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Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient

Overview of attention for article published in BioData Mining, August 2021
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Mentioned by

twitter
1 tweeter

Readers on

mendeley
10 Mendeley
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Title
Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient
Published in
BioData Mining, August 2021
DOI 10.1186/s13040-021-00263-w
Pubmed ID
Authors

Haripriya Harikumar, Thomas P. Quinn, Santu Rana, Sunil Gupta, Svetha Venkatesh

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

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 30%
Other 2 20%
Student > Doctoral Student 1 10%
Student > Ph. D. Student 1 10%
Librarian 1 10%
Other 0 0%
Unknown 2 20%
Readers by discipline Count As %
Medicine and Dentistry 2 20%
Agricultural and Biological Sciences 2 20%
Computer Science 2 20%
Biochemistry, Genetics and Molecular Biology 1 10%
Unknown 3 30%

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 06 August 2021.
All research outputs
#17,052,420
of 19,280,406 outputs
Outputs from BioData Mining
#264
of 285 outputs
Outputs of similar age
#266,228
of 334,853 outputs
Outputs of similar age from BioData Mining
#1
of 1 outputs
Altmetric has tracked 19,280,406 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 285 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 1st percentile – i.e., 1% 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 334,853 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them