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RNAseq analysis of treatment-dependent signaling changes during inflammation in a mouse cutaneous wound healing model

Overview of attention for article published in BMC Genomics, November 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
2 tweeters

Readers on

mendeley
9 Mendeley
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Title
RNAseq analysis of treatment-dependent signaling changes during inflammation in a mouse cutaneous wound healing model
Published in
BMC Genomics, November 2021
DOI 10.1186/s12864-021-08083-2
Authors

Georges St. Laurent, Ian Toma, Bernd Seilheimer, Konstantin Cesnulevicius, Myron Schultz, Michael Tackett, Jianhua Zhou, Maxim Ri, Dmitry Shtokalo, Denis Antonets, Tisha Jepson, Timothy A. McCaffrey

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 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 %
Researcher 3 33%
Other 2 22%
Student > Bachelor 2 22%
Unspecified 1 11%
Unknown 1 11%
Readers by discipline Count As %
Medicine and Dentistry 3 33%
Biochemistry, Genetics and Molecular Biology 2 22%
Unspecified 1 11%
Chemistry 1 11%
Linguistics 1 11%
Other 0 0%
Unknown 1 11%

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 26 November 2021.
All research outputs
#12,826,423
of 21,271,011 outputs
Outputs from BMC Genomics
#5,047
of 10,260 outputs
Outputs of similar age
#215,343
of 460,431 outputs
Outputs of similar age from BMC Genomics
#286
of 688 outputs
Altmetric has tracked 21,271,011 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,260 research outputs from this source. They receive a mean Attention Score of 4.6. 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 460,431 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 51% of its contemporaries.
We're also able to compare this research output to 688 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.