Computational analysis of noncoding RNAs

Noncoding RNAs have emerged as important key players in the cell. Understanding their surprisingly diverse range of functions is challenging for experimental and computational biology. Here, we review computational methods to analyze noncoding RNAs. The topics covered include basic and advanced tech...

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Main Authors: Washietl, Stefan, Will, Sebastian, Hendrix, David A., Goff, Loyal, Rinn, John L., Berger, Bonnie, Kellis, Manolis
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: John Wiley & Sons, Inc 2014
Online Access:http://hdl.handle.net/1721.1/87066
https://orcid.org/0000-0002-2724-7228
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author Washietl, Stefan
Will, Sebastian
Hendrix, David A.
Goff, Loyal
Rinn, John L.
Berger, Bonnie
Kellis, Manolis
author2 Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
author_facet Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Washietl, Stefan
Will, Sebastian
Hendrix, David A.
Goff, Loyal
Rinn, John L.
Berger, Bonnie
Kellis, Manolis
author_sort Washietl, Stefan
collection MIT
description Noncoding RNAs have emerged as important key players in the cell. Understanding their surprisingly diverse range of functions is challenging for experimental and computational biology. Here, we review computational methods to analyze noncoding RNAs. The topics covered include basic and advanced techniques to predict RNA structures, annotation of noncoding RNAs in genomic data, mining RNA-seq data for novel transcripts and prediction of transcript structures, computational aspects of microRNAs, and database resources.
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spelling mit-1721.1/870662022-09-29T11:27:00Z Computational analysis of noncoding RNAs Washietl, Stefan Will, Sebastian Hendrix, David A. Goff, Loyal Rinn, John L. Berger, Bonnie Kellis, Manolis Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Department of Mathematics Washietl, Stefan Will, Sebastian Hendrix, David A. Goff, Loyal Berger, Bonnie Kellis, Manolis Noncoding RNAs have emerged as important key players in the cell. Understanding their surprisingly diverse range of functions is challenging for experimental and computational biology. Here, we review computational methods to analyze noncoding RNAs. The topics covered include basic and advanced techniques to predict RNA structures, annotation of noncoding RNAs in genomic data, mining RNA-seq data for novel transcripts and prediction of transcript structures, computational aspects of microRNAs, and database resources. Austrian Science Fund (Schrodinger Fellowship J2966-B12) German Research Foundation (grant WI 3628/1-1 to SW) National Institutes of Health (U.S.) (NIH award 1RC1CA147187) 2014-05-21T18:32:50Z 2014-05-21T18:32:50Z 2012-11 Article http://purl.org/eprint/type/JournalArticle 17577004 http://hdl.handle.net/1721.1/87066 Washietl, Stefan, Sebastian Will, David A. Hendrix, Loyal A. Goff, John L. Rinn, Bonnie Berger, and Manolis Kellis. “Computational Analysis of Noncoding RNAs.” WIREs RNA 3, no. 6 (November 2012): 759–778. https://orcid.org/0000-0002-2724-7228 en_US http://dx.doi.org/10.1002/wrna.1134 Wiley Interdisciplinary Reviews: RNA Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf John Wiley & Sons, Inc PMC
spellingShingle Washietl, Stefan
Will, Sebastian
Hendrix, David A.
Goff, Loyal
Rinn, John L.
Berger, Bonnie
Kellis, Manolis
Computational analysis of noncoding RNAs
title Computational analysis of noncoding RNAs
title_full Computational analysis of noncoding RNAs
title_fullStr Computational analysis of noncoding RNAs
title_full_unstemmed Computational analysis of noncoding RNAs
title_short Computational analysis of noncoding RNAs
title_sort computational analysis of noncoding rnas
url http://hdl.handle.net/1721.1/87066
https://orcid.org/0000-0002-2724-7228
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