A novel approach, PRBP predicts RNA-binding proteins using the information of predicted RNA-binding residues in conjunction with a random forest based method. For a given protein, we first predict its RNA-binding residues and then judge whether the protein binds RNA or not based on information from that prediction.
In this study we attempt to predict RNA-binding proteins directly from amino acid sequences. A novel approach, PRBP predicts RNA-binding proteins using the ...
A novel approach, PRBP predicts RNA-binding proteins using the information of predicted RNA-binding residues in conjunction with a random forest based method.
Bibliographic details on PRBP: Prediction of RNA-Binding Proteins Using a Random Forest Algorithm Combined with an RNA-Binding Residue Predictor.
Prediction of RNA-binding residues in proteins from primary sequence using an enriched random forest model with a novel hybrid feature. *Algorithms.
Oct 12, 2015 · In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the ...
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Dec 21, 2016 · In this study, we present the RBPPred (an RNA-binding protein predictor), a new method based on the support vector machine, to predict whether a protein binds ...
We predict RNA interacting residues in proteins by implementing a well-built random forest classifier. The experiments show that our method is able to detect ...
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This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA.
[PDF] Prediction of RNA-binding proteins from primary sequence by ...
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PRBP: Prediction of RNA-Binding Proteins Using a Random Forest Algorithm Combined with an RNA-Binding Residue Predictor · Xin MaJing GuoKe XiaoXiao Sun.
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