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Open AccessArticle

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

Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26508, USA
Faculty of Software, Fujian Normal University, Fuzhou 350108, China
McIntire School of Commerce, University of Virginia, Charlottesville, VA 22904, USA
McGovern Medical School, and School of Biomedical Informatics, The University of Texas Health Science Center at Houston (UTHealth), Houston, TX 77030, USA
Author to whom correspondence should be addressed.
A shorter version of this work was presented at ACM BCB’17, August 2017, Boston, MA, USA.
Molecules 2018, 23(3), 697;
Received: 21 December 2017 / Revised: 17 February 2018 / Accepted: 21 February 2018 / Published: 19 March 2018
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. View Full-Text
Keywords: RNA Protein Interaction; RPI; k-mers; suffix trees; richness; protein structure; RNA structure RNA Protein Interaction; RPI; k-mers; suffix trees; richness; protein structure; RNA structure
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Adjeroh, D.; Allaga, M.; Tan, J.; Lin, J.; Jiang, Y.; Abbasi, A.; Zhou, X. Feature-Based and String-Based Models for Predicting RNA-Protein Interaction. Molecules 2018, 23, 697.

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