Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/13330
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dc.titleA parallel approach to miRNA target prediction
dc.contributor.authorRAHUL RAJAN THADANI
dc.date.accessioned2010-04-08T10:32:05Z
dc.date.available2010-04-08T10:32:05Z
dc.date.issued2007-12-28
dc.identifier.citationRAHUL RAJAN THADANI (2007-12-28). A parallel approach to miRNA target prediction. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/13330
dc.description.abstractMicroRNAs (miRNAs) are endogenous, post-transcriptional regulators of gene expression. Averaging 22 nucleotides in length, they bind to target messenger RNAs in a sequence-specific manner, inducing endonucleolytic cleavage or transcript destabilization. The accurate prediction of a comprehensive set of mRNAs regulated by animal miRNAs remains an open problem. In particular, the prediction of targets that do not possess evolutionarily conserved complementarity to their miRNA regulators is not adequately addressed by current tools. I describe a novel animal miRNA target prediction algorithm, MicroTar, which is based on miRNA--target complementarity and thermodynamic data. The algorithm uses predicted free energies of unbound mRNA and putative mRNA--miRNA heterodimers, implicitly addressing the accessibility of the mRNA 3 untranslated region. Parallelization makes feasible the use of full-molecule energy computations. MicroTar does not rely on evolutionary conservation to discern functional targets and is able to predict both conserved and non-conserved targets.
dc.language.isoen
dc.subjectmicroRNA, miRNA, target prediction
dc.typeThesis
dc.contributor.departmentBIOLOGICAL SCIENCES
dc.contributor.supervisorTAMMI, MARTTI TAPANI
dc.description.degreeMaster's
dc.description.degreeconferredMASTER OF SCIENCE
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Master's Theses (Open)

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