A new phylogenetic tree construction method from a given set of objects (proteins, species, etc.) is presented. As an extension of ant colony optimization, this method proposes an adaptive heuristic phylogenetic clustering algorithm based on a digraph to find a tree-like structure that defines certain ancestral relationships between the given objects. In our method, the given objects are clustered by the ant colony, and these clusters are used to construct phylogenetic trees progressively. In the end of the algorithm, these phylogenetic trees are optimized by the ant colony to get the fittest to the given objects. Our phylogenetic tree constructing method is tested to compare its results with that of the GA method. Experimental results show that our algorithm is easier to implement and more efficient. It can convergence faster and obtain higher quality results than GA.
['Ling Qin', 'Jianli Luo', 'Zhimin Chen', 'Jing Guo', 'Ling Chen', 'Yi Pan']
Phelogenetic Tree Construction using Self adaptive Ant Colony Algorithm