Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Methods of Obtaining Topography

Methods of Obtaining Topography

Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Machine Learning-Driven Simulations of the SARS-CoV-2 Fitness Landscape from Deep Mutational Scanning Experiments.

Journal of chemical information and modeling·2026

Same author

Active subspace learning for coarse-grained molecular dynamics.

The Journal of chemical physics·2026

Same author

Mechanism of HIV-1 Capsid Rupture and Uncoating by Reverse Transcription.

bioRxiv : the preprint server for biology·2026

Same author

Probabilistic Forecasting for Coarse-Grained Molecular Dynamics.

Journal of chemical theory and computation·2026

Same author

Physical Confinement Modulates the Rate-Limiting Transition in the Release of Phosphate from Actin Filaments.

bioRxiv : the preprint server for biology·2026

Same author

Hydration-Controlled Proton Transport in Respiratory Complex I.

Journal of the American Chemical Society·2026

Same journal

The Role of Functional Groups in Substituted Benzoic Acids Used as Dopants in Liquid Crystal Mixtures on the Nematic-Isotropic Transitions.

The journal of physical chemistry. B·2026

Same journal

Hyperfine Coupling Quantifies Hole Delocalization in Triarylamine Radical Cations of D-χ-A Molecules.

The journal of physical chemistry. B·2026

Same journal

A Solvatochromic-Chemometric Framework to Resolve Subtle Polarity Microenvironment Differences in Cycloalkanes Driven by Molecular Conformation and Substituent Effects: A Proof-Of-Concept for Advanced Aviation Fuel Design.

The journal of physical chemistry. B·2026

Same journal

Selective Effects of Backbone Cyclization and Disulfide Bonding as Global Covalent Constraints on the Conformational Ensemble of Sunflower Trypsin Inhibitor-1.

The journal of physical chemistry. B·2026

Same journal

Europium Coordination Structure in Peptide Complexes Resolved with Simulation and X-ray Absorption Spectroscopy.

The journal of physical chemistry. B·2026

Same journal

Competitive Coordination and Structural Evolution of Phenylalanine-Mg<sup>2+</sup> Complexes in Microaqueous Environments: Insights from DFT and Molecular Dynamics Simulations.

The journal of physical chemistry. B·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 15, 2025

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

OpenMSCG: A Software Tool for Bottom-Up Coarse-Graining.

Yuxing Peng¹, Alexander J Pak², Aleksander E P Durumeric³

¹NVIDIA Corporation, 2788 San Tomas Expressway, Santa Clara, California 95051, United States.

The Journal of Physical Chemistry. B

|October 4, 2023

Summary

This summary is machine-generated.

OpenMSCG software offers a modular, open-source toolkit for developing accurate coarse-grained (CG) models using bottom-up computational chemistry methods. This enhances the reliability and reproducibility of large-scale simulations in biophysics and materials science.

More Related Videos

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

Contrast-Matching Detergent in Small-Angle Neutron Scattering Experiments for Membrane Protein Structural Analysis and Ab Initio Modeling

Contrast-Matching Detergent in Small-Angle Neutron Scattering Experiments for Membrane Protein Structural Analysis and Ab Initio Modeling

Published on: October 21, 2018

Related Experiment Videos

Last Updated: Jul 15, 2025

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion

Published on: March 1, 2022

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

Contrast-Matching Detergent in Small-Angle Neutron Scattering Experiments for Membrane Protein Structural Analysis and Ab Initio Modeling

Contrast-Matching Detergent in Small-Angle Neutron Scattering Experiments for Membrane Protein Structural Analysis and Ab Initio Modeling

Published on: October 21, 2018

Area of Science:

Computational chemistry
Biophysics
Materials science

Background:

Bottom-up coarse-graining (CG) is crucial for simulating complex systems.
Accurate CG models require rigorous derivation from fine-grained data.
Existing methods can be complex to implement and share.

Purpose of the Study:

Introduce OpenMSCG, a novel open-source software for bottom-up CG model development.
Provide a comprehensive and modular toolset for various CG methodologies.
Facilitate the derivation of CG models from all-atom simulation data.

Main Methods:

Developed OpenMSCG as a modular Python framework.
Integrated multiple established bottom-up CG methods: Boltzmann Inversion (BI), Force-Matching (FM), Ultra-Coarse-Graining (UCG), Relative Entropy Minimization (REM), Essential Dynamics Coarse-Graining (EDCG), and Heterogeneous Elastic Network Modeling (HeteroENM).
Ensured compatibility with major molecular dynamics (MD) software (GROMACS, LAMMPS, NAMD).

Main Results:

OpenMSCG provides a high-performance, comprehensive toolset for CG model derivation.
The modular Python design enables user customization of modeling 'recipes'.
Supports reproducible generation of CG models from diverse fine-grained simulation data.

Conclusions:

OpenMSCG significantly improves the reliability and reproducibility of bottom-up CG models.
Enhances the sharing and application of CG models across computational disciplines.
Empowers researchers to develop and customize CG models efficiently.