Individual modeling techniques are often applicable in limited spatial-temporal domains leading to gaps in our biological modeling capabilities. To bridge these gaps, new methodological solutions to integrate levels of resolution are necessary. Mesh models can represent spatial data across all size scales, furthermore, they can be used with various levels of simulation resolution. Thus mesh structures provide an ideal integrative platform for multi-scale modeling. In this work, we describe a workflow to convert structural datasets, such as those from electron microscopy or x-ray crystallography, into mesh models suitable for modeling. To ensure that resultant meshes are "compute quality" we employ a redesigned version of GAMer (Geometry-preserving Adaptive MeshER), a mesh generation tool that produces and refines high-quality simplex meshes. GAMer is available as a stand-alone package or it can be accessed as a plug-in to 3D-modeling software Blender. To improve the robustness of mesh generation, we have implemented automated detection and resolution of many common mesh defects. Drastic improvements in structural biology methods have lead to an abundance of structural datasets ranging from protein structures to sub-cellular images. The development of an integrative multi-scale meshing platform can yield important new biological insight into the effects of physiology and anatomy on function. These multi-scale models will provide new opportunities for drug discovery and have an impact on human health and longevity.

Investigating transport properties with multi-scale computable mesh models from heterogeneous structural datasets

253rd National Meeting (2017)

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