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

Mentioned by

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2 X users

Citations

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21 Dimensions

Readers on

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66 Mendeley
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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, 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.

X Demographics

X Demographics

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

Geographical breakdown

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

Demographic breakdown

Readers by professional status Count As %
Researcher 21 32%
Student > Ph. D. Student 16 24%
Student > Master 8 12%
Student > Bachelor 7 11%
Professor > Associate Professor 5 8%
Other 5 8%
Unknown 4 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 25 38%
Biochemistry, Genetics and Molecular Biology 10 15%
Engineering 7 11%
Computer Science 5 8%
Mathematics 2 3%
Other 8 12%
Unknown 9 14%
Attention Score in Context

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
#16,580,596
of 25,374,917 outputs
Outputs from BMC Systems Biology
#607
of 1,132 outputs
Outputs of similar age
#106,758
of 168,628 outputs
Outputs of similar age from BMC Systems Biology
#4
of 9 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 45th percentile – i.e., 45% 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 168,628 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.