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.
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2019-09-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-019-12342-y |