Genetic Algorithms for Constructing multiple Consensus Evolutionary Trees Using Bootstrapping and Maximum Likelihood Criterion

• Main Authors: Chih-Cheng Hsu, 許志成
• Other Authors: Pang-Yen Yin
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/d9kmj8

碩士 === 銘傳大學 === 資訊工程學系碩士班 === 92 === Phylogeny analysis is a process which derives the branching and mutations happened during the evolution. There are two main phylogeny analysis methods: distance-based and character-based; and there are two types of evolutionary trees: rooted and unrooted. This paper presents a maximum criterion-based phylogeny analysis method for unrooted trees. To increase the confidence level of the derived evolutionary trees, we use bootstrapping and consensus analysis in conjunction with a genetic algorithm for crossover and mutation between evolutionary trees. Multiple datasets of DNA sequences of species are generated using bootstrapping, the evolutionary trees are evaluated using these datasets and evolve to optimal trees by a genetic algorithm. The evolutionary trees are clustered based on similarity, a consensus tree is produced for each cluster. The experimental results manifest that the consensus trees produced by our system are highly similar to those validated by biologists.