Mature antibody immune response over SARS-CoV-2 as a pattern recognition with artificial immune system

A natural immune system has a remarkable ability to recognise self from nonself antigens in human body. The immune system has a natural ability to learn, recognise and respond accordingly to protect human body against viruses and diseases. B-cells produce detectable antibodies and immunoglobulins an...

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Bibliographic Details
Main Authors: Dhyani, Manita, Bordoloi, Dibyahash, Ghai, Anupriya Sharma
Format: Conference Proceeding
Language:English
Subjects:
Antibodies
Antigens
Artificial intelligence
Human body
Immune system
Immunoglobulins
Immunology
Lymphocytes
Machine learning
Pattern recognition
Viral diseases
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Summary:A natural immune system has a remarkable ability to recognise self from nonself antigens in human body. The immune system has a natural ability to learn, recognise and respond accordingly to protect human body against viruses and diseases. B-cells produce detectable antibodies and immunoglobulins and are responsible for humoral antibody immunity (IgM, IgG). Memory cells play an important role in this entire reactive process. With the help of these memory cells, the immune system recognises and responds immediately to the second entry of infection.I propose a supervised machine learning method (Immunos -R) to give an approach to build an immune response model to get an accurate antibody immunological response to SARS-CoV-2 without doing in-vitro laboratory studies.Accuracy rate for antibody immunological response (B lymphocytes cells subset) is 96.0% at fourth split and lowest at 8th split 68.0%
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0106084