Solving the problem of antibody grouping based on cross-inhibition index using hierarchical clustering methods

被引：0

作者：

Zelinskyi, Oleksandr ^{[1
]}

Horlatch, Vitaliy ^{[1
]}

Lebedin, Yuri ^{[2
]}

Paslavska, Yaryna ^{[1
]}

机构：

[1] Ivan Franko Natl Univ Lviv, 1 Univ St, UA-79000 Lvov, Ukraine

[2] Xema OY, Myllymaenkatu 21, Lappeenranta 53550, Finland

来源：

5TH INTERNATIONAL CONFERENCE ON INFORMATICS & DATA-DRIVEN MEDICINE, IDDM 2022 | 2022年 / 3302卷

关键词：

Hierarchical clustering; SARS-CoV-2; antibodies; viruses;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Due to increasing number of viral diseases (including Covid-19) rapid research with the purpose of their detection, prevention, and treatment is crucial. This article considers a problem of finding two optimal antibodies to any virus that is important for detection of disease and development of tests but not for creation of vaccine. It is worth noting that the target protein (nucleoprotein), described in this article, is the only generally established target for SARS-CoV-2 diagnostics, using antigen rapid tests or any other antigen detection tools. Possible ways of solving the aforementioned problem were described using hierarchical clustering algorithm with different linkage methods. Affirmative results of dividing antibodies into groups were achieved.

引用

页数：9

共 20 条

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