Data Sorting
Data Sorting - Related Videos
10:31
A Visual Guide to Sorting Electrophysiological Recordings Using 'SpikeSorter'
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Cited by 8 •
2017
The article shows how to use the program SpikeSorter to detect and sort spikes in extracellular recordings made with multi-electrode arrays.
08:37
Setting a Successful Sorting for Extracellular Vesicle Isolation
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Cited by 2 •
2024
This protocol provides a detailed description of sorting extracellular vesicles (EVs) released by mesenchymal stromal cells. In particular, it focuses on the instrument setting and the optimization of the sorting conditions. The goal is to sort extracellular vesicles while preserving their characteristics.
07:19
Executive Function and the Dimensional Change Card Sort Task
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2023
Source: Laboratories of Nicholaus Noles and Judith Danovitch—University of Louisville Infants are born with amazing cognitive resources at their disposal, but they don’t know how to use them effectively. In order to harness the power of their brains, humans must develop high-level cognitive processes that manage basic brain functions. These processes make up what psychologists refer to as executive function. Executive function is a key factor in many self-regulatory behaviors, including forming...
07:47
Isolation of Lung Retinoid-Containing Cells by Cell Sorting
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Cited by 1 •
2025
The protocol described below is a simple and effective way to isolate retinoid-containing cells from highly heterogeneous lung cell populations by making use of specific retinoid autofluorescence and by employing fluorescence-activated cell sorting.
13:35
Fluorescence Activated Cell Sorting of Plant Protoplasts
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Cited by 83 •
2010
A method for isolating specific cell types from plant material is demonstrated. This technique employs transgenic marker lines expressing fluorescent proteins in particular cell types, cellular dissociation and Fluorescence Activated Cell Sorting. Additionally, a growth setup is established here that facilitates treatment of Arabidopsis thaliana seedlings prior to cell sorting.
FAQs
Preserving record-level associations is essential because an observation usually contains several related values. When records are ordered by one variable, the corresponding values in other variables must move with them. Otherwise, the dataset no longer represents the original observations, and later inspection of relationships, rankings, or statistical summaries may be based on mismatched information.
Ascending and descending numerical order place low or high observations at the most visible ends, while alphabetical, date-based, or ranked-score ordering organizes nonnumeric information differently. The selected rule should match the variable being examined. Choosing an appropriate order makes extremes, repeated categories, chronological patterns, or rank positions easier to inspect.
Once values are ordered, unusually large gaps, unexpected repetitions, or implausible positions become easier to notice. Comparing the sequence with expected values or categories can draw attention to possible entry errors and potential outliers. Sorting therefore supports an initial quality check before researchers proceed to more formal statistical analysis.
A median depends on the ordered position of observations, so sorting places values in the sequence needed to identify the central location. The same ordered sequence allows researchers to assign ranks consistently and organize repeated values for frequency tables. These results can then support statistical summaries and visualizations within the dataset.
First identify the variable or variables that determine the order. Next choose the rule, such as ascending, descending, alphabetical, date, or ranked-score order. Apply it to complete records rather than isolated cells, then inspect the resulting sequence for extremes, gaps, repetitions, and possible errors before calculating summaries or creating visualizations.
An ordered dataset gives researchers a clearer basis for grouping repeated observations into frequency tables and for viewing how values are distributed across a sequence. It can also make minimums, maximums, gaps, trends, and potential outliers easier to recognize. As a preparation step, sorting improves organization before results are displayed or analyzed.