A graph-based genetic algorithm for the multiple sequence alignment problem

Authors:
Heitor S. Lopes;Guilherme L. Moritz
Affiliations:
Bioinformatics Laboratory, CPGEI, Federal Technological University of Paraná, Curitiba, PR, Brazil;Bioinformatics Laboratory, CPGEI, Federal Technological University of Paraná, Curitiba, PR, Brazil
Venue:
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Year:
2006

Citing 1
Cited 2

Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms

A New Mutation Operator for the Elitism-Based Compact Genetic Algorithm

ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Multiple sequence alignment using reconfigurable computing

ARC'07 Proceedings of the 3rd international conference on Reconfigurable computing: architectures, tools and applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

We developed a new approach for the multiple sequence alignment problem based on Genetic Algorithms (GA). A new method to represent an alignment is proposed as a multidimensional oriented graph, which dramatically decreases the storage complexity. Details of the proposed GA are explained, including new structure-preserving genetic operators. A sensitivity analysis was done for adjusting running parameters of the GA. Performance of the proposed system was evaluated using a benchmark of hand-aligned sequences (Balibase). Overall, the results obtained are comparable or better to those obtained by a well-known software (Clustal). These results are very promising and suggest more efforts for further developments.