g_wham—A Free Weighted Histogram Analysis Implementation Including Robust Error and Autocorrelation Estimates
By Jochen S. Hub, B. L. de Groot, D. van der Spoel. 2010
1,539 citations recorded by the source corpus.
Subfields: Atomic and Molecular Physics, and Optics, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/5be3ff667dd9bbea9f9115c6b0ad46991d4071bf
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Atomic and Molecular Physics, and Optics
- Justin A. Lemkul
- D. van der Spoel
- Erik Lindahl
- Michael R. Shirts
- Vijay S. Pande
- Eric J. Sorin
- Kevin J. Karplus
- A. G. D. Brevern
In Molecular Biology
- Justin A. Lemkul
- Erik Lindahl
- Michael R. Shirts
- D. van der Spoel
- Szilárd Páll
- Per Larsson
- Siewert-Jan Marrink
- Vijay S. Pande
Citations in the corpus
- GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit (2013, background): “…code also comes with a new g_bar tool that automatically analyzes the statistical overlap, calculates the free energy of each component, and provides a finished curve of the free energy required to move from one end state to the other, including estimates of the standard error and sampling (Fig.”
- From Proteins to Perturbed Hamiltonians: A Suite of Tutorials for the GROMACS-2018 Molecular Simulation Package [Article v1.0] (2019, methodology): “6 Data Analysis To compute the PMF along the reaction coordinate, the Weighted Histogram Analysis Method (WHAM) [61] is employed, implemented in GROMACS as the wham program [62], which also includes algorithms to estimate errors associated with the resulting PMF.”