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Cell Press

Identifying Recent Adaptations in Large-Scale Genomic Data

Overview of attention for article published in Cell, February 2013
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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 (98th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Citations

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334 Dimensions

Readers on

mendeley
722 Mendeley
citeulike
15 CiteULike
Title
Identifying Recent Adaptations in Large-Scale Genomic Data
Published in
Cell, February 2013
DOI 10.1016/j.cell.2013.01.035
Pubmed ID
Authors

Sharon R. Grossman, Kristian G. Andersen, Ilya Shlyakhter, Shervin Tabrizi, Sarah Winnicki, Angela Yen, Daniel J. Park, Dustin Griesemer, Elinor K. Karlsson, Sunny H. Wong, Moran Cabili, Richard A. Adegbola, Rameshwar N.K. Bamezai, Adrian V.S. Hill, Fredrik O. Vannberg, John L. Rinn, 1000 Genomes Project, Eric S. Lander, Stephen F. Schaffner, Pardis C. Sabeti

Abstract

Although several hundred regions of the human genome harbor signals of positive natural selection, few of the relevant adaptive traits and variants have been elucidated. Using full-genome sequence variation from the 1000 Genomes (1000G) Project and the composite of multiple signals (CMS) test, we investigated 412 candidate signals and leveraged functional annotation, protein structure modeling, epigenetics, and association studies to identify and extensively annotate candidate causal variants. The resulting catalog provides a tractable list for experimental follow-up; it includes 35 high-scoring nonsynonymous variants, 59 variants associated with expression levels of a nearby coding gene or lincRNA, and numerous variants associated with susceptibility to infectious disease and other phenotypes. We experimentally characterized one candidate nonsynonymous variant in Toll-like receptor 5 (TLR5) and show that it leads to altered NF-κB signaling in response to bacterial flagellin. PAPERFLICK:

X Demographics

X Demographics

The data shown below were collected from the profiles of 31 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 722 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 22 3%
Germany 6 <1%
Italy 6 <1%
United Kingdom 6 <1%
Spain 4 <1%
France 2 <1%
Austria 2 <1%
China 2 <1%
Finland 2 <1%
Other 16 2%
Unknown 654 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 211 29%
Researcher 159 22%
Student > Master 60 8%
Student > Bachelor 59 8%
Professor 40 6%
Other 123 17%
Unknown 70 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 393 54%
Biochemistry, Genetics and Molecular Biology 148 20%
Medicine and Dentistry 26 4%
Computer Science 15 2%
Social Sciences 10 1%
Other 48 7%
Unknown 82 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 74. 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 13 December 2023.
All research outputs
#577,647
of 25,477,125 outputs
Outputs from Cell
#2,751
of 17,198 outputs
Outputs of similar age
#4,334
of 291,665 outputs
Outputs of similar age from Cell
#11
of 144 outputs
Altmetric has tracked 25,477,125 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 17,198 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 84% 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 291,665 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 98% of its contemporaries.
We're also able to compare this research output to 144 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.