Lars Andersen Bratholm
Lars Andersen Bratholm
Verified email at bristol.ac.uk
Title
Cited by
Cited by
Year
Training neural nets to learn reactive potential energy surfaces using interactive quantum chemistry in virtual reality
S Amabilino, LA Bratholm, SJ Bennie, AC Vaucher, M Reiher, ...
The Journal of Physical Chemistry A 123 (20), 4486-4499, 2019
312019
QML: A Python toolkit for quantum machine learning
AS Christensen, FA Faber, B Huang, LA Bratholm, A Tkatchenko, ...
URL https://github. com/qmlcode/qml, 2017
29*2017
FCHL revisited: Faster and more accurate quantum machine learning
AS Christensen, LA Bratholm, FA Faber, O Anatole von Lilienfeld
The Journal of Chemical Physics 152 (4), 044107, 2020
282020
Photutils: Photometry tools
L Bradley, B Sipocz, T Robitaille, E Tollerud, C Deil, Z Vinícius, K Barbary, ...
ascl, ascl: 1609.011, 2016
252016
Automated Fragmentation Polarizable Embedding Density Functional Theory (PE-DFT) Calculations of Nuclear Magnetic Resonance (NMR) Shielding Constants of Proteins with …
C Steinmann, LA Bratholm, JMH Olsen, J Kongsted
Journal of chemical theory and computation 13 (2), 525-536, 2017
112017
ProCS15: a DFT-based chemical shift predictor for backbone and Cβ atoms in proteins
AS Larsen, LA Bratholm, AS Christensen, M Channir, JH Jensen
PeerJ 3, e1344, 2015
112015
IMPRESSION–prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy
W Gerrard, LA Bratholm, MJ Packer, AJ Mulholland, DR Glowacki, ...
Chemical Science 11 (2), 508-515, 2020
92020
Bayesian inference of protein structure from chemical shift data
LA Bratholm
8*
Low dimensional representations along intrinsic reaction coordinates and molecular dynamics trajectories using interatomic distance matrices
SR Hare, LA Bratholm, DR Glowacki, BK Carpenter
Chemical science 10 (43), 9954-9968, 2019
72019
Sonifying stochastic walks on biomolecular energy landscapes
RE Arbon, AJ Jones, LA Bratholm, T Mitchell, DR Glowacki
arXiv preprint arXiv:1803.05805, 2018
52018
Protein structure refinement using a quantum mechanics-based chemical shielding predictor
LA Bratholm, JH Jensen
Chemical science 8 (3), 2061-2072, 2017
42017
GitHub: Calculate RMSD for two XYZ structures
JC Kromann, L Bratholm
32016
A community-powered search of machine learning strategy space to find NMR property prediction models
LA Bratholm, W Gerrard, B Anderson, S Bai, S Choi, L Dang, P Hanchar, ...
arXiv preprint arXiv:2008.05994, 2020
2020
Training atomic neural networks using fragment-based data generated in virtual reality
S Amabilino, LA Bratholm, SJ Bennie, MB O'Connor, DR Glowacki
arXiv preprint arXiv:2007.02824, 2020
2020
Protein Structure Validation and Refinement Using Chemical Shifts Derived from Quantum Mechanics
LA Bratholm
Department of Chemistry, Faculty of Science, University of Copenhagen, 2016
2016
Computational Assignment of Chemical Shifts for Protein Residues
LA Bratholm
arXiv preprint arXiv:1311.3186, 2013
2013
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Articles 1–16