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An Open-Source Mesh Generation Platform for Biophysical Modeling Using Realistic Cellular Geometries.

  • Author(s): Lee, Christopher T
  • Laughlin, Justin G
  • Moody, John B
  • Amaro, Rommie E
  • McCammon, J Andrew
  • Holst, Michael
  • Rangamani, Padmini
  • et al.

Published Web Location

https://doi.org/10.1016/j.bpj.2019.11.3400
No data is associated with this publication.
Abstract

Advances in imaging methods such as electron microscopy, tomography, and other modalities are enabling high-resolution reconstructions of cellular and organelle geometries. Such advances pave the way for using these geometries for biophysical and mathematical modeling once these data can be represented as a geometric mesh, which, when carefully conditioned, enables the discretization and solution of partial differential equations. In this work, we outline the steps for a naïve user to approach the Geometry-preserving Adaptive MeshER software version 2, a mesh generation code written in C++ designed to convert structural data sets to realistic geometric meshes while preserving the underlying shapes. We present two example cases: 1) mesh generation at the subcellular scale as informed by electron tomography and 2) meshing a protein with a structure from x-ray crystallography. We further demonstrate that the meshes generated by the Geometry-preserving Adaptive MeshER software are suitable for use with numerical methods. Together, this collection of libraries and tools simplifies the process of constructing realistic geometric meshes from structural biology data.

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