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

Modeling and Similitude01:12

Modeling and Similitude

711
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...
711
Steps in the Modeling Process01:14

Steps in the Modeling Process

796
Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...
796
Virtual Work for a System of Connected Rigid Bodies01:06

Virtual Work for a System of Connected Rigid Bodies

835
Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
Next,...
835
Torque Free Motion01:15

Torque Free Motion

902
The torque-free motion refers to the movement of a rigid body in space when no external torques are acting upon it. This type of motion can be observed in environments where there are no external forces or frictions, like in outer space. For example, a rotation of Mars in space is a torque-free motion. Mars is an axisymmetric object, meaning it has an axis of symmetry along which it rotates, designated as the z-axis. The rotating frame of reference is defined such that the center of mass of...
902
Modeling with Differential Equations01:25

Modeling with Differential Equations

159
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
159
Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

894
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
894

You might also read

Related Articles

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

Sort by
Same author

Enhancing Clinical Note Generation with ICD-10, Clinical Ontology Knowledge Graphs, and Chain-of-Thought Prompting Using GPT-4.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same author

SAGE: Spatially Aware Gene Selection and Dual-View Embedding Fusion for Domain Identification in Spatial Transcriptomics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

ChromNet: A Multi-Task Learning Framework for Cross-Cell Type Prediction of 3D Chromatin Interactions Using Epigenetic Signals.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025
Same author

CATH-ddG: towards robust mutation effect prediction on protein-protein interactions out of CATH homologous superfamily.

Bioinformatics (Oxford, England)·2025
Same author

ColdstartCPI: Induced-fit theory-guided DTI predictive model with improved generalization performance.

Nature communications·2025
Same author

Foundation models in bioinformatics.

National science review·2025

Related Experiment Video

Updated: Mar 21, 2026

Computer-Generated Animal Model Stimuli
26:43

Computer-Generated Animal Model Stimuli

Published on: July 29, 2007

11.5K

RCD+: Fast loop modeling server.

José Ramón López-Blanco1, Alejandro Jesús Canosa-Valls1, Yaohang Li2

  • 1Department of Biological Chemical Physics, Rocasolano Physical Chemistry Institute C.S.I.C., Serrano 119, 28006 Madrid, Spain.

Nucleic Acids Research
|May 7, 2016
PubMed
Summary
This summary is machine-generated.

We developed an improved Random Coordinate Descent (RCD) method for ab initio protein loop modeling. This fast, accurate online service predicts near-native loop conformations for protein structure prediction.

More Related Videos

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
09:32

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

Published on: April 11, 2018

10.4K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

8.1K

Related Experiment Videos

Last Updated: Mar 21, 2026

Computer-Generated Animal Model Stimuli
26:43

Computer-Generated Animal Model Stimuli

Published on: July 29, 2007

11.5K
Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
09:32

Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion

Published on: April 11, 2018

10.4K
A Rapid Method for Modeling a Variable Cycle Engine
04:58

A Rapid Method for Modeling a Variable Cycle Engine

Published on: August 13, 2019

8.1K

Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein structure prediction

Background:

  • Protein loop modeling is essential for accurate protein structure prediction.
  • Existing methods face challenges in efficiency and accuracy for ab initio loop modeling.

Purpose of the Study:

  • To present an enhanced ab initio loop modeling service based on the Random Coordinate Descent (RCD) algorithm.
  • To improve sampling efficiency and accuracy in protein loop modeling.

Main Methods:

  • Developed an improved RCD algorithm incorporating workflow optimization, MPI-parallelization, and fast backbone angle sampling.
  • Combined coarse-grained conformational search with full-atom refinement.
  • Utilized a distance-orientation dependent energy filter for ranking and Rosetta for refinement.

Main Results:

  • Achieved average root mean squared deviations (RMSD) of 0.8 Å for 8-residue loops and 1.4 Å for 12-residue loops.
  • Demonstrated competitive accuracy compared to state-of-the-art methods.
  • Achieved results approximately 10-fold faster than existing methods.

Conclusions:

  • The enhanced RCD service provides a fast and accurate solution for ab initio protein loop modeling.
  • The improved algorithm effectively samples near-native conformations, aiding protein structure prediction.
  • The user-friendly web interface facilitates interactive inspection of predicted loop models.