Evidence map›Paper›PMID 20169418›Full record

ArticleBulletin of mathematical biology2010

Differential geometry based multiscale models.

Guo-Wei Wei

Abstract read
In one paragraph

Article in Bulletin of mathematical biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Geometric algebra generation of molecular surfaces.Journal of the Royal Society, Interface · 2022
    Article
  6. EVOLUTIONARY DE RHAM-HODGE METHOD.Discrete and continuous dynamical systems. Series B · 2021
    Article
  7. Article
  8. Article
  9. A review of mathematical representations of biomolecular data.Physical chemistry chemical physics : PCCP · 2020
    Review
  10. MathDL: mathematical deep learning for D3R Grand Challenge 4.Journal of computer-aided molecular design · 2020
    Article
  11. DG-GL: Differential geometry-based geometric learning of molecular datasets.International journal for numerical methods in biomedical engineering · 2019
    Article
  12. Generative network complex (GNC) for drug discovery.Communications in information and systems · 2019
    Article
  13. Article
  14. Article
  15. Article
  16. Object-oriented Persistent Homology.Journal of computational physics · 2016
    Article
  17. Article
  18. Matched Interface and Boundary Method for Elasticity Interface Problems.Journal of computational and applied mathematics · 2015
    Article
  19. Article
  20. Multidimensional persistence in biomolecular data.Journal of computational chemistry · 2015
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Guo-Wei WeiDepartment of Mathematics, Michigan State University, East Lansing, MI 48824, USA. wei@math.msu.edu

Funding

Collaborative research: Geometric flow approach to implicit solvation modelingR01GM090208 · NIGMS · MICHIGAN STATE UNIVERSITY · PI WEI, GUOWEI · 2009 to 2014
$1.3M
Temperature-Modulated Bioluminescence TomographyR21CA127189 · NCI · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI WANG, GE · 2007 to 2008
$319k
NCI NIH HHS CA-127189NCI NIH HHS R21 CA127189NIGMS NIH HHS GM-090208NIGMS NIH HHS R01 GM090208
6 · The paper itself

Abstract

Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier-Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson-Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson-Nernst-Planck equations that are coupled to generalized Navier-Stokes equations for fluid dynamics, Newton's equation for molecular dynamics, and potential and surface driving geometric flows for the micro-macro interface. For excessively large aqueous macromolecular complexes in chemistry and biology, we further develop differential geometry based multiscale fluid-electro-elastic models to replace the expensive molecular dynamics description with an alternative elasticity formulation.

Indexed as

Computer SimulationModels, TheoreticalElastic ModulusIon ChannelsMacromolecular SubstancesMolecular Dynamics SimulationPoisson DistributionStatic ElectricityWaterIon ChannelsMacromolecular SubstancesWater

Identifiers

PMID20169418
PMCPMC2914853

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.