Wouter Boomsma
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
- Published
3D steerable CNNs: Learning rotationally equivariant features in volumetric data
Weiler, M., Geiger, M., Welling, M., Boomsma, Wouter & Cohen, T., 2018, Proceedings of the 32nd International Conference on Neural Information Processing Systems. derc ed. NIPS Proceedings, Vol. 2018. p. 10381-10392 12 p. (Advances in Neural Information Processing Systems, Vol. 31).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
A Monte Carlo study of the early steps of functional amyloid formation
Tian, P., Lindorff-Larsen, Kresten, Boomsma, Wouter, Jensen, Mogens Høgh & Otzen, D. E., 2016, In: P L o S One. 11, 1, 18 p., e0146096.Research output: Contribution to journal › Journal article › Research › peer-review
A comparison of adaptive operator scheduling methods on the traveling salesman problem
Boomsma, Wouter, 2004, Evolutionary Computation in Combinatorial Optimization: 4th European Conference, EvoCOP 2004, Coimbra, Portugal, April 5-7, 2004. Proceedings. Gottlieb, J. & Raidl, G. R. (eds.). Springer, p. 31-40 10 p. (Lecture notes in computer science, Vol. 3004).Research output: Chapter in Book/Report/Conference proceeding › Book chapter › Research › peer-review
- Published
A context-dependent and disordered ubiquitin-binding motif
Dreier, Jesper Elmsted, Prestel, Andreas, Martins, J. M., Brøndum, S. S., Nielsen, Olaf, Garbers, Anna Engstrøm, Suga, H., Boomsma, Wouter, Rogers, Joseph Matthew, Hartmann-Petersen, Rasmus & Kragelund, Birthe Brandt, 2022, In: Cellular and molecular life sciences : CMLS. 79, 9, 21 p., 484.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
A generative, probabilistic model of local protein structure
Boomsma, Wouter, Mardia, K. V., Taylor, C. C., Ferkinghoff-Borg, J., Krogh, Anders & Hamelryck, Thomas Wim, 2008, In: Proceedings of the National Academy of Science of the United States of America. 105, 26, p. 8932-8937 5 p.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
A probabilistic approach to protein structure prediction: PHAISTOS in CASP8
Borg, M., Boomsma, Wouter, Ferkinghoff-Borg, J., Frellsen, J., Harder, T. P., Mardia, K., Røgen, P., Stovgaard, K. & Hamelryck, Thomas Wim, 2009, LASR 2009 — Statistical Tools for Challenges in Bioinformatics. Proceedings. Gusnanto, A., Mardia, K. V. & Fallaize, C. J. (eds.). University of Leeds, p. 65-70 6 p.Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
- Published
A probabilistic approach to protein structureprediction: PHAISTOS in CASP8
Borg, M., Boomsma, Wouter, Ferkinghoff-Borg, J., Frellsen, J., Harder, T. P., Mardia, K. V., Røgen, P., Stovgaard, K. & Hamelryck, Thomas Wim, 2009, In: School of Mathematics. p. 65-70Research output: Contribution to journal › Journal article › Research › peer-review
- Published
A sticky cage can slow down folding
Boomsma, Wouter & Lindorff-Larsen, Kresten, 2013, In: Biophysical Journal. 104, 5, p. 964-965 2 p.Research output: Contribution to journal › Comment/debate › Research
- Published
A systematic analysis of regression models for protein engineering
Michael, Richard, Kæstel-Hansen, Jacob, Groth, Peter Mørch, Bartels, S., Salomon, J., Tian, P., Hatzakis, Nikos & Boomsma, Wouter, 2024, In: PLOS Computational Biology. 20, 5 May, 22 p., e1012061.Research output: Contribution to journal › Journal article › Research › peer-review
- Published
Adaptive Cholesky Gaussian Processes
Bartels, S., Stensbo-Smidt, K., Moreno-Muñoz, P., Boomsma, Wouter, Frellsen, J. & Hauberg, S., 2023, In: Proceedings of Machine Learning Research. 206, p. 408--452 44 p.Research output: Contribution to journal › Conference article › Research › peer-review
ID: 40103911
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Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics
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Potentials of mean force for protein structure prediction vindicated, formalized and generalized
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Inference of structure ensembles of flexible biomolecules from sparse, averaged data
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