Citation Impact
Citing Papers
Innovative scattering analysis shows that hydrophobic disordered proteins are expanded in water
2017 StandoutScienceNobel
Geometric deep learning of RNA structure
2021 Science
Hallucinating symmetric protein assemblies
2022 StandoutScienceNobel
State-of-the-art in artificial neural network applications: A survey
2018 Standout
A review of uncertainty quantification in deep learning: Techniques, applications and challenges
2021 Standout
Structure-based protein design with deep learning
2021
LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales
2021 Standout
Discovery of archaeal fusexins homologous to eukaryotic HAP2/GCS1 gamete fusion proteins
2022 StandoutNobel
Ensemble Docking in Drug Discovery
2018
A guide to machine learning for biologists
2021
Machine learning in protein structure prediction
2021
Kohn-Sham Equations as Regularizer: Building Prior Knowledge into Machine-Learned Physics
2021
In silico methods for design of biological therapeutics
2017
An introduction to the maximum entropy approach and its application to inference problems in biology
2018
An Efficient Algorithm to Perform Local Concerted Movements of a Chain Molecule
2015
Accurate prediction of protein–nucleic acid complexes using RoseTTAFoldNA
2023 StandoutNobel
Pushing the frontiers of density functionals by solving the fractional electron problem
2021 StandoutScienceNobel
Glycoproteomics
2022 StandoutNobel
Consistent View of Polypeptide Chain Expansion in Chemical Denaturants from Multiple Experimental Methods
2016
Computer Simulation of Liquids
2017 Standout
Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data
2020 StandoutNobel
Ion-dependent protein–surface interactions from intrinsic solvent response
2021 StandoutNobel
Molecular Docking: Shifting Paradigms in Drug Discovery
2019 Standout
Machine learning and the physical sciences
2019
Physics-informed machine learning
2021 Standout
Computer-inspired quantum experiments
2020 StandoutNobel
Closing the Gap Between Modeling and Experiments in the Self-Assembly of Biomolecules at Interfaces and in Solution
2020
Markov State Models: From an Art to a Science
2018
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
2019
Improving the Efficiency of Ligand-Binding Protein Design with Molecular Dynamics Simulations
2019 StandoutNobel
Works of Simon Olsson being referenced
Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning
2019 Science
Combining experimental and simulation data of molecular processes via augmented Markov models
2017
Inference of Structure Ensembles of Flexible Biomolecules from Sparse, Averaged Data
2013
Machine Learning of Coarse-Grained Molecular Dynamics Force Fields
2019
Mechanistic Models of Chemical Exchange Induced Relaxation in Protein NMR
2016
PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure
2013
Bayesian inference of protein ensembles from SAXS data
2015