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MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis

Overview of attention for article published in BMC Bioinformatics, December 2013
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  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

Mentioned by

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4 X users

Citations

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70 Dimensions

Readers on

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178 Mendeley
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1 CiteULike
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Title
MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis
Published in
BMC Bioinformatics, December 2013
DOI 10.1186/1471-2105-14-349
Pubmed ID
Authors

Arun Shivanandan, Aleksandra Radenovic, Ivo F Sbalzarini

Abstract

Analyzing spatial distributions of objects in images is a fundamental task in many biological studies. The relative arrangement of a set of objects with respect to another set of objects contains information about potential interactions between the two sets of objects. If they do not "feel" each other's presence, their spatial distributions are expected to be independent of one another. Spatial correlations in their distributions are indicative of interactions and can be modeled by an effective interaction potential acting between the points of the two sets. This can be used to generalize co-localization analysis to spatial interaction analysis. However, no user-friendly software for this type of analysis was available so far.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 2%
Netherlands 2 1%
Czechia 1 <1%
United States 1 <1%
Unknown 171 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 24%
Researcher 37 21%
Student > Master 20 11%
Student > Doctoral Student 11 6%
Student > Bachelor 9 5%
Other 32 18%
Unknown 27 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 30%
Biochemistry, Genetics and Molecular Biology 28 16%
Engineering 13 7%
Physics and Astronomy 9 5%
Computer Science 8 4%
Other 33 19%
Unknown 34 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 18 December 2013.
All research outputs
#13,164,646
of 22,733,113 outputs
Outputs from BMC Bioinformatics
#4,003
of 7,266 outputs
Outputs of similar age
#163,315
of 306,782 outputs
Outputs of similar age from BMC Bioinformatics
#49
of 105 outputs
Altmetric has tracked 22,733,113 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,266 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 42nd percentile – i.e., 42% 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 306,782 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 105 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.