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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...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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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. |
format | Online Article Text |
id | pubmed-7058350 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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