Identification of protein-interacting nucleotides in a RNA sequence using composition profile of tri-nucleotides.

Panwar, Bharat and Raghava, G.P.S. (2015) Identification of protein-interacting nucleotides in a RNA sequence using composition profile of tri-nucleotides. Genomics, 105 (4). pp. 197-203. ISSN 1089-8646

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Abstract

The RNA-protein interactions play a diverse role in the cells, thus identification of RNA-protein interface is essential for the biologist to understand their function. In the past, several methods have been developed for predicting RNA interacting residues in proteins, but limited efforts have been made for the identification of protein-interacting nucleotides in RNAs. In order to discriminate protein-interacting and non-interacting nucleotides, we used various classifiers (NaiveBayes, NaiveBayesMultinomial, BayesNet, ComplementNaiveBayes, MultilayerPerceptron, J48, SMO, RandomForest, SMO and SVM(light)) for prediction model development using various features and achieved highest 83.92% sensitivity, 84.82 specificity, 84.62% accuracy and 0.62 Matthew's correlation coefficient by SVM(light) based models. We observed that certain tri-nucleotides like ACA, ACC, AGA, CAC, CCA, GAG, UGA, and UUU preferred in protein-interaction. All the models have been developed using a non-redundant dataset and are evaluated using five-fold cross validation technique. A web-server called RNApin has been developed for the scientific community (http://crdd.osdd.net/raghava/rnapin/).

Item Type:	Article
Additional Information:	Copyright of this article belongs to Elsevier.
Uncontrolled Keywords:	Protein-interacting nucleotide (PIN); Binary profile of patterns (BPP); Tri-nucleotide composition profile of patterns (TNCPP); SVM; Prediction; RNApin
Subjects:	Q Science > QR Microbiology
Depositing User:	Dr. K.P.S.Sengar
Date Deposited:	11 Jul 2015 04:57
Last Modified:	14 Jul 2015 04:57
URI:	http://crdd.osdd.net/open/id/eprint/1665

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