An Open-Source Mesh Generation Platform for Biophysical Modeling Using Realistic Cellular Geometries
An Open-Source Mesh Generation Platform for Biophysical Modeling Using Realistic Cellular Geometries
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DOI：
10.1016/j.bpj.2019.11.3400
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发表时间：
2020-03-10
影响因子：
3.4
通讯作者：
Rangamani, Padmini
中科院分区：
文献类型：
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作者：
Lee, Christopher T.;Laughlin, Justin G.;Rangamani, Padmini
电子显微镜、断层扫描和其他成像方法的进步使细胞和细胞器几何形状的高分辨率重建成为可能。一旦这些数据可以表示为几何网格，这些进步为使用这些几何结构进行生物物理和数学建模铺平了道路，当仔细调节时，可以实现偏微分方程的离散化和求解。在这项工作中，我们概述了一个天真的用户接近几何保持自适应网格软件版本2的步骤，网格生成代码编写的C++设计的结构数据集转换为现实的几何网格，同时保留底层的形状。我们提出两个示例情况：1）通过电子断层扫描在亚细胞尺度上生成网格，以及2）将蛋白质与来自X射线晶体学的结构网格化。我们进一步证明了几何保持自适应MeshER软件生成的网格适用于数值方法。这些库和工具集合一起简化了从结构生物学数据构建逼真几何网格的过程。
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 naive 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.