@inproceedings{6d55e9181aa54df3a50c0dfca7bfdf3c,
title = "Phylogeny inference using a multi-objective evolutionary algorithm with indirect representation",
abstract = "The inference of phylogenetic trees is one of the most important tasks in computational biology. In this paper, we propose an extension to multi-objective evolutionary algorithms to address this problem. Here, we adopt an enhanced indirect encoding for a tree using the corresponding Pr{\"u}fer code represented in Newick format. The algorithm generates a range of non-dominated trees given alternative fitness measures such as statistical likelihood and maximum parsimony. A key feature of this approach is the preservation of the evolutionary hierarchy between species. Preliminary experimental results indicate that our model is capable of generating a set of optimized phylogenetic trees for given species data and the results are comparable with other techniques.",
author = "Hassan, \{Md Rafiul\} and Hossain, \{M. Maruf\} and Karmakar, \{C. K.\} and Michael Kirley",
year = "2008",
doi = "10.1007/978-3-540-89694-4\_5",
language = "English",
isbn = "3540896937",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "41--50",
booktitle = "Simulated Evolution and Learning - 7th International Conference, SEAL 2008, Proceedings",
note = "7th International Conference on Simulated Evolution and Learning, SEAL 2008 ; Conference date: 07-12-2008 Through 10-12-2008",
}