Computational methods for ribosome profiling data analysis

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dc.contributor.author Kiniry, Stephen J.
dc.contributor.author Michel, Audrey M.
dc.contributor.author Baranov, Pavel V.
dc.date.accessioned 2019-12-18T11:25:46Z
dc.date.available 2019-12-18T11:25:46Z
dc.date.issued 2019-11-24
dc.identifier.citation Kiniry, S. J., Michel, A. M. and Baranov, P. V. (2019) 'Computational methods for ribosome profiling data analysis', Wiley Interdisciplinary Reviews RNA, e1577. doi: 10.1002/wrna.1577 en
dc.identifier.issn 1757-7004
dc.identifier.issn 2573-9468
dc.identifier.uri http://hdl.handle.net/10468/9435
dc.identifier.doi 10.1002/wrna.1577 en
dc.description.abstract Since the introduction of the ribosome profiling technique in 2009 its popularity has greatly increased. It is widely used for the comprehensive assessment of gene expression and for studying the mechanisms of regulation at the translational level. As the number of ribosome profiling datasets being produced continues to grow, so too does the need for reliable software that can provide answers to the biological questions it can address. This review describes the computational methods and tools that have been developed to analyze ribosome profiling data at the different stages of the process. It starts with initial routine processing of raw data and follows with more specific tasks such as the identification of translated open reading frames, differential gene expression analysis, or evaluation of local or global codon decoding rates. The review pinpoints challenges associated with each step and explains the ways in which they are currently addressed. In addition it provides a comprehensive, albeit incomplete, list of publicly available software applicable to each step, which may be a beneficial starting point to those unexposed to ribosome profiling analysis. The outline of current challenges in ribosome profiling data analysis may inspire computational biologists to search for novel, potentially superior, solutions that will improve and expand the bioinformatician's toolbox for ribosome profiling data analysis. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher John Wiley & Sons, Inc. en
dc.relation.uri https://onlinelibrary.wiley.com/doi/abs/10.1002/wrna.1577
dc.rights © 2019, Wiley Periodicals, Inc. All rights reserved. This is the peer reviewed version of the following article: Kiniry, S. J., Michel, A. M. and Baranov, P. V. (2019) 'Computational methods for ribosome profiling data analysis', Wiley Interdisciplinary Reviews RNA, e1577, doi: 10.1002/wrna.1577, which has been published in final form at https://doi.org/10.1002/wrna.1577 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. en
dc.subject mRNA translation en
dc.subject Protein synthesis en
dc.subject Ribosome profiling en
dc.subject Translatome en
dc.subject Ribo‐Seq en
dc.title Computational methods for ribosome profiling data analysis en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Pavel Baranov, Biochemistry and Cell Biology, University College Cork, Cork, Ireland. +353-21-490-3000 Email: p.baranov@ucc.ie en
dc.internal.availability Full text available en
dc.check.info Access to this article is restricted until 12 months after publication by request of the publisher. en
dc.check.date 2020-11-24
dc.date.updated 2019-12-18T10:10:49Z
dc.description.version Accepted Version en
dc.internal.rssid 500170918
dc.contributor.funder Wellcome Trust en
dc.contributor.funder Science Foundation Ireland en
dc.contributor.funder Health Research Board en
dc.description.status Peer reviewed en
dc.identifier.journaltitle Wiley Interdisciplinary Reviews RNA en
dc.internal.copyrightchecked Yes
dc.internal.licenseacceptance Yes en
dc.internal.IRISemailaddress p.baranov@ucc.ie en
dc.identifier.articleid e1577 en
dc.internal.bibliocheck In press. Check vol / issue / page range. Amend citation and copyright statement as necessary. en


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