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Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics

Overview of attention for article published in BMC Systems Biology, March 2012
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
66 Mendeley
citeulike
2 CiteULike
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Title
Simplification of biochemical models: a general approach based on the analysis of the impact of individual species and reactions on the systems dynamics
Published in
BMC Systems Biology, March 2012
DOI 10.1186/1752-0509-6-14
Pubmed ID
Authors

Irina Surovtsova, Irina Surovtsova, Natalia Simus, Katrin Hübner, Sven Sahle, Ursula Kummer

Abstract

Given the complex mechanisms underlying biochemical processes systems biology researchers tend to build ever increasing computational models. However, dealing with complex systems entails a variety of problems, e.g. difficult intuitive understanding, variety of time scales or non-identifiable parameters. Therefore, methods are needed that, at least semi-automatically, help to elucidate how the complexity of a model can be reduced such that important behavior is maintained and the predictive capacity of the model is increased. The results should be easily accessible and interpretable. In the best case such methods may also provide insight into fundamental biochemical mechanisms.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
United Kingdom 1 2%
Netherlands 1 2%
Russia 1 2%
Germany 1 2%
Unknown 60 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 22 33%
Student > Ph. D. Student 16 24%
Student > Master 8 12%
Student > Bachelor 7 11%
Professor > Associate Professor 5 8%
Other 5 8%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 38%
Biochemistry, Genetics and Molecular Biology 11 17%
Engineering 7 11%
Computer Science 3 5%
Chemistry 3 5%
Other 8 12%
Unknown 9 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 06 March 2012.
All research outputs
#2,088,219
of 4,506,051 outputs
Outputs from BMC Systems Biology
#255
of 670 outputs
Outputs of similar age
#27,956
of 76,965 outputs
Outputs of similar age from BMC Systems Biology
#6
of 12 outputs
Altmetric has tracked 4,506,051 research outputs across all sources so far. This one has received more attention than most of these and is in the 52nd percentile.
So far Altmetric has tracked 670 research outputs from this source. They receive a mean Attention Score of 2.8. This one has gotten more attention than average, scoring higher than 60% 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 76,965 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 62% of its contemporaries.
We're also able to compare this research output to 12 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 50% of its contemporaries.