GAMer

GAMer generates geometry-preserving surface and tetrahedral meshes from high-resolution structural biology imaging data for discretizing and solving partial differential equations in biophysical models.

Key Features:

• Implementation: Implemented in C++ for converting structural biology data into geometric meshes.
• Geometry-preserving adaptive meshing: Preserves intricate cellular and subcellular geometries when generating surface meshes, including from noisy imaging data.
• Tetrahedral meshing via Tetgen: Integrates Tetgen to produce high-quality tetrahedral meshes suitable for finite element and reaction-diffusion simulations.
• Mesh conditioning: Performs conditioning to ensure shape preservation and numerical suitability for PDE discretization.
• Data source support: Generates meshes from electron microscopy, electron tomography, and x-ray crystallography-derived structures, including protein models.
• Scripting and visualization integration: Provides PyGAMer for Python-based scripted mesh generation and BlendGAMer for integration with Blender-based visualization workflows.

Scientific Applications:

• Subcellular-scale modeling: Generation of meshes from electron tomography for subcellular geometry representation in computational studies.
• Protein-structure meshing: Conversion of x-ray crystallographic protein structures into geometric meshes for molecular-scale simulations.
• Reaction–diffusion and finite element simulations: Production of meshes tailored for reaction–diffusion systems and finite element analyses that require precise geometric fidelity.
• PDE discretization for biophysical models: Transformation of structural datasets into meshes used for discretizing and solving partial differential equations in biophysical modeling.

Methodology:

Starting from acquired structural datasets, GAMer applies conditioning to preserve shape, generates surface meshes, and uses Tetgen for tetrahedralization to produce meshes suitable for numerical PDE discretization and solution.