Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun

Harun, Hazaruddin (2015) Linear-PSO with binary search algorithm for DNA Motif Discovery / Hazaruddin Harun. In: The Doctoral Research Abstracts. IPSis Biannual Publication, 7 (7). Institute of Graduate Studies, UiTM.

[img]
Preview
Text
ABS_HAZARUDDIN HARUN TDRA VOL 7 IGS 15.pdf

Download (1MB) | Preview

Abstract

Motif Discovery (MD) is the process of identifying meaningful patterns in DNA, RNA, or protein sequences. In the field of bioinformatics, a pattern is also known as a motif. Numerous algorithms had been developed for MD, but most of these were not designed to discover species specific motifs used in identifying a specifically selected species where the exact location of these motifs also needs to be identified. Evaluation of these algorithms showed that the results are unsatisfactory due to the lower validity and accuracy of these algorithms. At present, DNA sequencing analysis is the most utilised technique for species identification where patterns of DNA sequences are determined by comparing the sequence to comprehensive databases. However, several false and gap sequences had been identified to be present in these databases which lead to false identification. Therefore, this study addresses these problems by introducing a hybrid algorithm for MD. In this study, the MD is a process to discover all possible motifs that existed in DNA sequences whereas Motif Identification (MI) is a process to identify the correct motif that can represent a selected species. Particle Swarm Optimisation (PSO) was selected as the base algorithm that needs improvement and integration with other techniques. The Linear-PSO algorithm was the first version of improvement…

Item Type: Book Section
Creators:
CreatorsEmail
Harun, HazaruddinUNSPECIFIED
Subjects: L Education > LB Theory and practice of education > Higher Education > Dissertations, Academic. Preparation of theses > Malaysia
Divisions: Institut Pengajian Siswazah (IPSis) : Institute of Graduate Studies (IGS)
Series Name: IPSis Biannual Publication
Volume: 7
Number: 7
Item ID: 19220
Uncontrolled Keywords: Abstract; Abstract of thesis; Newsletter; Research information; Doctoral graduates; IPSis; IGS; UiTM; algorithm
Last Modified: 12 Jun 2018 06:53
Depositing User: Staf Pendigitalan 5
URI: http://ir.uitm.edu.my/id/eprint/19220

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year