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Exploiting Cell-To-Cell Variability To Detect Cellular Perturbations

Overview of attention for article published in PLOS ONE, March 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

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1 blog
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3 X users

Citations

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12 Dimensions

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53 Mendeley
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1 CiteULike
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Title
Exploiting Cell-To-Cell Variability To Detect Cellular Perturbations
Published in
PLOS ONE, March 2014
DOI 10.1371/journal.pone.0090540
Pubmed ID
Authors

Gautam Dey, Gagan D. Gupta, Balaji Ramalingam, Mugdha Sathe, Satyajit Mayor, Mukund Thattai

Abstract

Any single-cell-resolved measurement generates a population distribution of phenotypes, characterized by a mean, a variance, and a shape. Here we show that changes in the shape of a phenotypic distribution can signal perturbations to cellular processes, providing a way to screen for underlying molecular machinery. We analyzed images of a Drosophila S2R+ cell line perturbed by RNA interference, and tracked 27 single-cell features which report on endocytic activity, and cell and nuclear morphology. In replicate measurements feature distributions had erratic means and variances, but reproducible shapes; RNAi down-regulation reliably induced shape deviations in at least one feature for 1072 out of 7131 genes surveyed, as revealed by a Kolmogorov-Smirnov-like statistic. We were able to use these shape deviations to identify a spectrum of genes that influenced cell morphology, nuclear morphology, and multiple pathways of endocytosis. By preserving single-cell data, our method was even able to detect effects invisible to a population-averaged analysis. These results demonstrate that cell-to-cell variability contains accessible and useful biological information, which can be exploited in existing cell-based assays.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 4%
Mexico 1 2%
United States 1 2%
Germany 1 2%
Unknown 48 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 45%
Researcher 7 13%
Professor 6 11%
Student > Doctoral Student 5 9%
Student > Bachelor 2 4%
Other 5 9%
Unknown 4 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 53%
Biochemistry, Genetics and Molecular Biology 11 21%
Engineering 3 6%
Computer Science 2 4%
Physics and Astronomy 1 2%
Other 2 4%
Unknown 6 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 04 July 2014.
All research outputs
#3,385,454
of 23,577,654 outputs
Outputs from PLOS ONE
#44,565
of 202,026 outputs
Outputs of similar age
#34,355
of 222,553 outputs
Outputs of similar age from PLOS ONE
#1,270
of 6,071 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 202,026 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. This one has done well, scoring higher than 77% 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 222,553 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 6,071 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.