Research On Establishing Phylogenetic Tree With Missing Data Based On Prior Decision Model

A phylogenetic tree is used to represent the evolutionary relationship among species,which is the important contents in life science,Morphological data is the foundation for construction of paleontologic tree.However,Paleontology morphology data often have missing information,rendered traditional phylogenetic tree construction algorithm invalid.This paper proposes a method of constructing missing data phylogenetic tree based on a priori decision model to solve this problem.The research contents of this paper are as follows:(1)In order to construct phylogenetic tree with missing morphological data,this paper proposes method of constructing phylogenetic tree based on priori decision model.Firstly,More complete data were employed to construct an initial phylogenetic tree;Then,attribute reduction strategies are applied to get the decision nodes,and the decision model are constructed based on the decision nodes;Finally,the position of the species with high proportion of missing data in the initial phylogenetic tree is determined by the constructed decision model,and the phylogenetic Tree is constructed using Species Grafting technology.The comprehensive experimental results show that when the proportion of morphological missing data of a single species is greater than 10%,the average species accuracy with the proposed method is about 10%higher than the Maximum Parsimony(MP).(2)The generation of attribute decision set in decision point is a problem of attribute combination optimization,This paper proposes a set of attribute decision set based on genetic algorithm.This method combines the number of attributes to be reduced and the classification of the combination category,and puts forward the unique coding method,the corresponding fitness function and the cross variation method.Which further improved the accuracy and stability of the grafted species in the phylogenetic tree.The experimental results show that the phylogenetic tree was constructed by this method is 3.4%higher than the simple heuristic method in the average accuracy of species.(3)In order to eliminate the parallel tree generated by multiple grafts,a method of parallel tree prediction based on weighted fit hierarchical clustering is proposed.Firstly,we use the least squares method to fit the attribute weight of the initial phylogenetic tree,and then weight the property of the system.Finally,we use the method of weighted fit hierarchical clustering to construct the subtree.The experimental results show that the method can predict the parallel tree,and finally get a phylogenetic tree without parallel tree.