A Simple Decision Rule for Recognition of Poly(A) Tail Signal Motifs in Human Genome

Handle URI:
http://hdl.handle.net/10754/565912
Title:
A Simple Decision Rule for Recognition of Poly(A) Tail Signal Motifs in Human Genome
Authors:
AbouEisha, Hassan M. ( 0000-0003-4560-7175 ) ; Chikalov, Igor; Moshkov, Mikhail ( 0000-0003-0085-9483 ) ; Jankovic, Boris R.
Abstract:
Background 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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computational Bioscience Research Center (CBRC)
Citation:
Hassan 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
Publisher:
Engineering and Technology Publishing
Journal:
Journal of Advances in Information Technology
Issue Date:
12-May-2015
DOI:
10.12720/jait.6.2.71-74
Type:
Article
ISSN:
1798-2340
Additional Links:
http://www.jait.us/index.php?m=content&c=index&a=show&catid=165&id=881
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAbouEisha, Hassan M.en
dc.contributor.authorChikalov, Igoren
dc.contributor.authorMoshkov, Mikhailen
dc.contributor.authorJankovic, Boris R.en
dc.date.accessioned2015-08-12T08:47:19Zen
dc.date.available2015-08-12T08:47:19Zen
dc.date.issued2015-05-12en
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.6.2.71-74en
dc.identifier.issn1798-2340en
dc.identifier.doi10.12720/jait.6.2.71-74en
dc.identifier.urihttp://hdl.handle.net/10754/565912en
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.en
dc.language.isoenen
dc.publisherEngineering and Technology Publishingen
dc.relation.urlhttp://www.jait.us/index.php?m=content&c=index&a=show&catid=165&id=881en
dc.rightsArchived with thanks to Journal of Advances in Information Technologyen
dc.subjectpoly (A) tailsen
dc.subjectdecision rulesen
dc.subjectgenomic sequencesen
dc.subjectmachine learningen
dc.subjectclassificationen
dc.titleA Simple Decision Rule for Recognition of Poly(A) Tail Signal Motifs in Human Genomeen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.identifier.journalJournal of Advances in Information Technologyen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorAbouEisha, Hassan M.en
kaust.authorChikalov, Igoren
kaust.authorMoshkov, Mikhailen
kaust.authorJankovic, Boris R.en
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