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The Multiscale Systems Immunology project: software for cell-based immunological simulation

Overview of attention for article published in Source Code for Biology and Medicine, April 2008
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#34 of 127)
  • Good Attention Score compared to outputs of the same age (72nd percentile)

Mentioned by

wikipedia
1 Wikipedia page
q&a
1 Q&A thread

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
56 Mendeley
citeulike
1 CiteULike
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Title
The Multiscale Systems Immunology project: software for cell-based immunological simulation
Published in
Source Code for Biology and Medicine, April 2008
DOI 10.1186/1751-0473-3-6
Pubmed ID
Authors

Faheem Mitha, Timothy A Lucas, Feng Feng, Thomas B Kepler, Cliburn Chan

Abstract

Computer simulations are of increasing importance in modeling biological phenomena. Their purpose is to predict behavior and guide future experiments. The aim of this project is to model the early immune response to vaccination by an agent based immune response simulation that incorporates realistic biophysics and intracellular dynamics, and which is sufficiently flexible to accurately model the multi-scale nature and complexity of the immune system, while maintaining the high performance critical to scientific computing.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
United Kingdom 2 4%
Germany 1 2%
Chile 1 2%
Afghanistan 1 2%
Russia 1 2%
Unknown 48 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 38%
Student > Ph. D. Student 15 27%
Student > Postgraduate 4 7%
Student > Master 4 7%
Professor > Associate Professor 3 5%
Other 4 7%
Unknown 5 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 39%
Medicine and Dentistry 9 16%
Computer Science 7 13%
Engineering 4 7%
Biochemistry, Genetics and Molecular Biology 3 5%
Other 6 11%
Unknown 5 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 29 May 2020.
All research outputs
#5,503,975
of 22,661,413 outputs
Outputs from Source Code for Biology and Medicine
#34
of 127 outputs
Outputs of similar age
#22,117
of 79,838 outputs
Outputs of similar age from Source Code for Biology and Medicine
#1
of 1 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has gotten more attention than average, scoring higher than 73% 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 79,838 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 72% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them