Wouter Boomsma
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
ORCID: 0000-0002-8257-3827
1 - 1 out of 1Page size: 10
- 2011
- Published
Efficient, non-disruptive local moves for Monte Carlo sampling of proteins
Bottaro, S., Boomsma, Wouter, Johansson, Kristoffer Enøe, Andreetta, C., Hamelryck, Thomas Wim & Ferkinghoff-Borg, J., 2011, Next Generation Statistics in Biosciences: Proceedings of the 30th Leeds Annual Statistical Research (LASR) Workshop. Mardia, K. V., Gusnanto, A., Riley, A. D. & Voss, J. (eds.). University of Leeds, p. 127 1 p.Research output: Chapter in Book/Report/Conference proceeding › Conference abstract in proceedings › Research
ID: 40103911
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Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics
Research output: Contribution to journal › Journal article › Research › peer-review
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Inference of structure ensembles of flexible biomolecules from sparse, averaged data
Research output: Contribution to journal › Journal article › Research › peer-review
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1429
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Potentials of mean force for protein structure prediction vindicated, formalized and generalized
Research output: Contribution to journal › Journal article › Research › peer-review
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