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演化德拉姆 - 霍奇方法。

EVOLUTIONARY DE RHAM-HODGE METHOD.

作者信息

Chen Jiahui, Zhao Rundong, Tong Yiying, Wei Guo-Wei

机构信息

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

Department of Computer Science and Engineering, Michigan State University, MI 48824, USA.

出版信息

Discrete Continuous Dyn Syst Ser B. 2021 Jul;26(7):3785-3821. doi: 10.3934/dcdsb.2020257.

DOI:10.3934/dcdsb.2020257
PMID:34675756
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8528240/
Abstract

The de Rham-Hodge theory is a landmark of the 20 Century's mathematics and has had a great impact on mathematics, physics, computer science, and engineering. This work introduces an evolutionary de Rham-Hodge method to provide a unified paradigm for the multiscale geometric and topological analysis of evolving manifolds constructed from a filtration, which induces a family of evolutionary de Rham complexes. While the present method can be easily applied to close manifolds, the emphasis is given to more challenging compact manifolds with 2-manifold boundaries, which require appropriate analysis and treatment of boundary conditions on differential forms to maintain proper topological properties. Three sets of unique evolutionary Hodge Laplacians are proposed to generate three sets of topology-preserving singular spectra, for which the multiplicities of zero eigenvalues correspond to exactly the persistent Betti numbers of dimensions 0, 1 and 2. Additionally, three sets of non-zero eigenvalues further reveal both topological persistence and geometric progression during the manifold evolution. Extensive numerical experiments are carried out via the discrete exterior calculus to demonstrate the potential of the proposed paradigm for data representation and shape analysis of both point cloud data and density maps. To demonstrate the utility of the proposed method, the application is considered to the protein B-factor predictions of a few challenging cases for which existing biophysical models break down.

摘要

德拉姆 - 霍奇理论是20世纪数学的一个里程碑,对数学、物理、计算机科学和工程学都产生了重大影响。这项工作引入了一种演化的德拉姆 - 霍奇方法,为从一个滤层构造的演化流形的多尺度几何和拓扑分析提供了一个统一的范式,该滤层诱导了一族演化的德拉姆复形。虽然目前的方法可以很容易地应用于闭流形,但重点是更具挑战性的具有二维流形边界的紧致流形,这需要对微分形式的边界条件进行适当的分析和处理,以保持适当的拓扑性质。提出了三组独特的演化霍奇拉普拉斯算子,以生成三组保持拓扑的奇异谱,其零特征值的重数恰好对应于0、1和2维的持久贝蒂数。此外,三组非零特征值进一步揭示了流形演化过程中的拓扑持久性和几何进展。通过离散外微积分进行了广泛的数值实验,以证明所提出的范式在点云数据和密度图的数据表示和形状分析方面的潜力。为了证明所提出方法的实用性,考虑将其应用于一些具有挑战性的案例的蛋白质B因子预测,而现有生物物理模型在这些案例中失效。

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本文引用的文献

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Evolutionary homology on coupled dynamical systems with applications to protein flexibility analysis.耦合动力系统的进化同源性及其在蛋白质灵活性分析中的应用
J Appl Comput Topol. 2020 Dec;4(4):481-507. doi: 10.1007/s41468-020-00057-9. Epub 2020 Jul 29.
2
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Bull Math Biol. 2020 Aug 8;82(8):108. doi: 10.1007/s11538-020-00783-2.
3
Persistent spectral graph.持续谱图。
Int J Numer Method Biomed Eng. 2020 Sep;36(9):e3376. doi: 10.1002/cnm.3376. Epub 2020 Aug 17.
4
Weighted persistent homology for biomolecular data analysis.生物分子数据分析的加权持续同调。
Sci Rep. 2020 Feb 7;10(1):2079. doi: 10.1038/s41598-019-55660-3.
5
MathDL: mathematical deep learning for D3R Grand Challenge 4.MathDL:用于 D3R 大挑战 4 的数学深度学习。
J Comput Aided Mol Des. 2020 Feb;34(2):131-147. doi: 10.1007/s10822-019-00237-5. Epub 2019 Nov 16.
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AGL-Score: Algebraic Graph Learning Score for Protein-Ligand Binding Scoring, Ranking, Docking, and Screening.AGL-Score:用于蛋白质-配体结合评分、排序、对接和筛选的代数图学习评分。
J Chem Inf Model. 2019 Jul 22;59(7):3291-3304. doi: 10.1021/acs.jcim.9b00334. Epub 2019 Jul 1.
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