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

Sampling Methods: Overview01:06

Sampling Methods: Overview

3.7K
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
3.7K
Sampling Plans01:23

Sampling Plans

1.2K
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
1.2K
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

3.5K
Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
3.5K
Stratified Sampling Method01:16

Stratified Sampling Method

15.9K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
15.9K
Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

813
In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
813
Cluster Sampling Method01:20

Cluster Sampling Method

15.4K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
15.4K

You might also read

Related Articles

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

Sort by
Same author

MDNA : a software module for DNA structure generation and analysis.

Nucleic acids research·2026
Same author

Nucleation of NaCl crystals from solution: Rate prediction and influence of noisy order parameters on the committor.

The Journal of chemical physics·2026
Same author

Activation of colloidal patchy particle networks.

Soft matter·2025
Same author

Optimal kinetics for catalytic cycles from a single path-sampling simulation.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Revisiting shooting point Monte Carlo methods for transition path sampling.

The Journal of chemical physics·2025
Same author

Kinetic phase diagram for two-step nucleation in colloid-polymer mixtures.

The Journal of chemical physics·2025
Same journal

Revisiting crossed-correlated baths in open quantum systems simulated by HEOM or T-TEDOPA.

The Journal of chemical physics·2026
Same journal

Vesicle size and membrane composition control monomer transfer pathways in multicomponent lipid vesicles.

The Journal of chemical physics·2026
Same journal

Polaron-mediated exciton dynamics of P(NDI2OD-T2) unveiled by transient absorption spectroscopy under electrochemical conditions.

The Journal of chemical physics·2026
Same journal

Green-Kubo relation in a mesoscale odd fluid model.

The Journal of chemical physics·2026
Same journal

Nitrogenation of microscopic MoS2 surfaces by oxidation scanning probe lithography.

The Journal of chemical physics·2026
Same journal

Molecular structure, binding, and disorder in TDBC-Ag plexcitonic assemblies.

The Journal of chemical physics·2026
See all related articles

Related Experiment Video

Updated: Mar 14, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.9K

Combining multiple interface set path ensembles with MBAR reweighting.

Rik S Breebaart1, Peter G Bolhuis1

  • 1Van't Hoff Institute for Molecular Sciences, Universiteit van Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands.

The Journal of Chemical Physics
|March 13, 2026
PubMed
Summary
This summary is machine-generated.

We developed a new method to improve statistical accuracy in simulations by combining transition interface sampling. This approach enhances the reliability of molecular dynamics simulations for complex systems.

More Related Videos

Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency
06:41

Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency

Published on: May 10, 2024

2.7K
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.2K

Related Experiment Videos

Last Updated: Mar 14, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.9K
Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency
06:41

Author Spotlight: Optimizing Cryo-EM Analysis with CryoSieve for Enhanced Particle Selection Efficiency

Published on: May 10, 2024

2.7K
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.2K

Area of Science:

  • Computational chemistry
  • Molecular dynamics simulations
  • Statistical mechanics

Background:

  • Transition interface sampling (TIS) is a powerful technique for enhanced molecular simulations.
  • Combining simulations conditioned on different collective variables can improve efficiency.
  • Existing methods for combining such simulations may lack global consistency.

Purpose of the Study:

  • To introduce a novel method for computing the reweighted path ensemble.
  • To achieve globally consistent reweighting of transition interface sampling simulations.
  • To enhance the statistical accuracy of molecular simulation results.

Main Methods:

  • Combining transition interface sampling (TIS) simulations.
  • Utilizing a globally consistent reweighting framework.
  • Applying the multistate Bennett acceptance ratio (MBAR) methodology to entire trajectories.

Main Results:

  • The proposed method successfully computes the reweighted path ensemble.
  • Demonstrated improved statistical accuracy compared to independently reweighted combinations.
  • Validated the technique on 2D potential models and a host-guest system.

Conclusions:

  • The new method offers significant improvements in statistical accuracy for molecular simulations.
  • Globally consistent reweighting of TIS simulations is feasible and beneficial.
  • This approach advances the reliable simulation of complex molecular systems.