) prediction represents a pivotal area of study in biology, playing a crucial role in elucidating the mechanistic underpinnings of diseases and facilitating the design of novel therapeutic interventions. Conventional methods for extracting features through experimental processes have proven to be both costly and exceedingly complex. In light of these challenges, the scientific community has turned to computational approaches, particularly those grounded in deep learning methodologies. Despite the progress achieved by current deep learning technologies, their effectiveness diminishes when applied to larger, unfamiliar datasets.

Authors

  • Jiahui Wu
    Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China.
  • Bo Liu
    Wuhan United Imaging Healthcare Surgical Technology Co., Ltd., Wuhan, China.
  • Jidong Zhang
    Department of Immunology, Zunyi Medical College, Zunyi, 563000, China.
  • Zhihan Wang
    Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China.
  • Jianqiang Li
    School of Software Engineering, Beijing University of Technology, Beijing, China. Electronic address: lijianqiang@bjut.edu.cn.