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: | , , , , , , , |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
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Materias: | |
Acceso en línea: | https://doaj.org/article/ca202084bd924cf29c6afd7e9e5166b7 |
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