Multi objective particle swarm optimization approach for DNA sequence design
Finding reliable and efficient DNA sequences is one of the most important tasks for successful DNA related experiments such as DNA computing. In DNA computing, perfect hybridization between a sequence and its base-pairing complement is important to retrieve the information stored in the sequences an...
Saved in:
Main Author: | |
---|---|
Format: | Thesis |
Published: |
2010
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/26864/ http://libraryopac.utm.my/client/en_AU/main/search/detailnonmodal/ent:$002f$002fSD_ILS$002f0$002fSD_ILS:770545/one?qu=Multi+objective+particle+swarm+optimization+approach+for+DNA+sequence+design |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Teknologi Malaysia |
id |
my.utm.26864 |
---|---|
record_format |
eprints |
spelling |
my.utm.268642017-08-14T01:02:53Z http://eprints.utm.my/id/eprint/26864/ Multi objective particle swarm optimization approach for DNA sequence design Mahabadi, Ali Arab Khazael TK Electrical engineering. Electronics Nuclear engineering Finding reliable and efficient DNA sequences is one of the most important tasks for successful DNA related experiments such as DNA computing. In DNA computing, perfect hybridization between a sequence and its base-pairing complement is important to retrieve the information stored in the sequences and to operate the computation processes. For this reason, the desired set of good DNA sequences, which have a stable duplex with their complement, are highly required. Various kinds of methods and strategies have been proposed to date to obtain good DNA sequences designed sequences using overlapping subsequences to enforce uniqueness. In this study a multi objective PSO is implemented to design DNA sequences based on Pareto optimality non-dominated solutions. The ability of the proposed approach is to detect the true Pareto optimal solutions and capture the true Pareto optimal front. By this method four objective functions, namely Hmeasure and similarity, hairpin, continuity were minimized simultaneously. The results were obtained from multi objective particle swarm optimization based on non dominated solutions are unique sequences which cannot be hybridized with other sequences in the set. 2010 Thesis NonPeerReviewed Mahabadi, Ali Arab Khazael (2010) Multi objective particle swarm optimization approach for DNA sequence design. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering. http://libraryopac.utm.my/client/en_AU/main/search/detailnonmodal/ent:$002f$002fSD_ILS$002f0$002fSD_ILS:770545/one?qu=Multi+objective+particle+swarm+optimization+approach+for+DNA+sequence+design |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
topic |
TK Electrical engineering. Electronics Nuclear engineering |
spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering Mahabadi, Ali Arab Khazael Multi objective particle swarm optimization approach for DNA sequence design |
description |
Finding reliable and efficient DNA sequences is one of the most important tasks for successful DNA related experiments such as DNA computing. In DNA computing, perfect hybridization between a sequence and its base-pairing complement is important to retrieve the information stored in the sequences and to operate the computation processes. For this reason, the desired set of good DNA sequences, which have a stable duplex with their complement, are highly required. Various kinds of methods and strategies have been proposed to date to obtain good DNA sequences designed sequences using overlapping subsequences to enforce uniqueness. In this study a multi objective PSO is implemented to design DNA sequences based on Pareto optimality non-dominated solutions. The ability of the proposed approach is to detect the true Pareto optimal solutions and capture the true Pareto optimal front. By this method four objective functions, namely Hmeasure and similarity, hairpin, continuity were minimized simultaneously. The results were obtained from multi objective particle swarm optimization based on non dominated solutions are unique sequences which cannot be hybridized with other sequences in the set. |
format |
Thesis |
author |
Mahabadi, Ali Arab Khazael |
author_facet |
Mahabadi, Ali Arab Khazael |
author_sort |
Mahabadi, Ali Arab Khazael |
title |
Multi objective particle swarm optimization approach for DNA sequence design |
title_short |
Multi objective particle swarm optimization approach for DNA sequence design |
title_full |
Multi objective particle swarm optimization approach for DNA sequence design |
title_fullStr |
Multi objective particle swarm optimization approach for DNA sequence design |
title_full_unstemmed |
Multi objective particle swarm optimization approach for DNA sequence design |
title_sort |
multi objective particle swarm optimization approach for dna sequence design |
publishDate |
2010 |
url |
http://eprints.utm.my/id/eprint/26864/ http://libraryopac.utm.my/client/en_AU/main/search/detailnonmodal/ent:$002f$002fSD_ILS$002f0$002fSD_ILS:770545/one?qu=Multi+objective+particle+swarm+optimization+approach+for+DNA+sequence+design |
_version_ |
1643647880859222016 |