Tools and Standards for Single-Cell Modelling in Neuroscience

Advancing tools and standards to unify biochemical and electrical modeling of neurons, improving interoperability, reproducibility, and model sharing across neuroscience and systems biology.

A representation of the brain with lines showing the connections between biochemical and electrical activity.

16 April 2025

Figure 1 (above) Biochemical and electrical brain activity.

Background

In 2024 we reported on a collaboration between Dr Sarah Keating (ARC) and Dr Padraig Gleeson (NPP), supported by the ARC Open Source Software Sustainability Fund and the Kavli Foundation, aimed at facilitating access to standardised modelling languages in computational biology. Their work focused on unifying APIs across different model formats to help build an integrated modelling and simulation workflow that captures both the biochemical and electrical activity of cells in the brain.

What We Did Next

With continued funding from the Kavli Foundation we worked to advance interoperability in computational neuroscience by bridging key modelling standards from the "COmputational Modeling in BIology NEtwork (COMBINE)", specifically SBML, SED-ML, and NeuroML. These standards span different biological domains and linking them is crucial for developing multiscale models of neuronal function.

To support this goal:

We carried out systematic testing of models across COMBINE-compliant simulators using the BioSimulators framework. This confirmed the ability to execute standardized simulation protocols (SED-ML) on models defined in both SBML and NeuroML, ensuring reproducibility and consistency across tools.
This included developing new workflows for cross-referencing and sharing models between BioModels (focused on biochemical systems) and Open Source Brain (focused on neural systems), improving model discoverability and reuse across domains.
Our team also played a key role in organizing and supporting HARMONY, COMBINE’s flagship hackathon. This event brought together developers and researchers to collaborate on cross-standard interoperability. Travel grants helped widen participation and promote inclusivity. Having representatives from BioSimulators, BioModels, and our own team together in one space proved invaluable.

“Having representatives from BioSimulators, BioModels, and our own team together in one space proved invaluable.

The Impact

These developments have significantly lowered the barriers for researchers in neuroscience and systems biology to build, share, and validate complex computational models. Key outcomes include:

Greater accessibility and expanded capabilities of the NeuroML toolchain for modeling neuronal dynamics
Enhanced reproducibility and confidence in multiscale simulations through BioSimulators
Increased model discoverability and reuse via new connections between BioModels and Open Source Brain

Together, these advances pave the way for more integrated, scalable modeling efforts—laying a strong foundation for breakthroughs in understanding brain function and tackling biomedical challenges using advanced computational approaches.

Next Steps

We plan to apply for further funding to continue building a unified workflow capable of modeling both the biochemical and electrical processes within the brain.