基于蚁群系统的DNA序列设计排序方法评价

2008 Second Asia International Conference on Modelling & Simulation (AMS) Pub Date : 2008-05-13 DOI:10.1109/AMS.2008.37

T. Kurniawan, Noor Khafifah Khalid, Z. Ibrahim, M. Khalid, M. Middendorf

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引用次数: 17

摘要

在DNA计算中，DNA序列及其碱基对互补体之间的杂交是检索DNA序列中存储的信息和操作计算过程的关键。因此，许多工作都集中在设计可靠的分子计算的DNA序列上。本文提出用蚁群系统(ACS)来解决DNA序列设计问题。蚁群优化算法是对蚁群系统(Ant System, AS)的改进，基于蚁群中的信息素，利用一些agent来求解问题。DNA序列设计问题由四个节点建模，代表四个DNA碱基(A, T, C和G)，使用最近邻的热力学参数沃森-克里克碱基对DeltaGdeg37作为一个节点与其他节点之间的距离。为了获得最优集解，本文提出了7种ACS排序方法。对每种方法的性能进行比较和评估，以确定此应用程序的最佳排序方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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2008 Second Asia International Conference on Modelling & Simulation (AMS)

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