iRBP-Motif-PSSM: Identification of RNA-Binding Proteins Based on Collaborative Learning

• Main Authors: Xin Gao, Donghua Wang, Jun Zhang, Qing Liao, Bin Liu
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: RNA-binding proteins; Motif-PSSM; collaborative learning
• Online Access: https://ieeexplore.ieee.org/document/8895778/

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.