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Design and implementation of microarray gene expression markup language (MAGE-ML)

Overview of attention for article published in Genome Biology (Online Edition), August 2002
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)

Mentioned by

policy
1 policy source

Citations

dimensions_citation
332 Dimensions

Readers on

mendeley
133 Mendeley
citeulike
6 CiteULike
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Title
Design and implementation of microarray gene expression markup language (MAGE-ML)
Published in
Genome Biology (Online Edition), August 2002
DOI 10.1186/gb-2002-3-9-research0046
Authors

Paul T Spellman, Michael Miller, Jason Stewart, Charles Troup, Ugis Sarkans, Steve Chervitz, Derek Bernhart, Gavin Sherlock, Catherine Ball, Marc Lepage, Marcin Swiatek, WL Marks, Jason Goncalves, Scott Markel, Daniel Iordan, Mohammadreza Shojatalab, Angel Pizarro, Joe White, Robert Hubley, Eric Deutsch, Martin Senger, Bruce J Aronow, Alan Robinson, Doug Bassett, Christian J Stoeckert, Alvis Brazma

Mendeley readers

The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 7%
Germany 3 2%
United Kingdom 3 2%
Netherlands 2 2%
Norway 1 <1%
Switzerland 1 <1%
Finland 1 <1%
Canada 1 <1%
Brazil 1 <1%
Other 4 3%
Unknown 107 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 49 37%
Student > Ph. D. Student 27 20%
Professor > Associate Professor 17 13%
Other 11 8%
Student > Master 9 7%
Other 16 12%
Unknown 4 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 74 56%
Computer Science 23 17%
Medicine and Dentistry 10 8%
Biochemistry, Genetics and Molecular Biology 8 6%
Engineering 4 3%
Other 8 6%
Unknown 6 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 01 January 2007.
All research outputs
#5,609,310
of 17,364,317 outputs
Outputs from Genome Biology (Online Edition)
#2,722
of 3,593 outputs
Outputs of similar age
#103,502
of 273,547 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 17,364,317 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,593 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one is in the 16th percentile – i.e., 16% 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 273,547 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 58% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them