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Lattice Paths for Persistent Diagrams.

Moo K Chung1, Hernando Ombao2

  • 1University of Wisconsin, Madison, USA.

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
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This summary is machine-generated.

This study introduces a novel lattice path method for statistical inference on persistent diagrams. This approach reveals topological changes in COVID-19 virus spike proteins during conformational shifts.

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Area of Science:

  • Computational topology
  • Statistical inference
  • Structural bioinformatics

Background:

  • Persistent homology is a powerful tool for analyzing data shape.
  • Statistical inference on persistent diagrams remains a significant challenge.
  • Understanding protein conformational changes is crucial for drug development.

Purpose of the Study:

  • To develop a new statistical inference procedure for persistent diagrams.
  • To apply this method to analyze protein structures, specifically COVID-19 spike proteins.
  • To investigate topological changes during protein conformational transitions.

Main Methods:

  • Developed a novel lattice path representation for persistent diagrams.
  • Created an exact statistical inference procedure using combinatorial enumerations on lattice paths.
  • Applied the lattice path method to topological characterization of protein structures.

Main Results:

  • Successfully implemented a new statistical inference method for persistent diagrams.
  • Demonstrated the application of the lattice path method to protein structure analysis.
  • Identified significant topological changes in COVID-19 spike proteins during conformational changes.

Conclusions:

  • The lattice path method provides a viable approach for statistical inference in persistent homology.
  • Topological characterization using this method can reveal critical insights into protein dynamics.
  • This work contributes to understanding the structural behavior of viral proteins.