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Support Vector Machine Classifier for Accurate Identification of piRNA

School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China
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Appl. Sci. 2018, 8(11), 2204; https://doi.org/10.3390/app8112204
Received: 26 September 2018 / Revised: 5 November 2018 / Accepted: 6 November 2018 / Published: 9 November 2018
(This article belongs to the Section Applied Biosciences and Bioengineering)
Piwi-interacting RNA (piRNA) is a newly identified class of small non-coding RNAs. It can combine with PIWI proteins to regulate the transcriptional gene silencing process, heterochromatin modifications, and to maintain germline and stem cell function in animals. To better understand the function of piRNA, it is imperative to improve the accuracy of identifying piRNAs. In this study, the sequence information included the single nucleotide composition, and 16 dinucleotides compositions, six physicochemical properties in RNA, the position specificities of nucleotides both in N-terminal and C-terminal, and the proportions of the similar peptide sequence of both N-terminal and C-terminal in positive and negative samples, which were used to construct the feature vector. Then, the F-Score was applied to choose an optimal single type of features. By combining these selected features, we achieved the best results on the jackknife and the 5-fold cross-validation running 10 times based on the support vector machine algorithm. Moreover, we further evaluated the stability and robustness of our new method. View Full-Text
Keywords: Piwi-interacting RNA; sequence information; feature extraction; feature selection; machine learning Piwi-interacting RNA; sequence information; feature extraction; feature selection; machine learning
MDPI and ACS Style

Li, T.; Gao, M.; Song, R.; Yin, Q.; Chen, Y. Support Vector Machine Classifier for Accurate Identification of piRNA. Appl. Sci. 2018, 8, 2204. https://doi.org/10.3390/app8112204

AMA Style

Li T, Gao M, Song R, Yin Q, Chen Y. Support Vector Machine Classifier for Accurate Identification of piRNA. Applied Sciences. 2018; 8(11):2204. https://doi.org/10.3390/app8112204

Chicago/Turabian Style

Li, Taoying; Gao, Mingyue; Song, Runyu; Yin, Qian; Chen, Yan. 2018. "Support Vector Machine Classifier for Accurate Identification of piRNA" Appl. Sci. 8, no. 11: 2204. https://doi.org/10.3390/app8112204

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