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TrackArt: the user friendly interface for single molecule tracking data analysis and simulation applied to complex diffusion in mica supported lipid bilayers

Overview of attention for article published in BMC Research Notes, May 2014
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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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

blogs
1 blog
twitter
1 tweeter

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
53 Mendeley
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Title
TrackArt: the user friendly interface for single molecule tracking data analysis and simulation applied to complex diffusion in mica supported lipid bilayers
Published in
BMC Research Notes, May 2014
DOI 10.1186/1756-0500-7-274
Pubmed ID
Authors

Artur Matysik, Rachel S Kraut

Abstract

Single molecule tracking (SMT) analysis of fluorescently tagged lipid and protein probes is an attractive alternative to ensemble averaged methods such as fluorescence correlation spectroscopy (FCS) or fluorescence recovery after photobleaching (FRAP) for measuring diffusion in artificial and plasma membranes. The meaningful estimation of diffusion coefficients and their errors is however not straightforward, and is heavily dependent on sample type, acquisition method, and equipment used. Many approaches require advanced computing and programming skills for their implementation.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
Mexico 1 2%
United States 1 2%
Germany 1 2%
Unknown 49 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 32%
Researcher 11 21%
Student > Bachelor 5 9%
Professor > Associate Professor 5 9%
Student > Master 5 9%
Other 5 9%
Unknown 5 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 23%
Physics and Astronomy 8 15%
Chemistry 7 13%
Biochemistry, Genetics and Molecular Biology 6 11%
Engineering 4 8%
Other 10 19%
Unknown 6 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 24 July 2015.
All research outputs
#3,972,755
of 22,754,104 outputs
Outputs from BMC Research Notes
#589
of 4,262 outputs
Outputs of similar age
#39,786
of 227,852 outputs
Outputs of similar age from BMC Research Notes
#13
of 85 outputs
Altmetric has tracked 22,754,104 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,262 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 86% 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 227,852 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 82% of its contemporaries.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.