Dai, K;
Hernando, J;
Billeh, YN;
Gratiy, SL;
Planas, J;
Davison, AP;
Dura-Bernal, S;
... Arkhipov, A; + view all
(2020)
The SONATA data format for efficient description of large-scale network models.
PLOS Computational Biology
, 16
(2)
, Article e1007696. 10.1371/journal.pcbi.1007696.
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Abstract
Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility.
| Type: | Article |
|---|---|
| Title: | The SONATA data format for efficient description of large-scale network models |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1371/journal.pcbi.1007696 |
| Publisher version: | https://doi.org/10.1371/journal.pcbi.1007696 |
| Language: | English |
| Additional information: | This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. |
| Keywords: | Neurons, Simulation and modeling, Network analysis, Neural networks, Biophysics, Biophysical simulations, Synapses, Neuronal morphology |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Neuro, Physiology and Pharmacology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10093154 |
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