Identification of self-interacting proteins by integrating random projection classifier and finite impulse response filter.

Journal: BMC genomics
PMID:

Abstract

BACKGROUND: Identification of protein-protein interactions (PPIs) is crucial for understanding biological processes and investigating the cellular functions of genes. Self-interacting proteins (SIPs) are those in which more than two identical proteins can interact with each other and they are the specific type of PPIs. More and more researchers draw attention to the SIPs detection, and several prediction model have been proposed, but there are still some problems. Hence, there is an urgent need to explore a efficient computational model for SIPs prediction.

Authors

  • Zhan-Heng Chen
    Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, Urumqi, 830011, China.
  • Zhu-Hong You
    Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, 830011, China. zhuhongyou@ms.xjb.ac.cn.
  • Li-Ping Li
    Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, Urumqi 830011, China.
  • Yan-Bin Wang
    Xinjiang Technical Institutes of Physics and Chemistry, Chinese Academy of Science, Urumqi 830011, China. zhuhongyou@ms.xjb.ac.cn xiaoli@ms.xjb.ac.cn.
  • Yu Qiu
    The Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, 830011, China.
  • Peng-Wei Hu
    IBM Research, Beijing, 100049, China.