Alfred Nordman
Assistant with doctoral duties at Department of Cell and Molecular Biology; Computational Biology and Bioinformatics
- E-mail:
- alfred.nordman@icm.uu.se
- Visiting address:
- Husargatan 3
752 37 Uppsala - Postal address:
- Box 596
751 24 UPPSALA
Publications
Recent publications
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Parameters, Potentials and Probabilistic Methods in Molecular Modeling
2026
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Bayesian three-point water models
Part of npj Computational Materials, 2025
- DOI for Bayesian three-point water models
- Download full text (pdf) of Bayesian three-point water models
-
Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
Part of Digital Discovery, p. 1925-1935, 2025
- DOI for Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
- Download full text (pdf) of Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
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An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
Part of Journal of Chemical Information and Modeling, p. 412-431, 2023
- DOI for An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
- Download full text (pdf) of An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
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Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
Part of Journal of Chemical Theory and Computation, p. 3307-3315, 2020
- DOI for Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
- Download full text (pdf) of Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
All publications
Articles in journal
-
Bayesian three-point water models
Part of npj Computational Materials, 2025
- DOI for Bayesian three-point water models
- Download full text (pdf) of Bayesian three-point water models
-
Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
Part of Digital Discovery, p. 1925-1935, 2025
- DOI for Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
- Download full text (pdf) of Evolutionary machine learning of physics-based force fields in high-dimensional parameter-space
-
Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
Part of Journal of Chemical Theory and Computation, p. 3307-3315, 2020
- DOI for Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
- Download full text (pdf) of Theoretical Infrared Spectra: Quantitative Similarity Measures and Force Fields
Articles, review/survey
-
An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
Part of Journal of Chemical Information and Modeling, p. 412-431, 2023
- DOI for An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation
- Download full text (pdf) of An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation