Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence

Detalles Bibliográficos
Autores principales: Bogdan, Paul, Ivanov, Plamen Ch., Pequito, Sergio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131101/
https://www.ncbi.nlm.nih.gov/pubmed/35634141
http://dx.doi.org/10.3389/fphys.2022.917001
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author Bogdan, Paul
Ivanov, Plamen Ch.
Pequito, Sergio
author_facet Bogdan, Paul
Ivanov, Plamen Ch.
Pequito, Sergio
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spelling pubmed-91311012022-05-26 Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence Bogdan, Paul Ivanov, Plamen Ch. Pequito, Sergio Front Physiol Physiology Frontiers Media S.A. 2022-05-11 /pmc/articles/PMC9131101/ /pubmed/35634141 http://dx.doi.org/10.3389/fphys.2022.917001 Text en Copyright © 2022 Bogdan, Ivanov and Pequito. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Bogdan, Paul
Ivanov, Plamen Ch.
Pequito, Sergio
Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence
title Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence
title_full Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence
title_fullStr Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence
title_full_unstemmed Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence
title_short Editorial: Inference, Causality and Control in Networks of Dynamical Systems: Data Science and Modeling Perspectives to Network Physiology With Implications for Artificial Intelligence
title_sort editorial: inference, causality and control in networks of dynamical systems: data science and modeling perspectives to network physiology with implications for artificial intelligence
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131101/
https://www.ncbi.nlm.nih.gov/pubmed/35634141
http://dx.doi.org/10.3389/fphys.2022.917001
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