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MicroRNA gene prediction refers to the computational methods designed to identify loci in the genome from which mature microRNAs are likely to originate. The predictions of these methods are frequently obtained from the analysis of several sources of data, including multiple genome comparisons and transcription data (Transcriptome).
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Computational methods are a primary source of novel MicroRNA predictions. The limitations of purely experimental methods, which are usually unable to detect microRNAs with low-expression levels or which are only expressed in a small number of tissues or physiological conditions, illustrate the need of in silico approaches. Recent RNA sequencing techniques (RNA-seq) address some of these limitations, but the wealth of data that they produce requires extensive computational analyses. Conventional gene finding methods cannot be used because non-coding genes in general, and microRNA genes in particular,...
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References
Cappé O, Moulines E, Ryden T (2005) Inference in hidden Markov models, Springer series in statistics. Springer
Mendes ND, Freitas AT, Sagot MF (2009) Current tools for the identification of microRNA genes and their targets. Nucleic Acids Res 37(8):2419–2433
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Mendes, N.D. (2013). MicroRNA, Gene Prediction. In: Dubitzky, W., Wolkenhauer, O., Cho, KH., Yokota, H. (eds) Encyclopedia of Systems Biology. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9863-7_1361
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DOI: https://doi.org/10.1007/978-1-4419-9863-7_1361
Publisher Name: Springer, New York, NY
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Online ISBN: 978-1-4419-9863-7
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