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Machine learning for protein folding and dynamics
Frank Noé, Gianni De Fabritiis, Cecilia Clementi
Many aspects of the study of protein folding and dynamics have been affected by the recent advances in machine learning. Methods for the prediction of protein structures from their…
Generating valid Euclidean distance matrices
Moritz Hoffmann, Frank Noé
Generating point clouds, e.g., molecular structures, in arbitrary rotations, translations, and enumerations remains a challenging task. Meanwhile, neural networks utilizing symmetr…
Machine learning for molecular simulation
Frank Noé, Alexandre Tkatchenko, Klaus-Robert Müller +1
Machine learning (ML) is transforming all areas of science. The complex and time-consuming calculations in molecular simulations are particularly suitable for a machine learning re…
Special Topic: Markov Models of Molecular Kinetics
Frank Noé, Edina Rosta
The Journal of Chemical Physics (JCP) article collection on Markov Models of Molecular Kinetics (MMMK) features recent advances developing and using Markov State Models (MSMs) in a…
Equivariant Flows: sampling configurations for multi-body systems with symmetric energies
Jonas Köhler, Leon Klein, Frank Noé
Flows are exact-likelihood generative neural networks that transform samples from a simple prior distribution to the samples of the probability distribution of interest. Boltzmann…
Deep neural network solution of the electronic Schrödinger equation
Jan Hermann, Zeno Schätzle, Frank Noé
[New and updated results were published in Nature Chemistry, doi:10.1038/s41557-020-0544-y.] The electronic Schrödinger equation describes fundamental properties of molecules and m…
Hydrodynamic coupling for particle-based solvent-free membrane models
Mohsen Sadeghi, Frank Noé
The great challenge with biological membrane systems is the wide range of scales involved, from nanometers and picoseconds for individual lipids, to the micrometers and beyond mill…
Diffusion-influenced reaction rates in the presence of pair interactions
Manuel Dibak, Christoph Fröhner, Frank Noé +1
The kinetics of bimolecular reactions in solution depends, among other factors, on intermolecular forces such as steric repulsion or electrostatic interaction. Microscopically, a p…
Kernel methods for detecting coherent structures in dynamical data
Stefan Klus, Brooke E. Husic, Mattes Mollenhauer +1
We illustrate relationships between classical kernel-based dimensionality reduction techniques and eigendecompositions of empirical estimates of reproducing kernel Hilbert space (R…