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Related Concept Videos

Sampling Methods: Overview01:06

Sampling Methods: Overview

479
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...
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Cluster Sampling Method01:20

Cluster Sampling Method

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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...
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Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

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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...
359
Sampling Plans01:23

Sampling Plans

242
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...
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Sampling Distribution01:12

Sampling Distribution

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Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
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Random Sampling Method01:09

Random Sampling Method

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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. Data are the result of sampling from a 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. Among the various sampling methods used by...
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Related Experiment Video

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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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CHARMM-GUI Enhanced Sampler for various collective variables and enhanced sampling methods.

Donghyuk Suh1,2, Shasha Feng1, Hwayoung Lee1

  • 1Department of Biological Sciences, Chemistry, Bioengineering, and Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania, USA.

Protein Science : a Publication of the Protein Society
|September 20, 2022
PubMed
Summary
This summary is machine-generated.

CHARMM-GUI Enhanced Sampler is a web tool simplifying enhanced sampling simulations for complex molecular dynamics. It aids researchers in achieving convergence for rugged potential energy surfaces, crucial for biological system analysis.

Keywords:
collective variablesenhanced samplingmolecular dynamicsrare events

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Area of Science:

  • Computational Chemistry
  • Molecular Dynamics Simulations
  • Biophysics

Background:

  • Conventional unbiased molecular dynamics (MD) simulations struggle with convergence for systems exhibiting rugged potential energy surfaces.
  • Enhanced sampling methodologies offer solutions by modifying Hamiltonians to overcome these limitations.

Purpose of the Study:

  • To introduce CHARMM-GUI Enhanced Sampler, a web-based tool for preparing enhanced sampling simulation inputs.
  • To facilitate the use of user-selected collective variables (CVs) for various enhanced sampling techniques.

Main Methods:

  • The tool supports nine enhanced sampling methods: accelerated MD, Gaussian accelerated MD, conformational flooding, metadynamics, adaptive biasing force, steered MD, temperature replica exchange MD, replica exchange solute tempering 2, and replica exchange umbrella sampling.
  • It is compatible with major MD packages: AMBER, CHARMM, GENESIS, GROMACS, NAMD, and OpenMM.
  • Users define nine common CVs (e.g., distance, angle, dihedral, RMSD, radius of gyration, coordination numbers) through an intuitive web interface.

Main Results:

  • CHARMM-GUI Enhanced Sampler streamlines the setup of complex enhanced sampling simulations.
  • The tool has been tested on biological systems, demonstrating the efficiency of enhanced sampling over conventional MD.
  • Optimized system-dependent parameters are provided to ensure meaningful simulation outcomes.

Conclusions:

  • CHARMM-GUI Enhanced Sampler significantly lowers the barrier for researchers to implement advanced enhanced sampling techniques.
  • This tool empowers scientists to gain deeper insights into complex molecular systems that are intractable with standard MD simulations.