Massive computational acceleration by using neural networks to emulate mechanism-based biological models

Mechanistic models provide valuable insights, but large-scale simulations are computationally expensive. Here, the authors show that it is possible to explore the dynamics of a mechanistic model over a large set of parameters by training an artificial neural network on a smaller set of simulations.

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Autores principales: Shangying Wang, Kai Fan, Nan Luo, Yangxiaolu Cao, Feilun Wu, Carolyn Zhang, Katherine A. Heller, Lingchong You
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2019
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Acceso en línea:https://doaj.org/article/ca202084bd924cf29c6afd7e9e5166b7
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spelling oai:doaj.org-article:ca202084bd924cf29c6afd7e9e5166b72021-12-02T15:35:55ZMassive computational acceleration by using neural networks to emulate mechanism-based biological models10.1038/s41467-019-12342-y2041-1723https://doaj.org/article/ca202084bd924cf29c6afd7e9e5166b72019-09-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-12342-yhttps://doaj.org/toc/2041-1723Mechanistic models provide valuable insights, but large-scale simulations are computationally expensive. Here, the authors show that it is possible to explore the dynamics of a mechanistic model over a large set of parameters by training an artificial neural network on a smaller set of simulations.Shangying WangKai FanNan LuoYangxiaolu CaoFeilun WuCarolyn ZhangKatherine A. HellerLingchong YouNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-9 (2019)
institution DOAJ
collection DOAJ
language EN
topic Science
Q
spellingShingle Science
Q
Shangying Wang
Kai Fan
Nan Luo
Yangxiaolu Cao
Feilun Wu
Carolyn Zhang
Katherine A. Heller
Lingchong You
Massive computational acceleration by using neural networks to emulate mechanism-based biological models
description Mechanistic models provide valuable insights, but large-scale simulations are computationally expensive. Here, the authors show that it is possible to explore the dynamics of a mechanistic model over a large set of parameters by training an artificial neural network on a smaller set of simulations.
format article
author Shangying Wang
Kai Fan
Nan Luo
Yangxiaolu Cao
Feilun Wu
Carolyn Zhang
Katherine A. Heller
Lingchong You
author_facet Shangying Wang
Kai Fan
Nan Luo
Yangxiaolu Cao
Feilun Wu
Carolyn Zhang
Katherine A. Heller
Lingchong You
author_sort Shangying Wang
title Massive computational acceleration by using neural networks to emulate mechanism-based biological models
title_short Massive computational acceleration by using neural networks to emulate mechanism-based biological models
title_full Massive computational acceleration by using neural networks to emulate mechanism-based biological models
title_fullStr Massive computational acceleration by using neural networks to emulate mechanism-based biological models
title_full_unstemmed Massive computational acceleration by using neural networks to emulate mechanism-based biological models
title_sort massive computational acceleration by using neural networks to emulate mechanism-based biological models
publisher Nature Portfolio
publishDate 2019
url https://doaj.org/article/ca202084bd924cf29c6afd7e9e5166b7
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AT carolynzhang massivecomputationalaccelerationbyusingneuralnetworkstoemulatemechanismbasedbiologicalmodels
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