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Computational Methods for MicroRNA Target Prediction
MicroRNAs (miRNAs) have been identified as one of the most important molecules that regulate gene expression in various organisms. miRNAs are short, 21–23 nucleotide-long, single stranded RNA molecules that bind to 3' untranslated regions (3' UTRs) of their target mRNAs. In general, they s...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4198924/ https://www.ncbi.nlm.nih.gov/pubmed/25153283 http://dx.doi.org/10.3390/genes5030671 |
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author | Ekimler, Semih Sahin, Kaniye |
author_facet | Ekimler, Semih Sahin, Kaniye |
author_sort | Ekimler, Semih |
collection | PubMed |
description | MicroRNAs (miRNAs) have been identified as one of the most important molecules that regulate gene expression in various organisms. miRNAs are short, 21–23 nucleotide-long, single stranded RNA molecules that bind to 3' untranslated regions (3' UTRs) of their target mRNAs. In general, they silence the expression of their target genes via degradation of the mRNA or by translational repression. The expression of miRNAs, on the other hand, also varies in different tissues based on their functions. It is significantly important to predict the targets of miRNAs by computational approaches to understand their effects on the regulation of gene expression. Various computational methods have been generated for miRNA target prediction but the resulting lists of candidate target genes from different algorithms often do not overlap. It is crucial to adjust the bioinformatics tools for more accurate predictions as it is equally important to validate the predicted target genes experimentally. |
format | Online Article Text |
id | pubmed-4198924 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-41989242014-10-16 Computational Methods for MicroRNA Target Prediction Ekimler, Semih Sahin, Kaniye Genes (Basel) Review MicroRNAs (miRNAs) have been identified as one of the most important molecules that regulate gene expression in various organisms. miRNAs are short, 21–23 nucleotide-long, single stranded RNA molecules that bind to 3' untranslated regions (3' UTRs) of their target mRNAs. In general, they silence the expression of their target genes via degradation of the mRNA or by translational repression. The expression of miRNAs, on the other hand, also varies in different tissues based on their functions. It is significantly important to predict the targets of miRNAs by computational approaches to understand their effects on the regulation of gene expression. Various computational methods have been generated for miRNA target prediction but the resulting lists of candidate target genes from different algorithms often do not overlap. It is crucial to adjust the bioinformatics tools for more accurate predictions as it is equally important to validate the predicted target genes experimentally. MDPI 2014-08-22 /pmc/articles/PMC4198924/ /pubmed/25153283 http://dx.doi.org/10.3390/genes5030671 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Review Ekimler, Semih Sahin, Kaniye Computational Methods for MicroRNA Target Prediction |
title | Computational Methods for MicroRNA Target Prediction |
title_full | Computational Methods for MicroRNA Target Prediction |
title_fullStr | Computational Methods for MicroRNA Target Prediction |
title_full_unstemmed | Computational Methods for MicroRNA Target Prediction |
title_short | Computational Methods for MicroRNA Target Prediction |
title_sort | computational methods for microrna target prediction |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4198924/ https://www.ncbi.nlm.nih.gov/pubmed/25153283 http://dx.doi.org/10.3390/genes5030671 |
work_keys_str_mv | AT ekimlersemih computationalmethodsformicrornatargetprediction AT sahinkaniye computationalmethodsformicrornatargetprediction |