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Related Concept Videos

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: Overview01:06

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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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Sample Handling01:02

Sample Handling

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Transportation of samples from the collection point to the laboratory, as well as storage and preservation techniques, are crucial for maintaining sample integrity and ensuring accurate and reliable test results.
Samples should be transported carefully from collection points to the laboratory. They should be properly sealed and clearly labeled to prevent cross-contamination. To preserve the sample integrity, optimal temperature conditions during transport are essential. This could involve using...
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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...
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Systematic Sampling Method01:17

Systematic 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.
Systematic sampling is one of the simplest methods...
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Sampling Plans01:23

Sampling Plans

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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.
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Efficient sample tracking with OpenLabFramework.

Markus List1, Steffen Schmidt2, Jakub Trojnar3

  • 11] Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, University of Southern Denmark, Odense, DK [2] Institute of Molecular Medicin (IMM), University of Southern Denmark, Odense, DK [3] Clinical Institute (CI), University of Southern Denmark, Odense, DK.

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Summary
This summary is machine-generated.

New technologies increase experimental data, making spreadsheets inadequate. OpenLabFramework offers a customizable web-application for tracking biological samples, especially vector clones and cell lines, enhancing lab productivity.

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Area of Science:

  • Biomedical Research
  • Laboratory Management
  • Bioinformatics

Background:

  • Advancements in biomedical research technologies have significantly increased experimental throughput and project complexity.
  • Traditional spreadsheet methods are insufficient for managing large-scale sample data generated in modern research.
  • Existing laboratory information management systems (LIMS) often lack domain-specific solutions, particularly for biological sample libraries.

Purpose of the Study:

  • To introduce OpenLabFramework, a novel web-application designed for comprehensive sample tracking.
  • To address the unmet need for managing vector clone and genetically engineered cell line libraries.
  • To provide a flexible and extensible platform for diverse biological materials and data types.

Main Methods:

  • Development of a web-based application, OpenLabFramework.
  • Implementation of a customizable sample tracking mechanism.
  • Integration of support for mobile devices and barcoded labels for enhanced usability.

Main Results:

  • OpenLabFramework effectively manages libraries of vector clones and genetically engineered cell lines.
  • The application's open architecture allows for extension to other biological materials and functional data.
  • Customizable tracking and mobile/barcode support improve laboratory productivity.

Conclusions:

  • OpenLabFramework provides a state-of-the-art solution for managing complex biological sample libraries.
  • The system's flexibility and extensibility make it suitable for various research domains.
  • This tool enhances experimental throughput and data management in biomedical research.