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HIV latency and integration site placement in five cell-based models

Overview of attention for article published in Retrovirology: Research & Treatment, August 2013
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1 tweeter

Citations

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93 Dimensions

Readers on

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148 Mendeley
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1 CiteULike
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Title
HIV latency and integration site placement in five cell-based models
Published in
Retrovirology: Research & Treatment, August 2013
DOI 10.1186/1742-4690-10-90
Pubmed ID
Authors

Scott Sherrill-Mix, Mary K Lewinski, Marylinda Famiglietti, Alberto Bosque, Nirav Malani, Karen E Ocwieja, Charles C Berry, David Looney, Liang Shan, Luis M Agosto, Matthew J Pace, Robert F Siliciano, Una O’Doherty, John Guatelli, Vicente Planelles, Frederic D Bushman

Abstract

HIV infection can be treated effectively with antiretroviral agents, but the persistence of a latent reservoir of integrated proviruses prevents eradication of HIV from infected individuals. The chromosomal environment of integrated proviruses has been proposed to influence HIV latency, but the determinants of transcriptional repression have not been fully clarified, and it is unclear whether the same molecular mechanisms drive latency in different cell culture models.

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 148 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
United Kingdom 1 <1%
Denmark 1 <1%
Germany 1 <1%
Unknown 143 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 27%
Researcher 34 23%
Student > Bachelor 16 11%
Student > Master 14 9%
Professor 9 6%
Other 20 14%
Unknown 15 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 49 33%
Biochemistry, Genetics and Molecular Biology 33 22%
Medicine and Dentistry 22 15%
Immunology and Microbiology 16 11%
Engineering 3 2%
Other 8 5%
Unknown 17 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 August 2013.
All research outputs
#4,606,221
of 6,228,730 outputs
Outputs from Retrovirology: Research & Treatment
#344
of 450 outputs
Outputs of similar age
#72,582
of 108,416 outputs
Outputs of similar age from Retrovirology: Research & Treatment
#24
of 32 outputs
Altmetric has tracked 6,228,730 research outputs across all sources so far. This one is in the 15th percentile – i.e., 15% of other outputs scored the same or lower than it.
So far Altmetric has tracked 450 research outputs from this source. They receive a mean Attention Score of 3.5. 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 108,416 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.