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Cells in Silico – introducing a high-performance framework for large-scale tissue modeling

Overview of attention for article published in BMC Bioinformatics, October 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
5 X users

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
23 Mendeley
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Title
Cells in Silico – introducing a high-performance framework for large-scale tissue modeling
Published in
BMC Bioinformatics, October 2020
DOI 10.1186/s12859-020-03728-7
Pubmed ID
Authors

Marco Berghoff, Jakob Rosenbauer, Felix Hoffmann, Alexander Schug

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 26%
Student > Ph. D. Student 3 13%
Student > Bachelor 1 4%
Other 1 4%
Student > Doctoral Student 1 4%
Other 1 4%
Unknown 10 43%
Readers by discipline Count As %
Computer Science 5 22%
Agricultural and Biological Sciences 2 9%
Biochemistry, Genetics and Molecular Biology 1 4%
Physics and Astronomy 1 4%
Engineering 1 4%
Other 0 0%
Unknown 13 57%
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 08 October 2020.
All research outputs
#12,943,365
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#3,659
of 7,387 outputs
Outputs of similar age
#183,409
of 415,098 outputs
Outputs of similar age from BMC Bioinformatics
#83
of 181 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,387 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 gotten more attention than average, scoring higher than 50% 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 415,098 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 55% of its contemporaries.
We're also able to compare this research output to 181 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 54% of its contemporaries.