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Biomolecular Simulations

Overview of attention for book
Cover of 'Biomolecular Simulations'

Table of Contents

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    Book Overview
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    Chapter 1 Atomistic Force Fields for Proteins
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    Chapter 2 Force Fields for Small Molecules
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    Chapter 3 Improvement of RNA Simulations with Torsional Revisions of the AMBER Force Field
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    Chapter 4 Quantum Chemical and QM/MM Models in Biochemistry
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    Chapter 5 A Practical View of the Martini Force Field.
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    Chapter 6 Using SMOG 2 to Simulate Complex Biomolecular Assemblies
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    Chapter 7 Replica-Exchange Methods for Biomolecular Simulations
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    Chapter 8 Metadynamics to Enhance Sampling in Biomolecular Simulations
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    Chapter 9 Protein–Ligand Binding Free Energy Calculations with FEP+
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    Chapter 10 Ligand-Binding Calculations with Metadynamics
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    Chapter 11 The Adaptive Path Collective Variable: A Versatile Biasing Approach to Compute the Average Transition Path and Free Energy of Molecular Transitions
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    Chapter 12 Google-Accelerated Biomolecular Simulations.
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    Chapter 13 A Practical Guide to the Simultaneous Determination of Protein Structure and Dynamics Using Metainference
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    Chapter 14 Inferring Structural Ensembles of Flexible and Dynamic Macromolecules Using Bayesian, Maximum Entropy, and Minimal-Ensemble Refinement Methods
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    Chapter 15 Modeling Biological Complexes Using Integrative Modeling Platform
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    Chapter 16 Coevolutionary Analysis of Protein Sequences for Molecular Modeling
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    Chapter 17 Coarse Graining of a Giant Molecular System: The Chromatin Fiber
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    Chapter 18 Analyzing Biomolecular Ensembles
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    Chapter 19 Using Data-Reduction Techniques to Analyze Biomolecular Trajectories
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    Chapter 20 Analysis Libraries for Molecular Trajectories: A Cross-Language Synopsis
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    Chapter 21 Analyzing and Biasing Simulations with PLUMED
Attention for Chapter 21: Analyzing and Biasing Simulations with PLUMED
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Citations

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Chapter title
Analyzing and Biasing Simulations with PLUMED
Chapter number 21
Book title
Biomolecular Simulations
DOI 10.1007/978-1-4939-9608-7_21
Pubmed ID
Book ISBNs
978-1-4939-9607-0, 978-1-4939-9608-7
Authors

Bussi, Giovanni, Tribello, Gareth A.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 123 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 36 29%
Researcher 16 13%
Student > Bachelor 10 8%
Student > Master 10 8%
Student > Postgraduate 5 4%
Other 8 7%
Unknown 38 31%
Readers by discipline Count As %
Chemistry 24 20%
Physics and Astronomy 13 11%
Biochemistry, Genetics and Molecular Biology 11 9%
Chemical Engineering 8 7%
Materials Science 6 5%
Other 16 13%
Unknown 45 37%