MolecularNodes 🧬🍝💻

About

MolecularNodes enables quick import and visualisation of structural biology data inside of Blender. Blender provides advanced industry-leading visualisation and animation technology, while MolecularNodes provides the interface that allows Blender to understand the unique data formats used in structural biology.

The add-on enables creating animations from static crystal structures, styling proteins and other molecules in a variety of highly customisable styles, importing and playing back molecular dynamics trajectories from a wide variety of sources, and even importing of EM density maps.

Examples

Procedural Animations

Different Protein Styles

Molecular Dynamics Trajectory Import

EM Density Map Import

EM Starfile Import

Installation

See the installation page of the documentation, for detailed instructions on how to install the add-on.

Getting Started

These tutorials are for earlier versions of the addon. There are some differences in design, but overall the workflow is the same. Watch through the videos to get an overview of how the addon works.

Contributing

If you would like to contribute to the project, please open an issue to discuss potential new features, or comment on an existing issue if you would like to help with fixing it. I welcome any and all potential PRs.

To contribute to the project, fork and clone the Molecular Nodes repo to your local machine. I recommend using VS Code and the Blender VS Code addon which streamlines the development process.

Once installed, you can use the Blender: Build and Start command with VS Code open in the addon directory, to start Blender with the addon built and installed. Any changes that are then made to the underlying addon code, can be quickly previewed inside of the running Blender by using the VS Code command Blender: Reload Addonds.

Once happy with your code, open a pull request to discuss and get it reviewed by others working on the project. Open a draft pull request early, or open an issue to discuss the scope and feasability of potential features.

Citation

A paper has not yet been published on the addon, but if you use it in your academic work you can site it from Zenodo:

Thanks

A massive thanks to the Blender Foundation which develops Blender as a free and open source program.

Buy Me a Coffee

If you'd like to say thank you, you can buy me a coffee (or 10!) as a thanks for developing the add-on. Many others have already down exactly that. You can also join our Blender.Science discord, where fellow science visualisation enthusiasts and experts hang out and help each other.