Implementation of ant colony system for DNA sequence optimization

DNA computation as a new paradigm has the computational power of molecules for information processing and many computational models have been proposed for solving mathematical problems in laboratory experiments. In order to achieve the correct computation, a set good of DNA sequences is crucial, bec...

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Main Authors: Ibrahim, Zuwairie, Kurniawan, Tri Basuki, Mohamed Saaid, Muhammad Faiz, Yahya, Azli
Format: Conference or Workshop Item
Published: 2009
Subjects:
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author Ibrahim, Zuwairie
Kurniawan, Tri Basuki
Mohamed Saaid, Muhammad Faiz
Yahya, Azli
author_facet Ibrahim, Zuwairie
Kurniawan, Tri Basuki
Mohamed Saaid, Muhammad Faiz
Yahya, Azli
author_sort Ibrahim, Zuwairie
collection ePrints
description DNA computation as a new paradigm has the computational power of molecules for information processing and many computational models have been proposed for solving mathematical problems in laboratory experiments. In order to achieve the correct computation, a set good of DNA sequences is crucial, because the code determines the way to process information on sequences in the experiments. Much works have focused on designing the DNA sequences to archive a reliable molecular computation and many algorithms have been proposed to obtain a set of good DNA sequences. In this paper, Ant Colony System (ACS) is proposed to solve the DNA sequence design problem. ACS used some ants to get their solutions based on the pheromone in their colony. A model is prepared which consists of four nodes representing four DNA bases. The results of the proposed approach are compared with the other methods such as Genetic Algorithm.
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spelling utm.eprints-152832020-08-30T08:46:18Z http://eprints.utm.my/15283/ Implementation of ant colony system for DNA sequence optimization Ibrahim, Zuwairie Kurniawan, Tri Basuki Mohamed Saaid, Muhammad Faiz Yahya, Azli TK Electrical engineering. Electronics Nuclear engineering DNA computation as a new paradigm has the computational power of molecules for information processing and many computational models have been proposed for solving mathematical problems in laboratory experiments. In order to achieve the correct computation, a set good of DNA sequences is crucial, because the code determines the way to process information on sequences in the experiments. Much works have focused on designing the DNA sequences to archive a reliable molecular computation and many algorithms have been proposed to obtain a set of good DNA sequences. In this paper, Ant Colony System (ACS) is proposed to solve the DNA sequence design problem. ACS used some ants to get their solutions based on the pheromone in their colony. A model is prepared which consists of four nodes representing four DNA bases. The results of the proposed approach are compared with the other methods such as Genetic Algorithm. 2009 Conference or Workshop Item PeerReviewed Ibrahim, Zuwairie and Kurniawan, Tri Basuki and Mohamed Saaid, Muhammad Faiz and Yahya, Azli (2009) Implementation of ant colony system for DNA sequence optimization. In: The 14th International Symposium on Artificial Life and Robotics (AROB 2009), 2009, Oita, Kitakyushu, Jepun. https://isarob.org/symhttp://dms.library.utm.my:8080/vital/access/manager/Repository/vital:105242posium/index.php?main_page=arob09
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ibrahim, Zuwairie
Kurniawan, Tri Basuki
Mohamed Saaid, Muhammad Faiz
Yahya, Azli
Implementation of ant colony system for DNA sequence optimization
title Implementation of ant colony system for DNA sequence optimization
title_full Implementation of ant colony system for DNA sequence optimization
title_fullStr Implementation of ant colony system for DNA sequence optimization
title_full_unstemmed Implementation of ant colony system for DNA sequence optimization
title_short Implementation of ant colony system for DNA sequence optimization
title_sort implementation of ant colony system for dna sequence optimization
topic TK Electrical engineering. Electronics Nuclear engineering
work_keys_str_mv AT ibrahimzuwairie implementationofantcolonysystemfordnasequenceoptimization
AT kurniawantribasuki implementationofantcolonysystemfordnasequenceoptimization
AT mohamedsaaidmuhammadfaiz implementationofantcolonysystemfordnasequenceoptimization
AT yahyaazli implementationofantcolonysystemfordnasequenceoptimization