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Persistent topological Laplacian analysis of SARS-CoV-2 variants

Xiaoqi Wei1, Jiahui Chen1, Guo-Wei Wei1,2,3

  • 1Department of Mathematics, Michigan State University, MI 48824, USA.

Journal of Computational Biophysics and Chemistry
|October 13, 2023
PubMed
Summary

Persistent topological Laplacians (PTLs) offer enhanced analysis of protein structures compared to persistent homology. This new topological data analysis tool effectively models SARS-CoV-2 variant mutations and binding interactions.

Keywords:
Mutation and binding induced protein structural changesPersistent LaplacianPersistent sheaf LaplacianSpectral data analysisTopological data analysisTopological deep learning

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