DNA sequence similarity detecting method based on Hurst indexes

A DNA sequence and detection method technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., to achieve the effect of simplifying the calculation complexity, concise method, and improving the degree of discrimination
CN101950326AInactive Publication Date: 2011-01-19CHONGQING UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
CHONGQING UNIV
Publication Date
2011-01-19
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention relates to the field of biological information processing, in particular to a DNA sequence similarity detecting method based on Hurst indexes, which can simultaneously detect the similarity of a plurality of DNA sequences, simplifies the computational complexity, improves the operational efficiency, and can increase the difference degree among analysis objects of nearer evolutionary distance. The method comprises the following steps: (1) acquiring DNA coding sequences of different species in the same function area as initial sequences; (2) carrying out digital conversion on the initial sequences acquired in the step (1) to acquire numerical sequences corresponding to the initial sequences; (3) analyzing each numerical sequence acquired in the step (2) by a R / S analysis method to acquire Hurst indexes of each numerical sequence; (4) constructing a distance matrix by utilizing the Hurst indexes acquired in the step (3); and (5) acquiring sequence similarity information from the distance matrix acquired in the step (4).
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Description

technical field

[0001] The invention relates to the field of biological information processing, in particular to a DNA sequence similarity detection method. Background technique

[0002] An important content of bioinformatics is sequence analysis. By analyzing the sequences of nucleic acids and proteins, their structural and functional information is obtained to understand the functions of nucleic acids and proteins in organisms and to study their evolutionary origins. The rapid expansion of sequence data in sequence databases has prompted researchers to conduct extensive research on sequence analysis methods.

[0003] Based on different sequence expression methods, researchers use a variety of algorithms to extract characteristic parameters that can effectively reflect sequence biological information from digital sequences, such as the largest eigenvalue and topological index of various matrices, and then construct a multidimensional vector corresponding to the analysis seq...

Claims

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