Title page for ETD etd-01162009-131115


Document Type Master's Dissertation
Author Zablocki, Fabien Bernard Roman
Email fabulon@gmail.com
URN etd-01162009-131115
Document Title Multiple sequence alignment using particle swarm optimization
Degree MSc
Department Computer Science
Supervisor
Advisor Name Title
Prof A P Engelbrecht Supervisor
Keywords
  • computational intelligence
  • particle swarm optimization
  • bioinformatics
  • artificial intelligence
  • multi sequence alignment
  • DNA
Date 2008-09-02
Availability unrestricted
Abstract

The recent advent of bioinformatics has given rise to the central and recurrent problem of optimally aligning biological sequences. Many techniques have been proposed in an attempt to solve this complex problem with varying degrees of success. This thesis investigates the application of a computational intelligence technique known as particle swarm optimization (PSO) to the multiple sequence alignment (MSA) problem. Firstly, the performance of the standard PSO (S-PSO) and its characteristics are fully analyzed. Secondly, a scalability study is conducted that aims at expanding the S-PSO’s application to complex MSAs, as well as studying the behaviour of three other kinds of PSOs on the same problems. Experimental results show that the PSO is efficient in solving the MSA problem and compares positively with well-known CLUSTAL X and T-COFFEE.

©University of Pretoria 2007

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