Construction of Phylogenetic Tree using MEGA

被引:0
|
作者
Kaur, Amandeep [1 ]
Sharma, Ajay Shiv [2 ]
Singh, Jasbir [3 ]
机构
[1] Guru Nanak Dev Engn Coll, Dept Comp Sci, Ludhiana, Punjab, India
[2] Guru Nanak Dev Engn Coll, Dept Informat Technol, Ludhiana, Punjab, India
[3] Guru Nanak Dev Engn Coll, Dept MCA, Ludhiana, Punjab, India
关键词
DNA; RNA; UPGMA; MEGA;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Computers are used in every field and by all types of users including biologists. This has made biology more interesting and trendy. Bioinformatics is the composition of the computers, biology and chemistry. The very purpose of construction of the phylogeny is to identify the information of the past and describes the present similarity and dis-similarity of living organisms. This will enable to describe the universal tree in the simple way. The phylogeny construction primarily deals with grouping the living organisms based on their amount of similarity where the differentiation of similar genes originates from several kinds for rebuild tree of these kinds. It also helps to identify the closest relative of the family by grouping the biological entities based on their relationship with their ancestor. There are the various processes for phylogenetic tree construction but mainly two approaches are used for construction of trees: Algorithmic approach and Tree search approach. An algorithmic approach uses an algorithm to recreate tree from the data while the tree search approach constructs many trees, and to decide the best tree based on some basis. The distance base methods used for phylogenetic tree construction which are the most commonly used under algorithmic approach are UPGMA (Unweighted Pair Group Method with Arithmetic Mean) method and another is the NJ (Neighbor Joining) method. The distance based methods are used widely and with the help of clustering techniques, it can produce a single, strictly bifurcating tree. Literature survey suggests the efficiency of these methods is better than other processes. It improves the efficiency of work by using Tamura 3-parameter (Gamma) models. In this work, UPGMA and NJ methods are used for tree recreation among different viruses in the different mammals. The improved value is 0.015 which is better from the previous work which is 0.91 and it is the strong proof of result.
引用
收藏
页码:531 / 534
页数:4
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