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摘要:
The novel coronavirus (SARS-COV-2) is generally referred to as Covid-19 virus has spread to 213 countries with nearly 7 million confirmed cases and nearly 400,000 deaths. Such major outbreaks demand classification and origin of the virus genomic sequence, for planning, containment, and treatment. Motivated by the above need, we report two alignment-free methods combing with CGR to perform clustering analysis and create a phylogenetic tree based on it. To each DNA sequence we associate a matrix then define distance between two DNA sequences to be the distance between their associated matrix. These methods are being used for phylogenetic analysis of coronavirus sequences. Our approach provides a powerful tool for analyzing and annotating genomes and their phylogenetic relationships. We also compare our tool to ClustalX algorithm which is one of the most popular alignment methods. Our alignment-free methods are shown to be capable of finding closest genetic relatives of coronaviruses.
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篇名 Similarity Studies of Corona Viruses through Chaos Game Representation
来源期刊 计算分子生物学(英文) 学科 医学
关键词 Covid-19 Chaos Game Representation Deoxyribonucleic Acid Phylogenetic Analysis Shannon Entropy
年,卷(期) 2020,(3) 所属期刊栏目
研究方向 页码范围 61-72
页数 12页 分类号 R37
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Covid-19
Chaos
Game
Representation
Deoxyribonucleic
Acid
Phylogenetic
Analysis
Shannon
Entropy
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研究分支
研究去脉
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期刊影响力
计算分子生物学(英文)
季刊
2165-3445
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
35
总下载数(次)
0
总被引数(次)
0
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