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CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data

Overview of attention for article published in BMC Bioinformatics, November 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

twitter
14 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
32 Dimensions

Readers on

mendeley
85 Mendeley
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Title
CellProfiler Tracer: exploring and validating high-throughput, time-lapse microscopy image data
Published in
BMC Bioinformatics, November 2015
DOI 10.1186/s12859-015-0759-x
Pubmed ID
Authors

Mark-Anthony Bray, Anne E. Carpenter

Abstract

Time-lapse analysis of cellular images is an important and growing need in biology. Algorithms for cell tracking are widely available; what researchers have been missing is a single open-source software package to visualize standard tracking output (from software like CellProfiler) in a way that allows convenient assessment of track quality, especially for researchers tuning tracking parameters for high-content time-lapse experiments. This makes quality assessment and algorithm adjustment a substantial challenge, particularly when dealing with hundreds of time-lapse movies collected in a high-throughput manner. We present CellProfiler Tracer, a free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts. CellProfiler Tracer is a useful, free tool for inspection and quality control of object tracking data, available from http://www.cellprofiler.org/tracer/ .

Twitter Demographics

The data shown below were collected from the profiles of 14 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 1%
Switzerland 1 1%
Unknown 83 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 24%
Student > Master 16 19%
Student > Ph. D. Student 15 18%
Student > Bachelor 6 7%
Student > Doctoral Student 4 5%
Other 12 14%
Unknown 12 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 26%
Biochemistry, Genetics and Molecular Biology 17 20%
Computer Science 12 14%
Engineering 9 11%
Immunology and Microbiology 3 4%
Other 7 8%
Unknown 15 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 19 November 2019.
All research outputs
#1,693,869
of 15,055,070 outputs
Outputs from BMC Bioinformatics
#665
of 5,549 outputs
Outputs of similar age
#40,527
of 285,763 outputs
Outputs of similar age from BMC Bioinformatics
#53
of 472 outputs
Altmetric has tracked 15,055,070 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,549 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has done well, scoring higher than 87% of its peers.
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 285,763 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 472 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.