Loading...
The SONATA data format for efficient description of large-scale network models.
Dai, Kael; Hernando, Juan; Billeh, Yazan N; Gratiy, Sergey L; Planas, Judit; Davison, Andrew P; Dura-Bernal, Salvador; Gleeson, Padraig; Devresse, Adrien; Dichter, Benjamin K; Gevaert, Michael; King, James G; Van Geit, Werner A H; Povolotsky, Arseny V; Muller, Eilif; Courcol, Jean-Denis; Arkhipov, Anton
Journal Title
PLoS computational biology
Keywords
Readers/Advisors
Journal Title
Term and Year
Publication Date
2020-02-24
Book Title
Publication Volume
16
Publication Issue
2
Publication Begin
e1007696
Publication End
Number of pages
Collections
Files
Loading...
file.pdf
Adobe PDF, 2.76 MB
Research Projects
Organizational Units
Journal Issue
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.
Citation
Dai K, Hernando J, Billeh YN, Gratiy SL, Planas J, Davison AP, Dura-Bernal S, Gleeson P, Devresse A, Dichter BK, Gevaert M, King JG, Van Geit WAH, Povolotsky AV, Muller E, Courcol JD, Arkhipov A. The SONATA data format for efficient description of large-scale network models. PLoS Comput Biol. 2020 Feb 24;16(2):e1007696. doi: 10.1371/journal.pcbi.1007696. PMID: 32092054; PMCID: PMC7058350.