Species taxonomy method based on diversity comparisons of distances among amino acids in protein sequences

Abstract

The invention brings forward a species taxonomy method based on diversity comparisons of distances among amino acids in protein sequences. The method comprises following steps: S10, numbering each amino acid of a protein sequence; S20, calculating the distance between every two adjacent proteins of the same kind in each protein sequence; S30, counting frequency of different distances between every two adjacent proteins of the same kind in each protein sequence; and S40, comparing statistical data in a pair-wise sequence manner, setting up distance matrixes and performing species taxonomy by calculating phylogeny trees in generating systems based on distance matrixes. The species taxonomy method based on diversity comparisons of distances among amino acids in protein sequences has following beneficial effects: differences among amino acid in sequences are shifted to be those among distances of amino acid so that space is saved and no gap is required; and the method is easy and helps to simplify calculation amount.

Description

technical field [0001] The invention belongs to the field of species identification, in particular to a method for classifying species by comparing protein sequences with amino acid distance polymorphisms. Background technique [0002] At present, according to the theory of evolution, if two protein sequences come from the same ancestor, there will be a certain degree of homology, and the closer the relative relationship, the higher the homology of the species, so it can be classified according to the sequence of amino acids in the protein sequence, and establish The phylogenetic tree of molecular evolution. At present, the Clustal algorithm proposed by Higgins and Sharp in 1988 is widely used. Firstly, multiple sequences are pairwise compared to construct a distance matrix to reflect the pairwise relationship between sequences, and then a phylogenetic tree is generated according to the distance matrix calculation. When two sequences are compared, the simplest case is to ig...

AI Technical Summary

Problems solved by technology

When comparing two sequences, the simplest case is to ignore gaps and only select the starting point for comparison, but this method has large errors and is difficult to reflect the real situation

At present, the most commonly used method is alignment alignment, that is, to align sequences of different lengths by inserting intervals, but there are many ways to insert intervals, which leads to the complexity of alignment and greatly increases the amount of calculation

Images