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Genes 2016, 7(12), 113; doi:10.3390/genes7120113

A Review of Computational Methods for Finding Non-Coding RNA Genes

College of Computer and Information Sciences, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia
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Author to whom correspondence should be addressed.
Academic Editor: George A. Calin
Received: 30 August 2016 / Revised: 4 November 2016 / Accepted: 17 November 2016 / Published: 3 December 2016
(This article belongs to the Special Issue microRNAs and Other Non-Coding RNAs in Human Diseases)
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Abstract

Finding non-coding RNA (ncRNA) genes has emerged over the past few years as a cutting-edge trend in bioinformatics. There are numerous computational intelligence (CI) challenges in the annotation and interpretation of ncRNAs because it requires a domain-related expert knowledge in CI techniques. Moreover, there are many classes predicted yet not experimentally verified by researchers. Recently, researchers have applied many CI methods to predict the classes of ncRNAs. However, the diverse CI approaches lack a definitive classification framework to take advantage of past studies. A few review papers have attempted to summarize CI approaches, but focused on the particular methodological viewpoints. Accordingly, in this article, we summarize in greater detail than previously available, the CI techniques for finding ncRNAs genes. We differentiate from the existing bodies of research and discuss concisely the technical merits of various techniques. Lastly, we review the limitations of ncRNA gene-finding CI methods with a point-of-view towards the development of new computational tools. View Full-Text
Keywords: gene; DNA; non-coding RNA; micro RNA; computational intelligence; support vector machine; Bayesian networks; genetic algorithm; neural network; deep learning gene; DNA; non-coding RNA; micro RNA; computational intelligence; support vector machine; Bayesian networks; genetic algorithm; neural network; deep learning
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Abbas, Q.; Raza, S.M.; Biyabani, A.A.; Jaffar, M.A. A Review of Computational Methods for Finding Non-Coding RNA Genes. Genes 2016, 7, 113.

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