DNA sequence similarity analysis method based on S-PCNN and Huffman encoding

Abstract

The present invention discloses a new desoxyribonucleic acid (DNA) sequence similarity analysis method by combining a simplified pulse coupled neural network (S-PCNN) model and Huffman encoding. The method comprises: firstly, carrying out Huffman encoding by taking triplet codons (A, G, C, T) as basic encoding units according to features of the S-PCNN model, wherein the encoding enables a DNA character sequence to be digitized and be suitable for the features, of the S-PCNN model, for extracting a DNA sequence; secondly, carrying out feature clustering on the encoded DNA sequence by using the S-PCNN model so as to obtain an oscillation time series (OTS); and finally, measuring the similarity of two sections of DNA sequences through an Euclidean distance of the OTS. According to the method of the present invention, the DNA sequence of a first exon of beta globulin frequently used by nine species is selected, experiments prove that the method of the present invention can effectively distinguish DNA similarity between different species, thereby reflecting good classification performance.

Description

technical field [0001] The invention belongs to the technical field of bioinformatics, and in particular relates to a DNA sequence similarity analysis method based on S-PCNN and Huffman coding. Background technique [0002] Deoxyribonucleic acid (DNA) is the main genetic material of organisms. It is composed of four bases: adenine (A), guanine (G), cytosine (C), and thymine (T). Each organism has its own unique base arrangement, and this arrangement and combination relationship stores the genetic information of the organism. With the development of human gene sequencing and protein sequencing technology, and the facilities of the genome project, the amount of data in biological sequence databases (DNA, RNA and protein sequences) has increased unprecedentedly, and the intelligent processing of its massive information has become an urgent need for biological researchers. need. [0003] The analysis of DNA sequences can help people decipher the information of genetic codes, h...

AI Technical Summary

Problems solved by technology

The earlier DNA similarity analysis method is to compare the two DNA sequences one by one. When the lengths of the two sequences are different, the comparison will be more difficult.

In recent years, the two-dimensional graphical representation of DNA sequences has become an important method for analyzing DNA sequences, but this series of methods will generate accumulated errors during the encoding process, which will eventually cause errors in similarity analysis

Since then, there has been an algorithm for mapping DNA sequences to a two-dimensional Cartesian coordinate system, and then performing DTW distance analysis similarity, but its discrimination against DNA sequences is not high

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