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A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue

Overview of attention for article published in BMC Systems Biology, January 2011
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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 (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

twitter
3 tweeters
patent
4 patents

Citations

dimensions_citation
67 Dimensions

Readers on

mendeley
62 Mendeley
citeulike
2 CiteULike
Title
A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue
Published in
BMC Systems Biology, January 2011
DOI 10.1186/1752-0509-5-168
Pubmed ID
Authors

Walter K Schlage, Jurjen W Westra, Stephan Gebel, Natalie L Catlett, Carole Mathis, Brian P Frushour, Arnd Hengstermann, Aaron Van Hooser, Carine Poussin, Ben Wong, Michael Lietz, Jennifer Park, David Drubin, Emilija Veljkovic, Manuel C Peitsch, Julia Hoeng, Renee Deehan

Abstract

Humans and other organisms are equipped with a set of responses that can prevent damage from exposure to a multitude of endogenous and environmental stressors. If these stress responses are overwhelmed, this can result in pathogenesis of diseases, which is reflected by an increased development of, e.g., pulmonary and cardiac diseases in humans exposed to chronic levels of environmental stress, including inhaled cigarette smoke (CS). Systems biology data sets (e.g., transcriptomics, phosphoproteomics, metabolomics) could enable comprehensive investigation of the biological impact of these stressors. However, detailed mechanistic networks are needed to determine which specific pathways are activated in response to different stressors and to drive the qualitative and eventually quantitative assessment of these data. A current limiting step in this process is the availability of detailed mechanistic networks that can be used as an analytical substrate.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Canada 1 2%
India 1 2%
Puerto Rico 1 2%
Germany 1 2%
Luxembourg 1 2%
Unknown 55 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 29%
Researcher 17 27%
Other 6 10%
Student > Master 5 8%
Professor > Associate Professor 5 8%
Other 9 15%
Unknown 2 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 37%
Biochemistry, Genetics and Molecular Biology 12 19%
Computer Science 7 11%
Engineering 5 8%
Medicine and Dentistry 3 5%
Other 7 11%
Unknown 5 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 31 January 2017.
All research outputs
#933,054
of 11,111,250 outputs
Outputs from BMC Systems Biology
#52
of 964 outputs
Outputs of similar age
#7,709
of 97,140 outputs
Outputs of similar age from BMC Systems Biology
#2
of 45 outputs
Altmetric has tracked 11,111,250 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 964 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 94% 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 97,140 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.