Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/5212
Title: Computational methods for ab initio detection of microRNAs
Authors: Allmer, Jens
Yousef, Malik
Allmer, Jens
Izmir Institute of Technology. Molecular Biology and Genetics
Keywords: Ab initio
Mature miRNA
Prediction accuracy
Prediction of miRNAs
Issue Date: 2012
Publisher: Frontiers Media S.A.
Source: Allmer, J. and Malik, Y. (2012). Computational methods for ab initio detection of microRNAs. Frontiers in Genetics, 3(OCT). doi:10.3389/fgene.2012.00209
Abstract: MicroRNAs are small RNA sequences of 18-24 nucleotides in length, which serve as templates to drive post-transcriptional gene silencing. The canonical microRNA pathway starts with transcription from DNA and is followed by processing via the microprocessor complex, yielding a hairpin structure. Which is then exported into the cytosol where it is processed by Dicer and then incorporated into the RNA-induced silencing complex. All of these biogenesis steps add to the overall specificity of miRNA production and effect. Unfortunately, their modes of action are just beginning to be elucidated and therefore computational prediction algorithms cannot model the process but are usually forced to employ machine learning approaches. This work focuses on ab initio prediction methods throughout; and therefore homology-based miRNA detection methods are not discussed. Current ab initio prediction algorithms, their ties to data mining, and their prediction accuracy are detailed.
URI: http://dx.doi.org/10.3389/fgene.2012.00209
http://hdl.handle.net/11147/5212
ISSN: 1664-8021
Appears in Collections:Molecular Biology and Genetics / Moleküler Biyoloji ve Genetik
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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