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Integration of gene expression, clinical, and epidemiologic data to characterize Chronic Fatigue Syndrome

Overview of attention for article published in Journal of Translational Medicine, December 2003
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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 (81st percentile)

Mentioned by

patent
2 patents
wikipedia
3 Wikipedia pages

Citations

dimensions_citation
52 Dimensions

Readers on

mendeley
37 Mendeley
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Title
Integration of gene expression, clinical, and epidemiologic data to characterize Chronic Fatigue Syndrome
Published in
Journal of Translational Medicine, December 2003
DOI 10.1186/1479-5876-1-10
Pubmed ID
Authors

Toni Whistler, Elizabeth R Unger, Rosane Nisenbaum, Suzanne D Vernon

Abstract

BACKGROUND: Chronic fatigue syndrome (CFS) has no diagnostic clinical signs or diagnostic laboratory abnormalities and it is unclear if it represents a single illness. The CFS research case definition recommends stratifying subjects by co-morbid conditions, fatigue level and duration, or functional impairment. But to date, this analysis approach has not yielded any further insight into CFS pathogenesis. This study used the integration of peripheral blood gene expression results with epidemiologic and clinical data to determine whether CFS is a single or heterogeneous illness. RESULTS: CFS subjects were grouped by several clinical and epidemiological variables thought to be important in defining the illness. Statistical tests and cluster analysis were used to distinguish CFS subjects and identify differentially expressed genes. These genes were identified only when CFS subjects were grouped according to illness onset and the majority of genes were involved in pathways of purine and pyrimidine metabolism, glycolysis, oxidative phosphorylation, and glucose metabolism. CONCLUSION: These results provide a physiologic basis that suggests CFS is a heterogeneous illness. The differentially expressed genes imply fundamental metabolic perturbations that will be further investigated and illustrates the power of microarray technology for furthering our understanding CFS.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 8%
Spain 1 3%
Portugal 1 3%
Unknown 32 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 32%
Professor > Associate Professor 5 14%
Other 3 8%
Student > Doctoral Student 3 8%
Student > Bachelor 2 5%
Other 7 19%
Unknown 5 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 24%
Medicine and Dentistry 6 16%
Biochemistry, Genetics and Molecular Biology 4 11%
Engineering 3 8%
Computer Science 2 5%
Other 6 16%
Unknown 7 19%
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 22 January 2015.
All research outputs
#5,446,994
of 25,374,647 outputs
Outputs from Journal of Translational Medicine
#974
of 4,635 outputs
Outputs of similar age
#16,716
of 142,657 outputs
Outputs of similar age from Journal of Translational Medicine
#2
of 4 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,635 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has done well, scoring higher than 77% 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 142,657 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.