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The SONATA data format for efficient description of large-scale network models

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 mod...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058350/
https://www.ncbi.nlm.nih.gov/pubmed/32092054
http://dx.doi.org/10.1371/journal.pcbi.1007696
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author 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
author_facet 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
author_sort Dai, Kael
collection PubMed
description 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.
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spelling pubmed-70583502020-03-12 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 PLoS Comput Biol Research Article 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. Public Library of Science 2020-02-24 /pmc/articles/PMC7058350/ /pubmed/32092054 http://dx.doi.org/10.1371/journal.pcbi.1007696 Text en https://creativecommons.org/publicdomain/zero/1.0/ 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 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
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
The SONATA data format for efficient description of large-scale network models
title The SONATA data format for efficient description of large-scale network models
title_full The SONATA data format for efficient description of large-scale network models
title_fullStr The SONATA data format for efficient description of large-scale network models
title_full_unstemmed The SONATA data format for efficient description of large-scale network models
title_short The SONATA data format for efficient description of large-scale network models
title_sort sonata data format for efficient description of large-scale network models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058350/
https://www.ncbi.nlm.nih.gov/pubmed/32092054
http://dx.doi.org/10.1371/journal.pcbi.1007696
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