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An unbiased metagenomic search for infectious agents using monozygotic twins discordant for chronic fatigue

Overview of attention for article published in BMC Microbiology, January 2011
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 tweeter
peer_reviews
1 peer review site

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
62 Mendeley
citeulike
1 CiteULike
Title
An unbiased metagenomic search for infectious agents using monozygotic twins discordant for chronic fatigue
Published in
BMC Microbiology, January 2011
DOI 10.1186/1471-2180-11-2
Pubmed ID
Authors

Patrick F Sullivan, Tobias Allander, Fredrik Lysholm, Shan Goh, Bengt Persson, Andreas Jacks, Birgitta Evengård, Nancy L Pedersen, Björn Andersson

Abstract

Chronic fatigue syndrome is an idiopathic syndrome widely suspected of having an infectious or immune etiology. We applied an unbiased metagenomic approach to try to identify known or novel infectious agents in the serum of 45 cases with chronic fatigue syndrome or idiopathic chronic fatigue. Controls were the unaffected monozygotic co-twins of cases, and serum samples were obtained at the same place and time.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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%
France 2 3%
Brazil 2 3%
United Kingdom 2 3%
Sweden 1 2%
India 1 2%
Germany 1 2%
Unknown 51 82%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 27%
Professor 11 18%
Student > Ph. D. Student 10 16%
Student > Master 8 13%
Student > Bachelor 4 6%
Other 11 18%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 50%
Medicine and Dentistry 9 15%
Biochemistry, Genetics and Molecular Biology 6 10%
Psychology 3 5%
Immunology and Microbiology 3 5%
Other 4 6%
Unknown 6 10%

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 27 May 2014.
All research outputs
#1,907,412
of 3,814,345 outputs
Outputs from BMC Microbiology
#335
of 775 outputs
Outputs of similar age
#50,035
of 114,826 outputs
Outputs of similar age from BMC Microbiology
#23
of 53 outputs
Altmetric has tracked 3,814,345 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 775 research outputs from this source. They receive a mean Attention Score of 2.8. This one has gotten more attention than average, scoring higher than 50% 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 114,826 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 50% of its contemporaries.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.