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

Molecular Models02:00

Molecular Models

39.9K
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.
39.9K
Distribution of Molecular Speeds01:27

Distribution of Molecular Speeds

4.1K
The motion of molecules in a gas is random in magnitude and direction for individual molecules, but a gas of many molecules has a predictable distribution of molecular speeds. This predictable distribution of molecular speeds is known as the Maxwell-Boltzmann distribution. The distribution of molecular speeds in liquids is comparable to that of gases but not identical and can help to understand the phenomenon of the boiling and vapor pressure of a liquid. Consider that a molecule requires a...
4.1K
The Fluid Mosaic Model01:34

The Fluid Mosaic Model

150.0K
The fluid mosaic model was first proposed as a visual representation of research observations. The model comprises the composition and dynamics of membranes and serves as a foundation for future membrane-related studies. The model depicts the structure of the plasma membrane with a variety of components, which include phospholipids, proteins, and carbohydrates. These integral molecules are loosely bound, defining the cell’s border and providing fluidity for optimal function.
150.0K
Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion

29.3K
Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
29.3K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

119
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
119

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

EnzymeMiner 2.0: advancing automated enzyme discovery with expansive sequence mining and smart property analysis.

Nucleic acids research·2026
Same author

Taurine inhibits apolipoprotein E4 aggregation.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie·2026
Same author

Experimentally validated deep learning control of protein aggregation.

Communications chemistry·2026
Same author

Structural insights into the evolution of alpha/beta-hydrolase fold luciferases.

International journal of biological macromolecules·2026
Same author

The effect of salidroside, an active component of Rhodiola rosea, on the metabolic activity of rat and human cytochromes P450 in preclinical studies.

Pharmacological reports : PR·2026
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026
Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026
Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026
See all related articles

Related Experiment Video

Updated: Aug 27, 2025

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
06:37

Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

Published on: September 17, 2021

4.6K

sMolBoxes: Dataflow Model for Molecular Dynamics Exploration.

Pavol Ulbrich, Manuela Waldner, Katarina Furmanova

    IEEE Transactions on Visualization and Computer Graphics
    |September 26, 2022
    PubMed
    Summary
    This summary is machine-generated.

    sMolBoxes offers a novel dataflow approach for analyzing long molecular dynamics (MD) simulations. This method integrates quantitative analysis with interactive 3D visualization, enhancing the exploration of complex molecular behaviors.

    More Related Videos

    Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
    09:17

    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

    3.2K
    Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
    05:00

    Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

    Published on: August 9, 2024

    1.4K

    Related Experiment Videos

    Last Updated: Aug 27, 2025

    Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
    06:37

    Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package

    Published on: September 17, 2021

    4.6K
    Structure-Based Simulation and Sampling of Transcription Factor Protein Movements along DNA from Atomic-Scale Stepping to Coarse-Grained Diffusion
    09:17

    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

    3.2K
    Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs
    05:00

    Author Spotlight: Streamlining Visual Dynamics to Simplify Molecular Dynamics Simulations Using Gromacs

    Published on: August 9, 2024

    1.4K

    Area of Science:

    • Biochemistry
    • Computational Biology
    • Data Visualization

    Background:

    • Molecular dynamics (MD) simulations generate vast datasets (millions of snapshots).
    • Frame-by-frame analysis of long MD simulations is infeasible.
    • Current methods rely on quantitative analysis, hindering spatial data exploration and increasing workload.

    Purpose of the Study:

    • To introduce sMolBoxes, a dataflow representation for exploring and analyzing long MD simulations.
    • To link quantitative property analysis with interactive 3D visualizations.
    • To facilitate efficient discovery of biochemically significant insights from MD data.

    Main Methods:

    • sMolBoxes utilize a node-based model for defining and evaluating properties.
    • Interactive 3D visualizations are integrated with quantitative analysis.
    • Progressive analytics allow fluid switching between multiple properties for hypothesis generation.

    Main Results:

    • sMolBoxes enable visual explanations of molecular behaviors.
    • Complex analytical tasks can be expressed with few sMolBoxes.
    • Exploratory analysis using sMolBoxes is more efficient than traditional scripting methods.

    Conclusions:

    • sMolBoxes improve the efficiency and effectiveness of MD simulation analysis.
    • The integration of visualization and quantitative analysis aids in discovering biochemical significance.
    • This approach supports hypothesis generation and streamlines the exploration of large-scale simulation data.