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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

117
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
117
Chromatographic Resolution01:15

Chromatographic Resolution

1.1K
In chromatography, a solute moves through a chromatographic column and tends to spread, forming a Gaussian-shaped band. The longer the solute spends in the column, the broader the band becomes. The broadening can lead to overlaps within the column, affecting separation effectiveness.
The effectiveness of separation can be evaluated by determining the level of separation between two neighboring peaks in a chromatogram, which represents the individual components of a sample.
In chromatography,...
1.1K
Modeling and Similitude01:12

Modeling and Similitude

373
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
373

You might also read

Related Articles

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

Sort by
Same author

hexABC seeking the physical code of DNA.

Nature communications·2026
Same author

Membrane-Inserting α‑Lipid Polymers: Understanding Lipid Membrane Insertion and Effect on Membrane Fluidity.

Chemistry of materials : a publication of the American Chemical Society·2025
Same author

The need to implement FAIR principles in biomolecular simulations.

Nature methods·2025
Same author

Interfacial water confers transcription factors with dinucleotide specificity.

Nature structural & molecular biology·2025
Same author

High-Throughput Microarray Approaches for Predicting the Stability of Drug-Polymer Solid Dispersions.

Molecular pharmaceutics·2024
Same author

Protein Oxidative Modifications in Neurodegenerative Diseases: From Advances in Detection and Modelling to Their Use as Disease Biomarkers.

Antioxidants (Basel, Switzerland)·2024
Same journal

Complementing Onsager's Conductivity Theory by Grotthuss Mechanism Mitigation via Ion-Induced Depletion of Hydrogen-Bond-Donating Water.

Journal of chemical theory and computation·2026
Same journal

Microscopic Stress in Biomembranes: A Perspective on Key Concepts, Methods, and Applications.

Journal of chemical theory and computation·2026
Same journal

Analytic Nuclear Gradients Including Oriented External Electric Fields in a Molecule-Fixed Frame.

Journal of chemical theory and computation·2026
Same journal

Knowledge Distillation of a Protein Language Model Yields a Foundational Implicit Solvent Model.

Journal of chemical theory and computation·2026
Same journal

Generalizable Protein Folding Pathway Exploration with DA2-GRASP: Extending Beyond Miniproteins.

Journal of chemical theory and computation·2026
Same journal

Improving PCM in Protic Media: Markov State Models for TD-DFT Calculations.

Journal of chemical theory and computation·2026
See all related articles

Related Experiment Video

Updated: Oct 11, 2025

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.6K

GLIMPS: A Machine Learning Approach to Resolution Transformation for Multiscale Modeling.

Keverne A Louison, Ian L Dryden, Charles A Laughton

    Journal of Chemical Theory and Computation
    |December 1, 2021
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a machine learning method to convert molecular models between different resolutions. The technique efficiently translates models using only particle coordinates, enabling versatile molecular modeling applications.

    More Related Videos

    Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
    09:10

    Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

    Published on: August 5, 2021

    1.9K
    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
    11:38

    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

    Published on: August 23, 2017

    10.0K

    Related Experiment Videos

    Last Updated: Oct 11, 2025

    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
    06:25

    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

    Published on: February 12, 2014

    8.6K
    Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures
    09:10

    Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

    Published on: August 5, 2021

    1.9K
    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench
    11:38

    Volume Segmentation and Analysis of Biological Materials Using SuRVoS Super-region Volume Segmentation Workbench

    Published on: August 23, 2017

    10.0K

    Area of Science:

    • Computational chemistry
    • Biophysics
    • Machine learning

    Background:

    • Molecular modeling often requires different levels of resolution for various analyses.
    • Existing methods for resolution transformation can be complex and require extensive prior information.

    Purpose of the Study:

    • To develop a general and data-driven approach for transforming molecular models between different resolutions.
    • To enable efficient and flexible interconversion of molecular representations.

    Main Methods:

    • Utilized machine learning on matched sets of molecular models at different resolutions.
    • The method requires only particle coordinates, avoiding the need for templates or force fields.
    • Trained models can perform transformations in both directions.

    Main Results:

    • Successfully demonstrated a general machine learning framework for resolution transformation.
    • The approach is versatile, applicable to various molecular systems.
    • Achieved efficient transformation of molecular models using minimal input data.

    Conclusions:

    • The developed machine learning approach offers a powerful and generalizable method for interconverting molecular models at different resolutions.
    • This technique simplifies and enhances the flexibility of molecular modeling workflows.
    • The method's reliance solely on particle coordinates makes it broadly applicable.