A suite to build, analyze and visualize circuits.
- Neurodamus - BBP Simulation Control application for NEURON.
- CoreNeuron — Optimised simulator engine for NEURON.
- Snap — Blue Brain Simulation and Neural network Analysis Productivity layer.
- BlueETL - Multiple simulations analysis tool.
- ConnectomeUtilities — Complex network representation and analysis layer.
- ConnectomeManipulator - A connectome manipulation framework for SONATA circuits .
- Functionalizer - Create a functional connectome from physical connections between cells.
- Brayns — Visualizer for large-scale and interactive ray-tracing of neurons.
- libsonata — C++ / Python reader for SONATA circuit files.
- BioExplorer - Extract and analyze scientific data for visualization and interactive exploration.
Useful links: GitHub repo, Documentation.
BBP Simulation Control application for NEURON
Neurodamus is a BBP Simulation Control application for the NEURON simulator. The Python implementation offers a comprehensive Python API for fine tunning of the simulation, defined by a configuration file in SONATA format.
Useful links: GitHub repo, Documentation.
Optimised simulator engine for NEURON
CoreNEURON is a compute engine for the NEURON simulator optimized for both memory usage and computational speed. Its goal is to simulate large cell networks with small memory footprint and optimal performance.
Useful links: GitHub repo, Documentation.
Blue Brain Simulation and Neural network Analysis Productivity layer (Blue Brain SNAP)
Blue Brain SNAP is a Python library for accessing BlueBrain circuit models represented in SONATA format.
Useful links: GitHub repo, Documentation. Core transformations: GitHub repo, Documentation.
Multiple simulations analysis tool
Useful links: GitHub repo
Complex network representation and analysis layer
It simplifies running topological analyses on detailed models of networks by providing a bridge between existing analyses and the model representation.
Useful links: GitHub repo
Connectome manipulation framework for SONATA circuits
The framework allows for rapid connectome manipulations of biophysically detailed network models in SONATA format, the standard for large-scale network models. Manipulations can be targeted to entire models, specific sub-networks, or even single neurons, ranging from insertion or removal of specific motifs to complete rewiring based on stochastic connectivity models at various levels of complexity.
Useful links: GitHub repo
Create a functional connectome from physical connections between cells
Functionalizer is a tool for filtering the output of a touch detector (the "touches") according to morphological models, given in in the form of recipe prescription as described in the SONATA extension.
Useful links: GitHub repo, Documentation.
Visualizer for large-scale and interactive ray-tracing of neurons
Brayns is a minimalistic visualizer that can perform ray-traced rendering of neurons. It provides an abstraction of the underlying rendering engines so that the best possible acceleration libraries can be used for the relevant hardware.
Useful links: GitHub repo, Documentation.
C++ / Python reader for SONATA circuit files
The Blue Brain BioExplorer is a tool for scientists to extract and analyze scientific data for visualization and interactive exploration
Exploration relies on building software that combines data integration, analysis and interactive visualization to build, modify and navigate through large scientific datasets. For this, Blue Brain built and open-sourced the Blue Brain BioExplorer. It was originally developed to answer key scientific questions related to the Coronavirus as a use case and to deliver a visualization tool. Today, the BioExplorer allows to reconstruct, visualize, explore, and describe in detail the structure and function of highly-detailed biological structures such as molecular systems, neurons, astrocytes, blood vessels, and more. You can see the first application of the BioExplorer in A Machine-Generated View of the Role of Blood Glucose Levels in the Severity of COVID-19 study.
Useful links: GitHub repo, Documentation.