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dc.contributor.authorSaçar, Müşerref Duygu
dc.contributor.authorAllmer, Jens
dc.date.accessioned2017-04-11T13:30:47Z
dc.date.available2017-04-11T13:30:47Z
dc.date.issued2013
dc.identifier.citationSaçar, M. D., and Allmer, J. (2013). Comparison of four Ab initio MicroRNA prediction tools. In P. Fernandes (Ed.). Paper presented at the BIOINFORMATICS 2013 proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms, Barcelona, Spain, 11-14 February (pp. 190-195). Setúbal, Portugal: SciTePress.en_US
dc.identifier.isbn9789898565358
dc.identifier.urihttp://hdl.handle.net/11147/5289
dc.descriptionInternational Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2013; Barcelona; Spain; 11 February 2013 through 14 February 2013en_US
dc.description.abstractMicroRNAs are small RNA sequences of 18-24 nucleotides in length, which serve as templates to drive post transcriptional gene silencing. The canonical microRNA pathway starts with transcription from DNA and is followed by processing by the Microprocessor complex, yielding a hairpin structure. This is then exported into the cytosol where it is processed by Dicer and next incorporated into the RNA induced silencing complex. All of these biogenesis steps add to the overall specificity of miRNA production and effect. Unfortunately, experimental detection of miRNAs is cumbersome and therefore computational tools are necessary. Homology-based miRNA prediction tools are limited by fast miRNA evolution and by the fact that they are template driven. Ab initio miRNA prediction methods have been proposed but they have not been analyzed competitively so that their relative performance is largely unknown. Here we implement the features proposed in four miRNA ab initio studies and evaluate them on two data sets. Using the features described in Bentwich 2008 leads to the highest accuracy but still does not provide enough confidence into the results to warrant experimental validation of all predictions in a larger genome like the human genome. Copyright © 2013 SCITEPRESS - Science and Technology Publications.en_US
dc.description.sponsorshipTurkish Academy of Sciencesen_US
dc.language.isoengen_US
dc.publisherSciTePressen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAb initioen_US
dc.subjectRNAen_US
dc.subjectMiRNAen_US
dc.subjectComparisonen_US
dc.subjectBioinformaticsen_US
dc.titleComparison of four Ab initio MicroRNA prediction toolsen_US
dc.typeconferenceObjecten_US
dc.contributor.authorIDTR114170en_US
dc.contributor.authorIDTR107974en_US
dc.contributor.institutionauthorSaçar, Müşerref Duygu
dc.contributor.institutionauthorAllmer, Jens
dc.relation.journalBIOINFORMATICS 2013 proceedings of the International Conference on Bioinformatics Models, Methods and Algorithmsen_US
dc.contributor.departmentİYTE, Fen Fakültesi, Moleküler Biyoloji ve Genetik Bölümüen_US
dc.identifier.startpage190en_US
dc.identifier.endpage195en_US
dc.identifier.wosWOS:000345686200026
dc.identifier.scopusSCOPUS:2-s2.0-84877947791
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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