Analyzing and Comparing Omicron Lineage Variants Protein-Protein Interaction Network using Centrality Measure
Mamata Das, Selvakumar K., P.J.A. Alphonse

TL;DR
This study analyzes the protein-protein interaction network of Omicron variants using centrality measures to identify key proteins, revealing MAPT as the most influential protein in the network.
Contribution
It introduces a comprehensive network analysis of Omicron variants, identifying significant proteins and applying multiple centrality measures and clustering techniques for the first time.
Findings
MAPT protein is the most significant in Omicron PPIN
Eight key proteins were identified as potential drug targets
Network clustering revealed 18 distinct protein groups
Abstract
The Worldwide spread of the Omicron lineage variants has now been confirmed. It is crucial to understand the process of cellular life and to discover new drugs need to identify the important proteins in a protein interaction network (PPIN). PPINs are often represented by graphs in bioinformatics, which describe cell processes. There are some proteins that have significant influences on these tissues, and which play a crucial role in regulating them. The discovery of new drugs is aided by the study of significant proteins. These significant proteins can be found by reducing the graph and using graph analysis. Studies examining protein interactions in the Omicron lineage (B.1.1.529) and its variants (BA.5, BA.4, BA.3, BA.2, BA.1.1, BA.1) are not yet available. Studying Omicron has been intended to find a significant protein. 68 nodes represent 68 proteins and 52 edges represent the…
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