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Mesh Analysis

Mesh Analysis

Mesh analysis is a valuable method for simplifying circuit analysis using mesh currents as key circuit variables. Unlike nodal analysis, which focuses on determining unknown voltages, mesh analysis applies Kirchhoff's voltage law (KVL) to find unknown currents within a circuit. This method is particularly convenient in reducing the number of simultaneous equations that need to be solved.
A fundamental concept in mesh analysis is the definition of meshes and mesh currents. A mesh is a closed...

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Updated: Dec 29, 2025

Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology

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Published on: April 18, 2018

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

Christopher T Lee¹, Justin G Laughlin¹, John B Moody²

¹Department of Mechanical and Aerospace Engineering, University of California, San Diego, La Jolla, California.

Biophysical Journal

|February 8, 2020

Summary

This study introduces Geometry-preserving Adaptive MeshER software v2, simplifying the creation of realistic geometric meshes from structural biology data. This tool aids biophysical modeling by converting imaging data into usable formats for simulations.

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Last Updated: Dec 29, 2025

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Area of Science:

Computational Biology
Structural Biology
Biophysics

Background:

High-resolution imaging techniques like electron microscopy and tomography generate detailed cellular and organelle geometries.
These geometric data require conversion into computational meshes for biophysical and mathematical modeling.
Meshing enables the discretization and solution of partial differential equations crucial for simulations.

Purpose of the Study:

To provide a guide for naïve users to generate geometric meshes using Geometry-preserving Adaptive MeshER software v2.
To demonstrate the software's capability in creating realistic meshes from diverse structural biology data.
To validate the suitability of generated meshes for numerical methods.

Main Methods:

Utilized Geometry-preserving Adaptive MeshER software v2, a C++ mesh generation tool.
Applied the software to electron tomography data for subcellular structures.
Used the software for meshing a protein structure obtained from x-ray crystallography.

Main Results:

Successfully generated realistic geometric meshes from both subcellular and protein structural data.
Demonstrated that the meshes preserve the underlying shapes of the biological structures.
Validated the usability of the generated meshes for numerical simulations.

Conclusions:

Geometry-preserving Adaptive MeshER software v2 simplifies the construction of geometric meshes from structural biology data.
The software facilitates the integration of imaging data into biophysical and mathematical modeling workflows.
This tool lowers the barrier for researchers to perform computational modeling on biological structures.