Umbrella sampling

By J. Kästner. 2011

1,282 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/ddbb7467f1aff6ea6e206ec2ba5f27e4f5a731ef

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

1. ST John
2. Stefano Moro
3. Ken A. Dill
4. Gábor Csányi
5. Carlos Simmerling
6. Veronica Salmaso
7. Emiliano Brini
8. Alexander V. Shapeev

In Molecular Biology

1. Ken A. Dill
2. Emiliano Brini
3. ST John
4. Stefano Moro
5. Gábor Csányi
6. Carlos Simmerling
7. Veronica Salmaso
8. Frank No'e

In Statistical and Nonlinear Physics

1. ST John
2. Stefano Moro
3. Ken A. Dill
4. Gábor Csányi
5. Carlos Simmerling
6. Veronica Salmaso
7. Emiliano Brini

Citations in the corpus

• Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview (2018, methodology): “Then the distribution of the system and consequently the free energy is calculated along the CV (Kästner, 2011).”
• Many-Body Coarse-Grained Interactions Using Gaussian Approximation Potentials. (2016, methodology): “The most popular methods are the gradient-based Umbrella Integration [67, 68], the Blue Moon method [69, 70], the Adaptive Biasing Force (ABF) method [71, 72], and the histogram-based Metadynamics [73–75].”
• Protein storytelling through physics (2020, background): “Advances are coming from enhanced samplingmethods, such asmetadynamics (34), replica exchange molecular dynamics (REMD) (35), simulated annealing (36), adaptive force biasing (37), and umbrella sampling (38) [for reviews, see (39, 40), and for the basic concepts see (21, 41)].”