Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease

Deep learning (DL) can be used to automatically extract complex features from dynamic systems. Here, the authors combine high-content imaging, DL and mechanistic models to extract and explain drug-induced morphological changes in the growth of the fungus responsible for Asian soybean rust.

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Autores principales:	Henry Cavanagh, Andreas Mosbach, Gabriel Scalliet, Rob Lind, Robert G. Endres
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/62b07d36ecec49c6a79eaecd11d5e4d1
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spelling	oai:doaj.org-article:62b07d36ecec49c6a79eaecd11d5e4d12021-11-08T11:07:56ZPhysics-informed deep learning characterizes morphodynamics of Asian soybean rust disease10.1038/s41467-021-26577-12041-1723https://doaj.org/article/62b07d36ecec49c6a79eaecd11d5e4d12021-11-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-26577-1https://doaj.org/toc/2041-1723Deep learning (DL) can be used to automatically extract complex features from dynamic systems. Here, the authors combine high-content imaging, DL and mechanistic models to extract and explain drug-induced morphological changes in the growth of the fungus responsible for Asian soybean rust.Henry CavanaghAndreas MosbachGabriel ScallietRob LindRobert G. EndresNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Henry Cavanagh Andreas Mosbach Gabriel Scalliet Rob Lind Robert G. Endres Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease
description	Deep learning (DL) can be used to automatically extract complex features from dynamic systems. Here, the authors combine high-content imaging, DL and mechanistic models to extract and explain drug-induced morphological changes in the growth of the fungus responsible for Asian soybean rust.
format	article
author	Henry Cavanagh Andreas Mosbach Gabriel Scalliet Rob Lind Robert G. Endres
author_facet	Henry Cavanagh Andreas Mosbach Gabriel Scalliet Rob Lind Robert G. Endres
author_sort	Henry Cavanagh
title	Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease
title_short	Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease
title_full	Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease
title_fullStr	Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease
title_full_unstemmed	Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease
title_sort	physics-informed deep learning characterizes morphodynamics of asian soybean rust disease
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/62b07d36ecec49c6a79eaecd11d5e4d1
work_keys_str_mv	AT henrycavanagh physicsinformeddeeplearningcharacterizesmorphodynamicsofasiansoybeanrustdisease AT andreasmosbach physicsinformeddeeplearningcharacterizesmorphodynamicsofasiansoybeanrustdisease AT gabrielscalliet physicsinformeddeeplearningcharacterizesmorphodynamicsofasiansoybeanrustdisease AT roblind physicsinformeddeeplearningcharacterizesmorphodynamicsofasiansoybeanrustdisease AT robertgendres physicsinformeddeeplearningcharacterizesmorphodynamicsofasiansoybeanrustdisease
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Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease

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