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BactImAS: a platform for processing and analysis of bacterial time-lapse microscopy movies

Overview of attention for article published in BMC Bioinformatics, July 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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6 X users
facebook
1 Facebook page

Citations

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15 Dimensions

Readers on

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47 Mendeley
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Title
BactImAS: a platform for processing and analysis of bacterial time-lapse microscopy movies
Published in
BMC Bioinformatics, July 2014
DOI 10.1186/1471-2105-15-251
Pubmed ID
Authors

Igor Mekterović, Darko Mekterović, željka Maglica

Abstract

The software available to date for analyzing image sequences from time-lapse microscopy works only for certain bacteria and under limited conditions. These programs, mostly MATLAB-based, fail for microbes with irregular shape, indistinct cell division sites, or that grow in closely packed microcolonies. Unfortunately, many organisms of interest have these characteristics, and analyzing their image sequences has been limited to time consuming manual processing.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Germany 1 2%
Brazil 1 2%
Unknown 44 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 21%
Researcher 9 19%
Student > Master 8 17%
Student > Bachelor 5 11%
Student > Doctoral Student 3 6%
Other 7 15%
Unknown 5 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 26%
Computer Science 7 15%
Medicine and Dentistry 4 9%
Biochemistry, Genetics and Molecular Biology 4 9%
Engineering 4 9%
Other 9 19%
Unknown 7 15%
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 25 July 2014.
All research outputs
#13,177,677
of 22,758,963 outputs
Outputs from BMC Bioinformatics
#3,999
of 7,272 outputs
Outputs of similar age
#106,522
of 228,769 outputs
Outputs of similar age from BMC Bioinformatics
#67
of 126 outputs
Altmetric has tracked 22,758,963 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 7,272 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 228,769 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 126 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.