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An automated cell-counting algorithm for fluorescently-stained cells in migration assays

Overview of attention for article published in Biological Procedures Online, October 2011
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Title
An automated cell-counting algorithm for fluorescently-stained cells in migration assays
Published in
Biological Procedures Online, October 2011
DOI 10.1186/1480-9222-13-9
Pubmed ID
Authors

Baraa K Al-Khazraji, Philip J Medeiros, Nicole M Novielli, Dwayne N Jackson

Abstract

A cell-counting algorithm, developed in Matlab®, was created to efficiently count migrated fluorescently-stained cells on membranes from migration assays. At each concentration of cells used (10,000, and 100,000 cells), images were acquired at 2.5 ×, 5 ×, and 10 × objective magnifications. Automated cell counts strongly correlated to manual counts (r2 = 0.99, P < 0.0001 for a total of 47 images), with no difference in the measurements between methods under all conditions. We conclude that our automated method is accurate, more efficient, and void of variability and potential observer bias normally associated with manual counting.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Sweden 1 2%
Unknown 40 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 36%
Student > Master 8 19%
Student > Bachelor 6 14%
Student > Postgraduate 3 7%
Researcher 3 7%
Other 4 10%
Unknown 3 7%
Readers by discipline Count As %
Engineering 11 26%
Agricultural and Biological Sciences 10 24%
Biochemistry, Genetics and Molecular Biology 5 12%
Neuroscience 4 10%
Computer Science 3 7%
Other 6 14%
Unknown 3 7%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 August 2012.
All research outputs
#18,312,024
of 22,673,450 outputs
Outputs from Biological Procedures Online
#131
of 164 outputs
Outputs of similar age
#114,896
of 139,289 outputs
Outputs of similar age from Biological Procedures Online
#2
of 2 outputs
Altmetric has tracked 22,673,450 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 164 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 139,289 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.