Computational tools for genome-wide miRNA prediction and study

Handle URI:
http://hdl.handle.net/10754/334517
Title:
Computational tools for genome-wide miRNA prediction and study
Authors:
Malas, T.B.; Ravasi, Timothy ( 0000-0002-9950-465X )
Abstract:
MicroRNAs (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.
KAUST Department:
Biological and Environmental Sciences and Engineering (BESE) Division; Computational Bioscience Research Center (CBRC)
Citation:
B. Malas T (2012) Computational Tools for Genome-Wide miRNA Prediction and Study. TOBIOJ 5: 23-30. doi:10.2174/1874196701205010023.
Publisher:
Bentham Science Publishers Ltd.
Journal:
The Open Biology Journal
Issue Date:
2-Nov-2012
DOI:
10.2174/1874196701205010023
Type:
Article
ISSN:
18741967
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Biological and Environmental Sciences and Engineering (BESE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorMalas, T.B.en
dc.contributor.authorRavasi, Timothyen
dc.date.accessioned2014-11-11T14:28:02Z-
dc.date.available2014-11-11T14:28:02Z-
dc.date.issued2012-11-2en
dc.identifier.citationB. Malas T (2012) Computational Tools for Genome-Wide miRNA Prediction and Study. TOBIOJ 5: 23-30. doi:10.2174/1874196701205010023.en
dc.identifier.issn18741967en
dc.identifier.doi10.2174/1874196701205010023en
dc.identifier.urihttp://hdl.handle.net/10754/334517en
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.en
dc.language.isoenen
dc.publisherBentham Science Publishers Ltd.en
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.en
dc.rightsArchived with thanks to Open Biology Journalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/en
dc.subjectBiological databasesen
dc.subjectComputational prediction toolsen
dc.subjectGene regulationen
dc.subjectGenomicsen
dc.subjectMiRNAsen
dc.titleComputational tools for genome-wide miRNA prediction and studyen
dc.typeArticleen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.identifier.journalThe Open Biology Journalen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionDivision of Medical Genetics, Department of Medicine, University of California, San Diego, 9500 Gilman Drive, San Diego, CA 92093, United Statesen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorMalas, Tareq Majed Yasinen
kaust.authorRavasi, Timothyen
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