Where we stand, where we are moving: Surveying computational techniques for identifying miRNA genes and uncovering their regulatory role

Handle URI:
http://hdl.handle.net/10754/566055
Title:
Where we stand, where we are moving: Surveying computational techniques for identifying miRNA genes and uncovering their regulatory role
Authors:
Kleftogiannis, Dimitrios A. ( 0000-0003-1086-821X ) ; Korfiati, Aigli; Theofilatos, Konstantinos A.; Likothanassis, Spiridon D.; Tsakalidis, Athanasios K.; Mavroudi, Seferina P.
Abstract:
Traditional biology was forced to restate some of its principles when the microRNA (miRNA) genes and their regulatory role were firstly discovered. Typically, miRNAs are small non-coding RNA molecules which have the ability to bind to the 3'untraslated region (UTR) of their mRNA target genes for cleavage or translational repression. Existing experimental techniques for their identification and the prediction of the target genes share some important limitations such as low coverage, time consuming experiments and high cost reagents. Hence, many computational methods have been proposed for these tasks to overcome these limitations. Recently, many researchers emphasized on the development of computational approaches to predict the participation of miRNA genes in regulatory networks and to analyze their transcription mechanisms. All these approaches have certain advantages and disadvantages which are going to be described in the present survey. Our work is differentiated from existing review papers by updating the methodologies list and emphasizing on the computational issues that arise from the miRNA data analysis. Furthermore, in the present survey, the various miRNA data analysis steps are treated as an integrated procedure whose aims and scope is to uncover the regulatory role and mechanisms of the miRNA genes. This integrated view of the miRNA data analysis steps may be extremely useful for all researchers even if they work on just a single step. © 2013 Elsevier Inc.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Elsevier BV
Journal:
Journal of Biomedical Informatics
Issue Date:
Jun-2013
DOI:
10.1016/j.jbi.2013.02.002
PubMed ID:
23501016
Type:
Article
ISSN:
15320464
Sponsors:
This research has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: Heracleitus II. Investing in knowledge society through the European Social Fund.
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorKleftogiannis, Dimitrios A.en
dc.contributor.authorKorfiati, Aiglien
dc.contributor.authorTheofilatos, Konstantinos A.en
dc.contributor.authorLikothanassis, Spiridon D.en
dc.contributor.authorTsakalidis, Athanasios K.en
dc.contributor.authorMavroudi, Seferina P.en
dc.date.accessioned2015-08-12T09:01:20Zen
dc.date.available2015-08-12T09:01:20Zen
dc.date.issued2013-06en
dc.identifier.issn15320464en
dc.identifier.pmid23501016en
dc.identifier.doi10.1016/j.jbi.2013.02.002en
dc.identifier.urihttp://hdl.handle.net/10754/566055en
dc.description.abstractTraditional biology was forced to restate some of its principles when the microRNA (miRNA) genes and their regulatory role were firstly discovered. Typically, miRNAs are small non-coding RNA molecules which have the ability to bind to the 3'untraslated region (UTR) of their mRNA target genes for cleavage or translational repression. Existing experimental techniques for their identification and the prediction of the target genes share some important limitations such as low coverage, time consuming experiments and high cost reagents. Hence, many computational methods have been proposed for these tasks to overcome these limitations. Recently, many researchers emphasized on the development of computational approaches to predict the participation of miRNA genes in regulatory networks and to analyze their transcription mechanisms. All these approaches have certain advantages and disadvantages which are going to be described in the present survey. Our work is differentiated from existing review papers by updating the methodologies list and emphasizing on the computational issues that arise from the miRNA data analysis. Furthermore, in the present survey, the various miRNA data analysis steps are treated as an integrated procedure whose aims and scope is to uncover the regulatory role and mechanisms of the miRNA genes. This integrated view of the miRNA data analysis steps may be extremely useful for all researchers even if they work on just a single step. © 2013 Elsevier Inc.en
dc.description.sponsorshipThis research has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: Heracleitus II. Investing in knowledge society through the European Social Fund.en
dc.publisherElsevier BVen
dc.subjectGene regulatory networksen
dc.subjectMachine learningen
dc.subjectMicroRNA genesen
dc.subjectMiRNA gene predictionen
dc.subjectMiRNA identificationen
dc.subjectMiRNA transcription mechanismen
dc.titleWhere we stand, where we are moving: Surveying computational techniques for identifying miRNA genes and uncovering their regulatory roleen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalJournal of Biomedical Informaticsen
dc.contributor.institutionDepartment of Computer Engineering and Informatics, School of Engineering, University of Patras, Greeceen
dc.contributor.institutionDepartment of Social Work, School of Sciences of Health and Care, Technological Educational Institute of Patras, Greeceen
kaust.authorKleftogiannis, Dimitrios A.en

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