Method and device for identifying repetitive regions in deoxyribonucleic acid (DNA) sequences

Abstract

The invention provides a method and device for identifying repetitive regions in deoxyribonucleic acid (DNA) sequences. The method comprises the steps of: identifying occurrence number of constructedn-item sequences in the DNA sequences; taking the n-item sequences with the occurrence number greater than a preset threshold as the repetitive regions and constructing a n-item sequence set of all the n-item sequences serving as the repetitive regions; and if the number of the n-item sequences in the n-item sequence set is not unique, constructing (n+1)-item sequences between two n-item sequencesin the n-item sequence set according to a preset rule. Compared with the prior art, the method provided by the embodiment of the invention has the advantages that only the constructed DNA subsequences are needed to be identified, so that identified objects are greatly reduced; the process of obtaining the repetitive regions can also be obtained by counting the occurrence number in the identification process, so that the identifying efficiency is further improved; and longer DNA subsequences are constructed from the repetitive regions through the preset rule with no need for firstly combiningthe repetitive regions with single bases and traversing the entire DNA sequence one by one, so that the identifying efficiency of the genomic repetitive regions can be greatly improved.

Description

technical field [0001] The invention relates to the technical field of systems biology, more specifically, to a method and a device for identifying repetitive regions in DNA sequences. Background technique [0002] As we all know, deoxyribonucleic acid (DNA) is a double-stranded molecule composed of deoxyribonucleotides, and the genetic information of organisms is always stored in related DNA sequences, which can form genetic instructions to guide biological development and vital functions. The DNA sequence consists of two linear strands coiled in a double helix structure, and each strand can be represented by a linear sequence of adenine (A), thymine (T), cytosine (C) or guanine (G). Additionally, the two strands in a DNA sequence obey the base pairing rules (A with T and C with G). Therefore, modern bioinformatics organizes DNA molecules into a string and stores it in a database for scientific research. With the development of bioinformatics and molecular biology experi...

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Problems solved by technology

In 2011, Zhou et al. proposed a genome (DNA) frequent pattern mining method based on the frequent subtree mining strategy. This method reduces the stored sequence according to the suffix tree structure, but the method intercepts two subsequences from the DNA sequence , compare the two subsequences, that is to say, this method needs to compare all the subsequences between two pairs, and count how many identical subsequences there are according to the comparison results, which is difficult to find Repeated sequences with a high number of occurrences in DNA sequences, and time-consuming

In 2013, Jiang et al. constructed frequent approximate patterns on the basis of introducing the concept of similarity, and proposed a frequent approximate pattern mining method SFAP, but the sequences mined by this method are not exactly the same, but similar, so not strictly a repeat region

In 2015, Mao et al. proposed the AMSMA method, which stores the genome (DNA) sequence information obtained by scanning the database in an association matrix for better time and space efficiency, but the row of the association matrix in this method Represents the identified DNA subsequence, and the number of columns has 4 columns, which are A, G, T and C, a total of 4 bases. By combining the DNA subsequence of each row with the bases of each column, you can Obtain an extended DNA subsequence, but there are too many candidate patterns in this method, resulting in long running time and low efficiency

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