Feature-Based and String-Based Models for Predicting RNA-Protein Interaction†
AbstractIn 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
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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.
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(3):697.Chicago/Turabian Style
Adjeroh, Donald; Allaga, Maen; Tan, Jun; Lin, Jie; Jiang, Yue; Abbasi, Ahmed; Zhou, Xiaobo. 2018. "Feature-Based and String-Based Models for Predicting RNA-Protein Interaction." Molecules 23, no. 3: 697.
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