DeepEP: a deep learning framework for identifying essential proteins.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Essential proteins are crucial for cellular life and thus, identification of essential proteins is an important topic and a challenging problem for researchers. Recently lots of computational approaches have been proposed to handle this problem. However, traditional centrality methods cannot fully represent the topological features of biological networks. In addition, identifying essential proteins is an imbalanced learning problem; but few current shallow machine learning-based methods are designed to handle the imbalanced characteristics.

Authors

  • Min Zeng
    Nephrology Department, Affiliated Hospital of Southern Medical University: Shenzhen Longhua New District People's Hospital, Shenzhen, China.
  • Min Li
    Hubei Provincial Institute for Food Supervision and Test, Hubei Provincial Engineering and Technology Research Center for Food Quality and Safety Test, Wuhan 430075, China.
  • Fang-Xiang Wu
  • Yaohang Li
  • Yi Pan
    Department of Neurosis and Psychosomatic Diseases, Huzhou Third Municipal Hospital, The Affiliated Hospital of Huzhou University, Huzhou, Zhejiang, China.