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Lattice Paths for Persistent Diagrams.

ABSTRACT: Persistent homology has undergone significant development in recent years. However, one outstanding challenge is to build a coherent statistical inference procedure on persistent diagrams. In this paper, we first present a new lattice path representation for persistent diagrams. We then develop a new exact statistical inference procedure for lattice paths via combinatorial enumerations. The lattice path method is applied to the topological characterization of the protein structures of the COVID-19 virus. We demonstrate that there are topological changes during the conformational change of spike proteins.

SUBMITTER: Chung MK

PROVIDER: S-EPMC8730383 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Lattice Paths for Persistent Diagrams.

Chung Moo K MK Ombao Hernando H

Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data : 4th International Workshop, iMIMIC 2021, and 1st International Workshop, TDA4MedicalData 2021, He... 20210921

Persistent homology has undergone significant development in recent years. However, one outstanding challenge is to build a coherent statistical inference procedure on persistent diagrams. In this paper, we first present a new lattice path representation for persistent diagrams. We then develop a new exact statistical inference procedure for lattice paths via combinatorial enumerations. The lattice path method is applied to the topological characterization of the protein structures of the COVID- ...[more]

PMID: 34993529

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Dataset Information

Lattice Paths for Persistent Diagrams.

Publications

Lattice Paths for Persistent Diagrams.

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