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When noise makes music: HIV reactivation with transcriptional noise enhancers

Overview of attention for article published in Genome Medicine, July 2014
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Title
When noise makes music: HIV reactivation with transcriptional noise enhancers
Published in
Genome Medicine, July 2014
DOI 10.1186/s13073-014-0055-9
Pubmed ID
Authors

Xu Tan, Stephen J Elledge

Abstract

Reactivating latent HIV is key to depleting the virus reservoir in AIDS patients. A recent paper has described the rationale for and discovery of a new class of drugs - transcriptional noise enhancers - that can synergize with conventional transcription activators to more effectively reactivate latently infected T cells. As well as describing a promising new strategy in the bid to find a cure for AIDS, this study more broadly highlights the utility of exploring drug combinations in treatment of human disease.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 33%
Student > Doctoral Student 2 22%
Researcher 2 22%
Student > Bachelor 1 11%
Other 1 11%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 44%
Medicine and Dentistry 2 22%
Biochemistry, Genetics and Molecular Biology 1 11%
Computer Science 1 11%
Arts and Humanities 1 11%
Other 0 0%
Attention Score in Context

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 29 July 2014.
All research outputs
#14,782,907
of 22,758,963 outputs
Outputs from Genome Medicine
#1,290
of 1,437 outputs
Outputs of similar age
#125,786
of 228,919 outputs
Outputs of similar age from Genome Medicine
#20
of 24 outputs
Altmetric has tracked 22,758,963 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,437 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.6. This one is in the 8th percentile – i.e., 8% 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 228,919 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.