ArticleBulletin of mathematical biology2020
The de Rham-Hodge Analysis and Modeling of Biomolecules.
Article in Bulletin of mathematical biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Correlated clustering and projection for dimensionality reduction.Machine learning: science and technology · 2026Article
- Topological data analysis and topological deep learning beyond persistent homology: a review.Artificial intelligence review · 2026Article
- PERSISTENT SHEAF LAPLACIANS.Foundations of data science (Springfield, Mo.) · 2025Article
- Position: Topological Deep Learning is the New Frontier for Relational Learning.Proceedings of machine learning research · 2024Article
- Hodge Decomposition of Single-Cell RNA Velocity.Journal of chemical information and modeling · 2024Article
- Combinatorial and Hodge Laplacians: Similarities and Differences.SIAM review. Society for Industrial and Applied Mathematics · 2024Article
- Persistent Dirac for molecular representation.Scientific reports · 2023Article
- PERSISTENT PATH LAPLACIAN.Foundations of data science (Springfield, Mo.) · 2023Article
- Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2.Chemical reviews · 2022Review
- Hodge theory-based biomolecular data analysis.Scientific reports · 2022Article
- Biomolecular Topology: Modelling and Analysis.Acta mathematica Sinica, English series · 2022Article
- EVOLUTIONARY DE RHAM-HODGE METHOD.Discrete and continuous dynamical systems. Series B · 2021Article
- HERMES: PERSISTENT SPECTRAL GRAPH SOFTWARE.Foundations of data science (Springfield, Mo.) · 2021Article
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5 authors.
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Abstract
Biological macromolecules have intricate structures that underpin their biological functions. Understanding their structure-function relationships remains a challenge due to their structural complexity and functional variability. Although de Rham-Hodge theory, a landmark of twentieth-century mathematics, has had a tremendous impact on mathematics and physics, it has not been devised for macromolecular modeling and analysis. In this work, we introduce de Rham-Hodge theory as a unified paradigm for analyzing the geometry, topology, flexibility, and Hodge mode analysis of biological macromolecules. Geometric characteristics and topological invariants are obtained either from the Helmholtz-Hodge decomposition of the scalar, vector, and/or tensor fields of a macromolecule or from the spectral analysis of various Laplace-de Rham operators defined on the molecular manifolds. We propose Laplace-de Rham spectral-based models for predicting macromolecular flexibility. We further construct a Laplace-de Rham-Helfrich operator for revealing cryo-EM natural frequencies. Extensive experiments are carried out to demonstrate that the proposed de Rham-Hodge paradigm is one of the most versatile tools for the multiscale modeling and analysis of biological macromolecules and subcellular organelles. Accurate, reliable, and topological structure-preserving algorithms for implementing discrete exterior calculus (DEC) have been developed to facilitate the aforementioned modeling and analysis of biological macromolecules. The proposed de Rham-Hodge paradigm has potential applications to subcellular organelles and the structure construction from medium- or low-resolution cryo-EM maps, and functional predictions from massive biomolecular datasets.
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