Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

Donald Adjeroh

doi:10.3390/molecules23030697

Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

2018-03-19

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DOI：10.3390/molecules23030697

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In this work, we study two approaches for the problem of RNA-Protein Interaction (RPI). In the first approach, we use a feature-based technique by combining extracted features from both sequences and secondary structures. The feature-based approach enhanced the prediction accuracy as it included much more available information about the RNA-protein pairs. In the second approach, we apply search algorithms and data structures to extract effective string patterns for prediction of RPI, using both sequence information (protein and RNA sequences), and structure information (protein and RNA secondary structures). This led to different string-based models for predicting interacting RNA-protein pairs. We show results that demonstrate the effectiveness of the proposed approaches, including comparative results against leading state-of-the-art methods.

Keywords:

RNA Protein Interaction

RPI

k-mers

suffix trees

richness

protein structure

RNA structure

Feature-Based and String-Based Models for Predicting RNA-Protein Interaction

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