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RNA-Binding Proteins

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Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions.

Protein and peptide letters
The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to det...

A deep neural network approach for learning intrinsic protein-RNA binding preferences.

Bioinformatics (Oxford, England)
MOTIVATION: The complexes formed by binding of proteins to RNAs play key roles in many biological processes, such as splicing, gene expression regulation, translation and viral replication. Understanding protein-RNA binding may thus provide important...

A deep boosting based approach for capturing the sequence binding preferences of RNA-binding proteins from high-throughput CLIP-seq data.

Nucleic acids research
Characterizing the binding behaviors of RNA-binding proteins (RBPs) is important for understanding their functional roles in gene expression regulation. However, current high-throughput experimental methods for identifying RBP targets, such as CLIP-s...

RBPPred: predicting RNA-binding proteins from sequence using SVM.

Bioinformatics (Oxford, England)
MOTIVATION: Detection of RNA-binding proteins (RBPs) is essential since the RNA-binding proteins play critical roles in post-transcriptional regulation and have diverse roles in various biological processes. Moreover, identifying RBPs by computationa...