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Attention Score in Context
Title |
scDual-Seq: mapping the gene regulatory program of Salmonella infection by host and pathogen single-cell RNA-sequencing
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Published in |
Genome Biology, October 2017
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DOI | 10.1186/s13059-017-1340-x |
Pubmed ID | |
Authors |
Gal Avital, Roi Avraham, Amy Fan, Tamar Hashimshony, Deborah T. Hung, Itai Yanai |
Abstract |
The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-sequencing method, scDual-Seq, that simultaneously captures both host and pathogen transcriptomes. We use it to study the process of infection of individual mouse macrophages with the intracellular pathogen Salmonella typhimurium. Among the infected macrophages, we find three subpopulations and we show evidence for a linear progression through these subpopulations, supporting a model in which these three states correspond to consecutive stages of infection. |
X Demographics
The data shown below were collected from the profiles of 41 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 8 | 20% |
Australia | 3 | 7% |
Israel | 2 | 5% |
Germany | 2 | 5% |
Italy | 1 | 2% |
Sweden | 1 | 2% |
France | 1 | 2% |
Chile | 1 | 2% |
India | 1 | 2% |
Other | 5 | 12% |
Unknown | 16 | 39% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 25 | 61% |
Members of the public | 15 | 37% |
Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 210 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 210 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 56 | 27% |
Researcher | 38 | 18% |
Student > Master | 16 | 8% |
Student > Doctoral Student | 15 | 7% |
Student > Bachelor | 13 | 6% |
Other | 19 | 9% |
Unknown | 53 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 54 | 26% |
Agricultural and Biological Sciences | 34 | 16% |
Immunology and Microbiology | 33 | 16% |
Medicine and Dentistry | 10 | 5% |
Engineering | 6 | 3% |
Other | 15 | 7% |
Unknown | 58 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 39. 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 12 August 2022.
All research outputs
#1,046,575
of 25,382,440 outputs
Outputs from Genome Biology
#753
of 4,468 outputs
Outputs of similar age
#21,816
of 339,185 outputs
Outputs of similar age from Genome Biology
#24
of 60 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has done well, scoring higher than 83% 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 339,185 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 60 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 60% of its contemporaries.