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Reverse engineering of gene regulatory networks: a finite state linear model

Overview of attention for article published in Genome Biology, April 2003
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
16 Mendeley
citeulike
1 CiteULike
connotea
2 Connotea
Title
Reverse engineering of gene regulatory networks: a finite state linear model
Published in
Genome Biology, April 2003
DOI 10.1186/gb-2003-4-6-p5
Authors

Alvis Brazma, Thomas Schlitt

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 6%
United States 1 6%
Italy 1 6%
Unknown 13 81%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 31%
Professor 3 19%
Student > Doctoral Student 2 13%
Student > Ph. D. Student 2 13%
Professor > Associate Professor 2 13%
Other 2 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 38%
Computer Science 3 19%
Biochemistry, Genetics and Molecular Biology 2 13%
Business, Management and Accounting 1 6%
Chemical Engineering 1 6%
Other 2 13%
Unknown 1 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 14 December 2016.
All research outputs
#6,597,135
of 25,371,288 outputs
Outputs from Genome Biology
#3,145
of 4,467 outputs
Outputs of similar age
#16,137
of 54,923 outputs
Outputs of similar age from Genome Biology
#5
of 23 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 29th percentile – i.e., 29% 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 54,923 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 70% of its contemporaries.
We're also able to compare this research output to 23 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.