eprintid: 2049
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/20/49
datestamp: 2023-11-09 15:50:13
lastmod: 2023-11-09 15:50:13
status_changed: 2023-11-09 15:41:54
type: article
metadata_visibility: show
creators_name: Ahmad, M.
creators_name: Abdullah, A.
creators_name: Buragga, K.
title: A novel optimized approach for gene identification in DNA sequences
ispublished: pub
note: cited By 7
abstract: Gene identification is an open optimization problem in Bioinformatics. Exponential growth of biological data needs efficient methods for protein translation. Several approaches have been proposed that rely on indicator sequences, statistical and DSP techniques but yet an optimized procedure is required to add an optimal solution. A novel approach for gene identification has been proposed in this paper by employing discrete wavelet transforms for noise reduction in DNA sequences and a novel indicator sequence has been introduced for better signal mapping. Wavelet transforms greatly reduced the background noise and visible peaks of genie regions were found in power spectral estimation. The comparative analysis of proposed and existing approaches showed significant results for novel approach over prevailing solutions for datasets Yersinia pestis (ACCESSION: NC004088, 4000 bp) and gene F56F11.5 of C elegans (Accession number AF099922) from location 7021. The same significance was observed with four other experiments with real datasets taken from NCBI. © 2011 Asian Network for Scientific Information.
date: 2011
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-79958192152&doi=10.3923%2fjas.2011.806.814&partnerID=40&md5=a74378d2758d31be2381e864b1e276c8
id_number: 10.3923/jas.2011.806.814
full_text_status: none
publication: Journal of Applied Sciences
volume: 11
number: 5
pagerange: 806-814
refereed: TRUE
issn: 18125654
citation:   Ahmad, M. and Abdullah, A. and Buragga, K.  (2011) A novel optimized approach for gene identification in DNA sequences.  Journal of Applied Sciences, 11 (5).  pp. 806-814.  ISSN 18125654