Conveners
Tutorial on advanced sampling schemes to discover molecular mechanisms from MD simulations: Hands-on session
- Roberto Covino ()
- Hendrik Jung ()
Tutorial on advanced sampling schemes to discover molecular mechanisms from MD simulations: Hands-on session
- Hendrik Jung ()
- Roberto Covino ()
Tutorial on advanced sampling schemes to discover molecular mechanisms from MD simulations: Lecture on scientific applications
- Hendrik Jung ()
- Roberto Covino ()
Description
Exascale computing holds great opportunities for molecular dynamics (MD) simulations. However, to take full advantage of the new possibilities, we must learn how to focus computational power on the discovery of complex molecular mechanisms, and how to extract them from enormous amounts of data. Both aspects still rely heavily on human experts, which becomes a serious bottleneck when a large number of parallel simulations have to be orchestrated to take full advantage of the available computing power. Here, we use artificial intelligence (AI) both to guide the sampling and to extract the relevant mechanistic information. We combine advanced sampling schemes with statistical inference, artificial neural networks, and deep learning to discover molecular mechanisms from MD simulations. Our framework adaptively and autonomously initialises simulations and learns the sampled mechanism, and is thus suitable for massively parallel computing architectures. We propose practical solutions to make the neural networks interpretable, as illustrated in applications to molecular systems.
