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Sequence similarity analysis between SARS-COV-2 and other viruses based on variant logic framework and topological entropy
4th International Conference on Information Systems and Computer Aided Education, ICISCAE 2021 ; : 2563-2567, 2021.
Article in English | Scopus | ID: covidwho-1566401
ABSTRACT
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) popular in just a few months the world, the present study found that the virus belongs to the β-coronavirus family. We study the sequence similarity, which can be coronavirus vaccine development and analysis provides a scientific help, including SARS-CoV-2 high similarity with Bat-CoV, SARS, etc. But the low accuracy of long time-consuming problems sequences analysis method. In this paper, the topological entropy of different combination dimensions of each sequence was calculated based on the Variant Logic Framework. the sequences of SARS CoV-2 and other categories of viruses were taken as input data. The sequence similarity matrix of mutual information among different sequences was obtained by calculating Euclidean distance. Finally, using a visualization diagram, generate the phylogenetic tree. The experimental results show that topology entropy is fast and effective for virus sequence processing and similarity analysis, which also provides a new idea for virus sequence research and traceability. © 2021 ACM.
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Full text: Available Collection: Databases of international organizations Database: Scopus Topics: Variants Language: English Journal: 4th International Conference on Information Systems and Computer Aided Education, ICISCAE 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Topics: Variants Language: English Journal: 4th International Conference on Information Systems and Computer Aided Education, ICISCAE 2021 Year: 2021 Document Type: Article