By Topic

Evaluation of Ordering Methods for DNA Sequence Design Based on Ant Colony System

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Kurniawan, T.B. ; Centre for Artificial Intell. & Robot., Univ. Teknol. Malaysia, Skudai ; Khalid, N.K. ; Ibrahim, Z. ; Khalid, M.
more authors

Hybridization between a DNA sequence and its base-pairing complement is crucial in DNA computing to retrieve the information stored in DNA sequences and operate a computation processes. Therefore, much works have focused on designing the DNA sequences for a reliable molecular computation. In this paper, Ant Colony System (ACS) is proposed to solve the DNA sequence design problem. ACS, which is based on Ant Colony Optimization (ACO) is an improvement of Ant System (AS) that uses some agents to obtain the solutions based on the pheromone in their colony. The DNA sequence design problem is modeled by four nodes, representing four DNA bases (A, T, C, and G) using the nearest-neighbor thermodynamic parameter's Watson-Crick base-pair DeltaGdeg37 as distances between one node to other nodes. Seven ordering methods for ACS are presented in this study in order to obtain the best set solution. The performance of each of those methods are compared and evaluated to decide the best ordering method for this application.

Published in:

Modeling & Simulation, 2008. AICMS 08. Second Asia International Conference on

Date of Conference:

13-15 May 2008