Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Orthogonal Trajectories01:26

Orthogonal Trajectories

67
Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
67
Molecular Models02:00

Molecular Models

43.8K
Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.
43.8K
Molecular and Ionic Solids02:54

Molecular and Ionic Solids

20.1K
Crystalline solids are divided into four types: molecular, ionic, metallic, and covalent network based on the type of constituent units and their interparticle interactions.
Molecular Solids
Molecular crystalline solids, such as ice, sucrose (table sugar), and iodine, are solids that are composed of neutral molecules as their constituent units. These molecules are held together by weak intermolecular forces such as London dispersion forces, dipole-dipole interactions, or hydrogen bonds, which...
20.1K
Molecular Orbital Theory II03:51

Molecular Orbital Theory II

27.5K
Molecular Orbital Energy Diagrams
27.5K
Molecular Orbital Theory I02:35

Molecular Orbital Theory I

47.7K
Overview of Molecular Orbital Theory
47.7K
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

46.0K
VSEPR Theory for Determination of Electron Pair Geometries
46.0K

You might also read

Related Articles

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

Sort by
Same author

Understanding chemical reactions through multimedia resolution data artistic educational tool (MRDAET).

Protein science : a publication of the Protein Society·2026
Same author

Embarrassingly Agile-Data Visualization Methodology in Emergency Responses.

IEEE computer graphics and applications·2025
Same author

Helveg: Diagrams for Software Documentation.

IEEE transactions on visualization and computer graphics·2025
Same author

A Survey on Quality Metrics for Text-to-Image Generation.

IEEE transactions on visualization and computer graphics·2025
Same author

DeepEM Playground: Bringing deep learning to electron microscopy labs.

Journal of microscopy·2025
Same author

Proto-Caps: interpretable medical image classification using prototype learning and privileged information.

PeerJ. Computer science·2025

Related Experiment Video

Updated: Feb 5, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

14.2K

Visualization of Large Molecular Trajectories.

David Duran, Pedro Hermosilla, Timo Ropinski

    IEEE Transactions on Visualization and Computer Graphics
    |September 13, 2018
    PubMed
    Summary
    This summary is machine-generated.

    Analyzing large protein-ligand interaction datasets is challenging. This study introduces a novel visualization system to interactively explore extensive simulation trajectories, aiding researchers in understanding complex molecular dynamics.

    More Related Videos

    Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns
    04:24

    Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns

    Published on: February 13, 2011

    9.9K
    Modeling an Enzyme Active Site using Molecular Visualization Freeware
    14:37

    Modeling an Enzyme Active Site using Molecular Visualization Freeware

    Published on: December 25, 2021

    11.5K

    Related Experiment Videos

    Last Updated: Feb 5, 2026

    Trajectory Data Analyses for Pedestrian Space-time Activity Study
    16:14

    Trajectory Data Analyses for Pedestrian Space-time Activity Study

    Published on: February 25, 2013

    14.2K
    Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns
    04:24

    Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns

    Published on: February 13, 2011

    9.9K
    Modeling an Enzyme Active Site using Molecular Visualization Freeware
    14:37

    Modeling an Enzyme Active Site using Molecular Visualization Freeware

    Published on: December 25, 2021

    11.5K

    Area of Science:

    • Computational chemistry and structural biology.
    • Development of novel visualization tools for molecular dynamics.

    Background:

    • Analyzing protein-ligand interactions is crucial but time-intensive.
    • Large simulation datasets (hundreds of thousands of steps) are difficult to investigate with traditional methods.
    • Existing approaches require manual inspection of multiple charts and 3D animations.

    Purpose of the Study:

    • To present a novel system for the visual exploration of very large molecular dynamics trajectories.
    • To facilitate interactive and user-friendly inspection of protein-ligand interplay.
    • To support simulations involving single or multiple ligands.

    Main Methods:

    • Development of a novel system for interactive visual exploration.
    • Automatic derivation of visualization motifs from simulation data.
    • Integration of specialized widgets for accelerated data inspection and navigation.

    Main Results:

    • The system provides automated visualization motifs to highlight protein-ligand interactions.
    • Specialized widgets enable efficient data inspection and navigation within large trajectories.
    • The tool effectively handles large datasets and simulations with multiple ligands.

    Conclusions:

    • The developed system significantly eases and accelerates the investigation of large protein-ligand simulation trajectories.
    • The interactive visualization approach enhances understanding of molecular dynamics and interactions.
    • Expert feedback confirms the usefulness of the tool for protein engineers.