%0 Conference Paper
%A Tran, Ngoc Ha
%A Do, Duc Dong
%A Hoang, Xuan-Huan
%B 2013 International Conference on Computing, Management and Telecommunications (ComManTel)
%C HoChiMinh city
%D 2013
%F SisLab:136
%K Algorithm design and analysis;Ant colony optimization;Greedy algorithms;Heuristic algorithms;Proteins;Runtime;Vectors;Ant Colony Optimization;Local Search;Multiple Graph Alignment;Pheromone update rule;label
%P 386-391
%T An Efficient Ant Colony Optimization Algorithm for Multiple Graph Alignment
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/136/
%X The Multiple Graph Alignment (MGA) is a new method to analyze the structure of biological molecules. This method allows detect functional similarities in the structure of biological systems. This article introduces an ant colony optimization algorithm combined with local search for optimal align multi-graph analysis of protein structures. Experiment results showed that the new algorithm outperformed the other heuristic approach and existing evolutionary computing.