Genomic Analysis using Higher Order Adaptive Exon Predictors

1Srinivasareddy Putluri, Nagesh Mantravadi, Md. Zia Ur Rahman

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Abstract:

In genomics, true identifying exon regions in deoxyribonucleic acid (DNA) sections are an important activity for the identification and development of disease medications. All exon identification techniques are based on three basic periodicity (TBP) properties of exons. The techniques of adaptive sign processing have been successful compared to various other methods. This paper uses the least mean fourth (LMF) algorithm also its signed variants that includes SRLMF, SLMF also SSLMF algorithms to develop multiple adaptive exon predictors (AEPs) with less computational complexity. Eventually, a performance evaluation is performed for different AEPs using various standard gene data sequences derived from National Biotechnology Information Centre (NBI) genomic sequence database, such as Sensitivity (Sn), Precision (Pr) and Specificity (Sp) measurements.

Keywords:

adaptive exon predictor, computational complexity, deoxyribonucleic acid, disease medications, exon, three base periodicity

Paper Details
Month5
Year2020
Volume24
IssueIssue 8
Pages7859-7867