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Synthetic lethality-mediated precision oncology via the tumor transcriptome

Overview of attention for article published in Cell, April 2021
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Citations

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62 Dimensions

Readers on

mendeley
294 Mendeley
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Title
Synthetic lethality-mediated precision oncology via the tumor transcriptome
Published in
Cell, April 2021
DOI 10.1016/j.cell.2021.03.030
Pubmed ID
Authors

Joo Sang Lee, Nishanth Ulhas Nair, Gal Dinstag, Lesley Chapman, Youngmin Chung, Kun Wang, Sanju Sinha, Hongui Cha, Dasol Kim, Alexander V Schperberg, Ajay Srinivasan, Vladimir Lazar, Eitan Rubin, Sohyun Hwang, Raanan Berger, Tuvik Beker, Ze'ev Ronai, Sridhar Hannenhalli, Mark R Gilbert, Razelle Kurzrock, Se-Hoon Lee, Kenneth Aldape, Eytan Ruppin

X Demographics

X Demographics

The data shown below were collected from the profiles of 176 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 294 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 294 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 68 23%
Student > Ph. D. Student 40 14%
Student > Master 20 7%
Student > Bachelor 19 6%
Professor > Associate Professor 13 4%
Other 36 12%
Unknown 98 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 75 26%
Medicine and Dentistry 29 10%
Agricultural and Biological Sciences 26 9%
Computer Science 16 5%
Immunology and Microbiology 10 3%
Other 33 11%
Unknown 105 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 129. 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 15 December 2022.
All research outputs
#321,601
of 25,402,528 outputs
Outputs from Cell
#1,743
of 17,191 outputs
Outputs of similar age
#9,622
of 455,351 outputs
Outputs of similar age from Cell
#63
of 162 outputs
Altmetric has tracked 25,402,528 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,191 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 59.2. This one has done well, scoring higher than 89% 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 455,351 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 97% of its contemporaries.
We're also able to compare this research output to 162 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 61% of its contemporaries.