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

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    20150512111117282.pdf
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    Type
    Article
    Authors
    AbouEisha, Hassan M. cc
    Chikalov, Igor
    Moshkov, Mikhail cc
    Jankovic, Boris R.
    KAUST Department
    Applied Mathematics and Computational Science Program
    Computational Bioscience Research Center (CBRC)
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Office of the VP
    Date
    2015-10-08
    Online Publication Date
    2015-10-08
    Print Publication Date
    2015
    Permanent link to this record
    http://hdl.handle.net/10754/565912
    
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    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.
    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
    DOI
    10.12720/jait.6.2.71-74
    Additional Links
    http://www.jait.us/index.php?m=content&c=index&a=show&catid=165&id=881
    ae974a485f413a2113503eed53cd6c53
    10.12720/jait.6.2.71-74
    Scopus Count
    Collections
    Articles; Applied Mathematics and Computational Science Program; Computer Science Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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