基于遗传算法的最大似然法构建系统发生树

Genetic algorithm-based maximum-likelihood method for regenerating phylogenetic tree

给出了一种基于遗传算法的最大似然法的建树方法,它是基于遗传算法的搜索最大似然树的启发式方法,将产生最优树和很多准最优树.这种技术在每次循环中只产生一棵树,并且在同代中没有重复的树出现.所以,结果树中含有最优树和很多准最优树,从而大大提高了搜索的效率.

The data from categorizing microbial molecule are always used to regenerating phylogenetic tree. It can intuitionisticly and scientificly show the relative relationship among different OTUs. NJ, ML and MP are the most popular methods . This paper presents a new method-genetic algorithm-based maximum-likelihood method. A heuristic approach to search for the maximum-likehood phylogenetic tree based on a genetic algorithm outputs the best tree as well as multiple alternative trees that are not significantly worse than the best one on the basis of the likehood criterion. A technique called steady-state reproduction without duplication is applied, in which only one new tree is generated in one cycle . Consequently, the resulting population consists of the best tree and alternative trees which have near-potimum likehood values.