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dc.contributor.authorMalas, Tareq Majed Yasin
dc.contributor.authorRavasi, Timothy
dc.date.accessioned2014-11-11T14:28:02Z
dc.date.available2014-11-11T14:28:02Z
dc.date.issued2012-11-12
dc.identifier.citationB. Malas T (2012) Computational Tools for Genome-Wide miRNA Prediction and Study. TOBIOJ 5: 23-30. doi:10.2174/1874196701205010023.
dc.identifier.issn18741967
dc.identifier.doi10.2174/1874196701205010023
dc.identifier.urihttp://hdl.handle.net/10754/334517
dc.description.abstractMicroRNAs (miRNAs) are single-stranded non-coding RNA susually of 22 nucleotidesin length that play an important post-transcriptional regulation role in many organisms. MicroRNAs bind a seed sequence to the 3-untranslated region (UTR) region of the target messenger RNA (mRNA), inducing degradation or inhibition of translation and resulting in a reduction in the protein level. This regulatory mechanism is central to many biological processes and perturbation could lead to diseases such as cancer. Given the biological importance, of miRNAs, there is a great need to identify and study their targets and functions. However, miRNAs are very difficult to clone in the lab and this has hindered the identification of novel miRNAs. Next-generation sequencing coupled with new computational tools has recently evolved to help researchers efficiently identify large numbers of novel miRNAs. In this review, we describe recent miRNA prediction tools and discuss their priorities, advantages and disadvantages. Malas and Ravasi.
dc.language.isoen
dc.publisherBentham Science Publishers Ltd.
dc.rightsThis is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
dc.rightsArchived with thanks to Open Biology Journal
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/
dc.subjectBiological databases
dc.subjectComputational prediction tools
dc.subjectGene regulation
dc.subjectGenomics
dc.subjectMiRNAs
dc.titleComputational tools for genome-wide miRNA prediction and study
dc.typeArticle
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentBioscience Program
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer Science Program
dc.contributor.departmentIntegrative Systems Biology Lab
dc.identifier.journalThe Open Biology Journal
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionDivision of Medical Genetics, Department of Medicine, University of California, San Diego, 9500 Gilman Drive, San Diego, CA 92093, United States
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personMalas, Tareq Majed Yasin
kaust.personRavasi, Timothy
refterms.dateFOA2018-06-13T15:40:52Z
dc.date.published-online2012-11-12
dc.date.published-print2012-11-02


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This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
Except where otherwise noted, this item's license is described as This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.