Department of Mechanical and Aerospace Engineering, University of California, San Diego, La Jolla, California.
Department of Mechanical and Aerospace Engineering, University of California, San Diego, La Jolla, California.
Biophys J. 2020 Mar 10;118(5):1003-1008. doi: 10.1016/j.bpj.2019.11.3400. Epub 2020 Jan 22.
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.
成像方法的进步，如电子显微镜、断层扫描和其他模态，使细胞和细胞器几何形状的高分辨率重建成为可能。这些进展为使用这些几何形状进行生物物理和数学建模铺平了道路，一旦这些数据可以表示为几何网格，并且经过仔细条件处理，就可以对偏微分方程进行离散化和求解。在这项工作中，我们概述了一个天真用户接近Geometry-preserving Adaptive MeshER 软件版本 2 的步骤，这是一个用 C++编写的网格生成代码，旨在将结构数据集转换为逼真的几何网格，同时保持底层形状。我们展示了两个示例案例：1）根据电子断层扫描进行亚细胞尺度的网格生成，2）对来自 X 射线晶体学的蛋白质进行网格划分。我们进一步证明了由 Geometry-preserving Adaptive MeshER 软件生成的网格适用于数值方法。总的来说，这些库和工具简化了从结构生物学数据构建逼真几何网格的过程。
