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

Three-Dimensional Force System01:30

Three-Dimensional Force System

2.0K
In mechanical engineering, a three-dimensional force system is a system of forces acting in three dimensions, with forces applied along the x, y, and z coordinate axes. The three-dimensional force system is an important concept in mechanical engineering, as it allows engineers to understand and analyze the behavior of objects and structures in three dimensions. By understanding the forces acting on a system, engineers can design more efficient and effective mechanical systems that can withstand...
2.0K
Two-Dimensional Force System01:20

Two-Dimensional Force System

906
A two-dimensional system in mechanical engineering involves the analysis of motion and forces in a plane. A two-dimensional force vector can be resolved into its components as:
906
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

666
A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
666
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

571
Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
571
Introduction to force01:25

Introduction to force

531
Consider water flowing from a nozzle to a turbine vane. As the water hits the turbine vane, it exerts a force that causes it to move along the flow of direction. Force is an impact that changes an object's motion, shape, or orientation. Forces can be caused by physical contact, such as a push or pull, or through non-contact interactions, such as magnetic or gravitational forces. Force is a vector quantity with both magnitude and direction, and is measured in newtons (N) in the SI unit...
531
Types of Forces01:09

Types of Forces

9.7K
In most situations, forces can be grouped into two categories: contact forces and field forces.  Contact forces occur as a result of direct physical contact between objects. Field forces, however, act without the necessity of physical contact between objects. They depend on the presence of a "field" in the region of space surrounding the body under consideration. You can think of a field as a property of space that is detectable by the forces it exerts. Scientists think there...
9.7K

You might also read

Related Articles

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

Sort by
Same author

Proteomic profiling of whole tissue sections in cardiac ATTR amyloidosis reveals increased extracellular matrix remodeling.

Cardiovascular pathology : the official journal of the Society for Cardiovascular Pathology·2026
Same author

Integrated omics reveal a unique antibacterial mechanism of action for the small molecule HSI#6.

Current research in microbial sciences·2026
Same author

Confirmation of monotypic immunofluorescence staining by mass spectrometry in a case of proliferative glomerulonephritis.

Histopathology·2026
Same author

FoldDelay web server: an online tool to quantify translation-driven delays in protein native contact formation.

Nucleic acids research·2026
Same author

Belgian recommendations for tissue diagnosis of amyloidosis.

Acta clinica Belgica·2026
Same author

Atomic structures of medin and Aβ fibrils reveal polymorphic remodeling in mixed amyloid systems.

Nature communications·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
Same journal

EDEL: Enhancing Dense Retrievers for Curation of Biomedical Knowledge Bases.

Bioinformatics (Oxford, England)·2026
Same journal

Informative Relational Learning for Adverse Reaction Prediction with Enhanced Generalization to Novel Drugs.

Bioinformatics (Oxford, England)·2026
Same journal

An interpretable deep learning framework uncovers features governing CRISPR-Cas9 genome-editing efficiency.

Bioinformatics (Oxford, England)·2026
Same journal

3DICE: Interpretable 3D Cross-Modal Learning for Drug-Target Interaction Prediction and Large-Scale Drug Discovery.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jun 30, 2025

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

2.2K

Integrating physics in deep learning algorithms: a force field as a PyTorch module.

Gabriele Orlando1,2,3, Luis Serrano4,5,6, Joost Schymkowitz1,2,3

  • 1Switch Laboratory, VIB Center for Brain and Disease Research, VIB, Leuven 3000, Belgium.

Bioinformatics (Oxford, England)
|March 21, 2024
PubMed
Summary
This summary is machine-generated.

MadraX is a new force field that integrates with deep learning algorithms for structural biology. This addresses limitations in data-scarce scenarios by enabling end-to-end learning of complex physical rules.

More Related Videos

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

8.9K
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.4K

Related Experiment Videos

Last Updated: Jun 30, 2025

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches
07:31

Author Spotlight: Advancing Cell Membrane Biophysics - Exploring Interactions and Challenges Through Experimental and Computational Approaches

Published on: September 1, 2023

2.2K
Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

8.9K
A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.4K

Area of Science:

  • Structural Biology
  • Computational Chemistry
  • Machine Learning

Background:

  • Deep learning in structural biology is hindered by limited data, preventing convergence to accurate models.
  • Current force fields are incompatible with deep learning due to implementation barriers.

Purpose of the Study:

  • To introduce MadraX, a novel force field designed for seamless integration with deep learning.
  • To enable end-to-end learning of physical principles in structural biology.

Main Methods:

  • Implementation of MadraX as a differentiable PyTorch module.
  • Integration of MadraX with deep learning frameworks for structural biology applications.

Main Results:

  • MadraX facilitates end-to-end interaction between force fields and deep learning algorithms.
  • Overcomes limitations of data scarcity in deep learning for structural biology.

Conclusions:

  • MadraX provides a powerful tool for advancing deep learning applications in structural biology.
  • The differentiable nature of MadraX enables more robust and accurate modeling.