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Wouter Boomsma
Wouter Boomsma
Professor, Department of Computer Science, University of Copenhagen
Verifierad e-postadress på di.ku.dk
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3d steerable cnns: Learning rotationally equivariant features in volumetric data
M Weiler, M Geiger, M Welling, W Boomsma, TS Cohen
Advances in Neural information processing systems 31, 2018
5862018
Ancient biomolecules from deep ice cores reveal a forested southern Greenland
E Willerslev, E Cappellini, W Boomsma, R Nielsen, MB Hebsgaard, ...
Science 317 (5834), 111-114, 2007
5602007
Statistical assignment of DNA sequences using Bayesian phylogenetics
K Munch, W Boomsma, JP Huelsenbeck, E Willerslev, R Nielsen
Systematic biology 57 (5), 750-757, 2008
2212008
A generative, probabilistic model of local protein structure
W Boomsma, KV Mardia, CC Taylor, J Ferkinghoff-Borg, A Krogh, ...
Proceedings of the National Academy of Sciences 105 (26), 8932-8937, 2008
2102008
Combining experiments and simulations using the maximum entropy principle
W Boomsma, J Ferkinghoff-Borg, K Lindorff-Larsen
PLoS computational biology 10 (2), e1003406, 2014
2022014
Learning meaningful representations of protein sequences
NS Detlefsen, S Hauberg, W Boomsma
Nature communications 13 (1), 1914, 2022
1412022
Comparing molecular dynamics force fields in the essential subspace
F Martín-García, E Papaleo, P Gomez-Puertas, W Boomsma, ...
PLoS One 10 (3), e0121114, 2015
1172015
Structure of a functional amyloid protein subunit computed using sequence variation
P Tian, W Boomsma, Y Wang, DE Otzen, MH Jensen, K Lindorff-Larsen
Journal of the American Chemical Society 137 (1), 22-25, 2015
1132015
The PCNA interaction motifs revisited: thinking outside the PIP-box
A Prestel, N Wichmann, JM Martins, R Marabini, N Kassem, SS Broendum, ...
Cellular and Molecular Life Sciences 76, 4923-4943, 2019
1112019
Spherical convolutions and their application in molecular modelling
W Boomsma, J Frellsen
Advances in neural information processing systems 30, 2017
1092017
Potentials of mean force for protein structure prediction vindicated, formalized and generalized
T Hamelryck, M Borg, M Paluszewski, J Paulsen, J Frellsen, C Andreetta, ...
PloS one 5 (11), e13714, 2010
1002010
Rapid protein stability prediction using deep learning representations
LM Blaabjerg, MM Kassem, LL Good, N Jonsson, M Cagiada, ...
Elife 12, e82593, 2023
922023
Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients
E Jimenez-Solem, TS Petersen, C Hansen, C Hansen, C Lioma, C Igel, ...
Scientific reports 11 (1), 3246, 2021
902021
ENCORE: software for quantitative ensemble comparison
M Tiberti, E Papaleo, T Bengtsen, W Boomsma, K Lindorff-Larsen
PLoS computational biology 11 (10), e1004415, 2015
832015
Fast phylogenetic DNA barcoding
K Munch, W Boomsma, E Willerslev, R Nielsen
Philosophical Transactions of the Royal Society B: Biological Sciences 363 …, 2008
832008
Beyond rotamers: a generative, probabilistic model of side chains in proteins
T Harder, W Boomsma, M Paluszewski, J Frellsen, KE Johansson, ...
BMC bioinformatics 11, 1-13, 2010
822010
Barnaba: software for analysis of nucleic acid structures and trajectories
S Bottaro, G Bussi, G Pinamonti, S Reißer, W Boomsma, K Lindorff-Larsen
Rna 25 (2), 219-231, 2019
682019
Bayesian inference of protein ensembles from SAXS data
LD Antonov, S Olsson, W Boomsma, T Hamelryck
Physical Chemistry Chemical Physics 18 (8), 5832-5838, 2016
652016
Inference of structure ensembles of flexible biomolecules from sparse, averaged data
S Olsson, J Frellsen, W Boomsma, KV Mardia, T Hamelryck
PloS one 8 (11), e79439, 2013
622013
Single-particle diffusional fingerprinting: A machine-learning framework for quantitative analysis of heterogeneous diffusion
HD Pinholt, SSR Bohr, JF Iversen, W Boomsma, NS Hatzakis
Proceedings of the National Academy of Sciences 118 (31), e2104624118, 2021
572021
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Artiklar 1–20