Design and Performance Evaluation of Hybrid Intelligent Systembased Algorithm for Multiple DNA Sequence Alignment
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Date
2011-10
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Addis Ababa University
Abstract
In this thesis work, a method to align multiple DNA sequences is designed. The proposed design
is an intelligent system based hybrid algorithm of two optimization algorithms: Genetic
Algorithm (GA) and Tabu Search (TS). GA phase is used to find new region of solution while
TS explores regions of solution not explored by GA. The designed hybrid system is implemented
using MATLAB. The TS part of the system is adapted so as to be processed by AccelDSP
Synthesis tool and implemented in VHDL (Very high speed integrated circuits Hardware
Description Language). The designed system is evaluated using benchmark methods
CLUSTALW and MAFFT (Multiple sequences Alignment using Fast Fourier Transform). The
system performs less than both the benchmarks. It performs less with percentage of matches
differing at most by 8.6 from CLUSTALW for 8 sequences. It also performs less with percentage
of matches differing at most by 4.25 from MAFFT for 16 sequences.
Key Words: Multiple DNA sequence alignment, Hybrid system, Genetic Algorithm, Tabu
Search and FPGA based TS.
Description
Keywords
Multiple DNA Sequence Alignment, Hybrid System, Genetic Algorithm, Tabu Search and FPGA Based TS