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dc.contributor.authorAbouEisha, Hassan M.
dc.contributor.authorChikalov, Igor
dc.contributor.authorMoshkov, Mikhail
dc.contributor.authorJankovic, Boris R.
dc.date.accessioned2015-08-12T08:47:19Z
dc.date.available2015-08-12T08:47:19Z
dc.date.issued2015-10-08
dc.identifier.citationHassan Abou Eisha, Igor Chikalov, Mikhail Moshkov, and Boris Jankovic, "A Simple Decision Rule for Recognition of Poly(A) Tail Signal Motifs in Human Genome," Vol. 6, No. 2, pp. 71-74, May, 2015. doi:10.12720/jait.6.2.71-74
dc.identifier.issn1798-2340
dc.identifier.doi10.12720/jait.6.2.71-74
dc.identifier.urihttp://hdl.handle.net/10754/565912
dc.description.abstractBackground is the numerous attempts were made to predict motifs in genomic sequences that correspond to poly (A) tail signals. Vast portion of this effort has been directed to a plethora of nonlinear classification methods. Even when such approaches yield good discriminant results, identifying dominant features of regulatory mechanisms nevertheless remains a challenge. In this work, we look at decision rules that may help identifying such features. Findings are we present a simple decision rule for classification of candidate poly (A) tail signal motifs in human genomic sequence obtained by evaluating features during the construction of gradient boosted trees. We found that values of a single feature based on the frequency of adenine in the genomic sequence surrounding candidate signal and the number of consecutive adenine molecules in a well-defined region immediately following the motif displays good discriminative potential in classification of poly (A) tail motifs for samples covered by the rule. Conclusions is the resulting simple rule can be used as an efficient filter in construction of more complex poly(A) tail motifs classification algorithms.
dc.language.isoen
dc.publisherEngineering and Technology Publishing
dc.relation.urlhttp://www.jait.us/index.php?m=content&c=index&a=show&catid=165&id=881
dc.rightsArchived with thanks to Journal of Advances in Information Technology
dc.subjectpoly (A) tails
dc.subjectdecision rules
dc.subjectgenomic sequences
dc.subjectmachine learning
dc.subjectclassification
dc.titleA Simple Decision Rule for Recognition of Poly(A) Tail Signal Motifs in Human Genome
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentOffice of the VP
dc.identifier.journalJournal of Advances in Information Technology
dc.eprint.versionPublisher's Version/PDF
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personAbouEisha, Hassan M.
kaust.personChikalov, Igor
kaust.personMoshkov, Mikhail
kaust.personJankovic, Boris R.
refterms.dateFOA2018-06-14T08:26:20Z
dc.date.published-online2015-10-08
dc.date.published-print2015


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