Frequent Patterns Mining in DNA Sequence
As a common biological sequence, DNA sequences contain important information. The discovery of frequent patterns in DNA sequences can help to study the evolution, function and variation of genes. The findings are of great significance to genetic and mutation analysis, analysis of disease causes and...
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2019-01-01
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Online Access: | https://ieeexplore.ieee.org/document/8787813/ |
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doaj-5656fe8c52424a5881e2a2e3daa3d0062021-04-05T17:04:11ZengIEEEIEEE Access2169-35362019-01-01710840010841010.1109/ACCESS.2019.29330448787813Frequent Patterns Mining in DNA SequenceNa Deng0https://orcid.org/0000-0002-4413-2625Xu Chen1Desheng Li2Caiquan Xiong3School of Computer, Hubei University of Technology, Wuhan, ChinaSchool of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan, ChinaCollege of Mathematics, Physics and Information Engineering, Anhui University of Science and Technology, Huainan, ChinaSchool of Computer, Hubei University of Technology, Wuhan, ChinaAs a common biological sequence, DNA sequences contain important information. The discovery of frequent patterns in DNA sequences can help to study the evolution, function and variation of genes. The findings are of great significance to genetic and mutation analysis, analysis of disease causes and treatment of diseases. Traditional methods of frequent pattern discovery need to scan DNA sequences multiple times. To overcome this shortcoming, this article proposes a new method to discover frequent patterns from DNA sequences. This method is based on a two-level nested hash table data structure and set operation. All frequent patterns and their positions in DNA sequences can be found by scanning DNA sequences only once. Experimental results show that this method can correctly recognize all the frequent patterns in DNA sequences and their locations. The method can also be applied to discover frequent patterns in RNA, protein or other biological sequences.https://ieeexplore.ieee.org/document/8787813/Big databiological informationdata miningDNA sequencefrequent patternhash table |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Na Deng Xu Chen Desheng Li Caiquan Xiong |
spellingShingle |
Na Deng Xu Chen Desheng Li Caiquan Xiong Frequent Patterns Mining in DNA Sequence IEEE Access Big data biological information data mining DNA sequence frequent pattern hash table |
author_facet |
Na Deng Xu Chen Desheng Li Caiquan Xiong |
author_sort |
Na Deng |
title |
Frequent Patterns Mining in DNA Sequence |
title_short |
Frequent Patterns Mining in DNA Sequence |
title_full |
Frequent Patterns Mining in DNA Sequence |
title_fullStr |
Frequent Patterns Mining in DNA Sequence |
title_full_unstemmed |
Frequent Patterns Mining in DNA Sequence |
title_sort |
frequent patterns mining in dna sequence |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2019-01-01 |
description |
As a common biological sequence, DNA sequences contain important information. The discovery of frequent patterns in DNA sequences can help to study the evolution, function and variation of genes. The findings are of great significance to genetic and mutation analysis, analysis of disease causes and treatment of diseases. Traditional methods of frequent pattern discovery need to scan DNA sequences multiple times. To overcome this shortcoming, this article proposes a new method to discover frequent patterns from DNA sequences. This method is based on a two-level nested hash table data structure and set operation. All frequent patterns and their positions in DNA sequences can be found by scanning DNA sequences only once. Experimental results show that this method can correctly recognize all the frequent patterns in DNA sequences and their locations. The method can also be applied to discover frequent patterns in RNA, protein or other biological sequences. |
topic |
Big data biological information data mining DNA sequence frequent pattern hash table |
url |
https://ieeexplore.ieee.org/document/8787813/ |
work_keys_str_mv |
AT nadeng frequentpatternsminingindnasequence AT xuchen frequentpatternsminingindnasequence AT deshengli frequentpatternsminingindnasequence AT caiquanxiong frequentpatternsminingindnasequence |
_version_ |
1721540356273602560 |