Evidence map›Paper›PMID 22582140›Full record

ArticleInternational journal for numerical methods in biomedical engineering2012

Biomolecular surface construction by PDE transform.

Qiong Zheng, Siyang Yang, Guo-Wei Wei

Abstract read
In one paragraph

Article in International journal for numerical methods in biomedical engineering, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Geometric algebra generation of molecular surfaces.Journal of the Royal Society, Interface · 2022
    Article
  2. The de Rham-Hodge Analysis and Modeling of Biomolecules.Bulletin of mathematical biology · 2020
    Article
  3. An efficient second-order poisson-boltzmann method.Journal of computational chemistry · 2019
    Article
  4. Article
  5. Article
  6. Object-oriented Persistent Homology.Journal of computational physics · 2016
    Article
  7. Multidimensional persistence in biomolecular data.Journal of computational chemistry · 2015
    Article
  8. Review
  9. Persistent homology analysis of protein structure, flexibility, and folding.International journal for numerical methods in biomedical engineering · 2014
    Article
  10. Article
  11. Multiscale Multiphysics and Multidomain Models I: Basic Theory.Journal of theoretical & computational chemistry · 2013
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Geometric modeling of subcellular structures, organelles, and multiprotein complexes.International journal for numerical methods in biomedical engineering · 2012
    Article
  18. Selective Extraction of Entangled Textures via Adaptive PDE Transform.International journal of biomedical imaging · 2012
    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

3 authors.

Qiong ZhengDepartment of Mathematics, Michigan State University, MI 48824, USA.
Siyang Yang
Guo-Wei Wei

Funding

Collaborative research: Geometric flow approach to implicit solvation modelingR01GM090208 · NIGMS · MICHIGAN STATE UNIVERSITY · PI WEI, GUOWEI · 2009 to 2014
$1.3M
NIGMS NIH HHS R01 GM090208NIGMS NIH HHS R01GM-090208
6 · The paper itself

Abstract

This work proposes a new framework for the surface generation based on the partial differential equation (PDE) transform. The PDE transform has recently been introduced as a general approach for the mode decomposition of images, signals, and data. It relies on the use of arbitrarily high-order PDEs to achieve the time-frequency localization, control the spectral distribution, and regulate the spatial resolution. The present work provides a new variational derivation of high-order PDE transforms. The fast Fourier transform is utilized to accomplish the PDE transform so as to avoid stringent stability constraints in solving high-order PDEs. As a consequence, the time integration of high-order PDEs can be done efficiently with the fast Fourier transform. The present approach is validated with a variety of test examples in two-dimensional and three-dimensional settings. We explore the impact of the PDE transform parameters, such as the PDE order and propagation time, on the quality of resulting surfaces. Additionally, we utilize a set of 10 proteins to compare the computational efficiency of the present surface generation method and a standard approach in Cartesian meshes. Moreover, we analyze the present method by examining some benchmark indicators of biomolecular surface, that is, surface area, surface-enclosed volume, solvation free energy, and surface electrostatic potential. A test set of 13 protein molecules is used in the present investigation. The electrostatic analysis is carried out via the Poisson-Boltzmann equation model. To further demonstrate the utility of the present PDE transform-based surface method, we solve the Poisson-Nernst-Planck equations with a PDE transform surface of a protein. Second-order convergence is observed for the electrostatic potential and concentrations. Finally, to test the capability and efficiency of the present PDE transform-based surface generation method, we apply it to the construction of an excessively large biomolecule, a virus surface capsid. Virus surface morphologies of different resolutions are attained by adjusting the propagation time. Therefore, the present PDE transform provides a multiresolution analysis in the surface visualization. Extensive numerical experiment and comparison with an established surface model indicate that the present PDE transform is a robust, stable, and efficient approach for biomolecular surface generation in Cartesian meshes.

Indexed as

Fourier AnalysisStatic ElectricitySurface PropertiesAlgorithmsCapsidComputer SimulationModels, MolecularProteinsProteinsmolecular surface generationPDE transformPoisson equationsolvation analysistotal variationvirus capsid

Identifiers

PMID22582140
PMCPMC3347862

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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.