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Mapping the stabilome: a novel computational method for classifying metabolic protein stability

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

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
33 Mendeley
citeulike
1 CiteULike
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Title
Mapping the stabilome: a novel computational method for classifying metabolic protein stability
Published in
BMC Systems Biology, June 2012
DOI 10.1186/1752-0509-6-60
Pubmed ID
Authors

Ralph Patrick, Kim-Anh Lê Cao, Melissa Davis, Bostjan Kobe, Mikael Bodén

Abstract

The half-life of a protein is regulated by a range of system properties, including the abundance of components of the degradative machinery and protein modifiers. It is also influenced by protein-specific properties, such as a protein's structural make-up and interaction partners. New experimental techniques coupled with powerful data integration methods now enable us to not only investigate what features govern protein stability in general, but also to build models that identify what properties determine each protein's metabolic stability.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 3%
Unknown 32 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 42%
Student > Master 5 15%
Student > Ph. D. Student 5 15%
Professor > Associate Professor 3 9%
Student > Bachelor 2 6%
Other 2 6%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 52%
Biochemistry, Genetics and Molecular Biology 4 12%
Computer Science 3 9%
Social Sciences 1 3%
Immunology and Microbiology 1 3%
Other 4 12%
Unknown 3 9%

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 20 September 2012.
All research outputs
#11,210,629
of 18,796,975 outputs
Outputs from BMC Systems Biology
#498
of 1,127 outputs
Outputs of similar age
#75,179
of 137,402 outputs
Outputs of similar age from BMC Systems Biology
#12
of 30 outputs
Altmetric has tracked 18,796,975 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,127 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 53% 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 137,402 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30 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 63% of its contemporaries.