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Systematic integration of experimental data and models in systems biology

Overview of attention for article published in BMC Bioinformatics, November 2010
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

blogs
1 blog
wikipedia
1 Wikipedia page

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
157 Mendeley
citeulike
17 CiteULike
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Title
Systematic integration of experimental data and models in systems biology
Published in
BMC Bioinformatics, November 2010
DOI 10.1186/1471-2105-11-582
Pubmed ID
Authors

Peter Li, Joseph O Dada, Daniel Jameson, Irena Spasic, Neil Swainston, Kathleen Carroll, Warwick Dunn, Farid Khan, Naglis Malys, Hanan L Messiha, Evangelos Simeonidis, Dieter Weichart, Catherine Winder, Jill Wishart, David S Broomhead, Carole A Goble, Simon J Gaskell, Douglas B Kell, Hans V Westerhoff, Pedro Mendes, Norman W Paton

Abstract

The behaviour of biological systems can be deduced from their mathematical models. However, multiple sources of data in diverse forms are required in the construction of a model in order to define its components and their biochemical reactions, and corresponding parameters. Automating the assembly and use of systems biology models is dependent upon data integration processes involving the interoperation of data and analytical resources.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 7 4%
United States 5 3%
Germany 3 2%
Japan 3 2%
France 2 1%
Canada 2 1%
Turkey 1 <1%
Hong Kong 1 <1%
Netherlands 1 <1%
Other 5 3%
Unknown 127 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 43 27%
Student > Ph. D. Student 28 18%
Professor > Associate Professor 18 11%
Other 14 9%
Professor 12 8%
Other 29 18%
Unknown 13 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 73 46%
Computer Science 23 15%
Biochemistry, Genetics and Molecular Biology 10 6%
Medicine and Dentistry 9 6%
Engineering 9 6%
Other 10 6%
Unknown 23 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 12 February 2012.
All research outputs
#3,656,524
of 22,790,780 outputs
Outputs from BMC Bioinformatics
#1,348
of 7,280 outputs
Outputs of similar age
#23,926
of 180,387 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 61 outputs
Altmetric has tracked 22,790,780 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 81% 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 180,387 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.