IRBP-Motif-PSSM: Identification of RNA-binding proteins based on collaborative learning

Xin Gao, Donghua Wang, Jun Zhang, Qing Liao*, Bin Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

RNAs and RNA-binding proteins (RBPs) in cells can bind with each other to form a nuclear ribonucleoprotein (RNP) complex, playing important roles in life processes, and gene regulation. How to accurately predict the RNA-binding proteins is a big challenge and hot research task. Here, we proposed a new computational predictor called iRBP-Motif-PSSM for identifying RNA-binding proteins by combining the motif information and the evolutionary information extracted from the Position Specific Scoring Matrixes. Collaborative Learning was employed to address the instability problem of the predictor. The experimental results showed that iRBP-Motif-PSSM showed better performance than other existing methods for identifying NA-binding proteins, indicating that iRBP-Motif-PSSM is a useful tool for biological analysis.

Original languageEnglish
Article number8895778
Pages (from-to)168956-168962
Number of pages7
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019

Keywords

  • Motif-PSSM
  • RNA-binding proteins
  • collaborative learning

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