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Experimental and computational framework for a dynamic protein atlas of human cell division

Overview of attention for article published in Nature, September 2018
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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 (99th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

news
11 news outlets
blogs
3 blogs
twitter
262 tweeters
facebook
3 Facebook pages
reddit
1 Redditor

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
145 Mendeley
Title
Experimental and computational framework for a dynamic protein atlas of human cell division
Published in
Nature, September 2018
DOI 10.1038/s41586-018-0518-z
Pubmed ID
Authors

Yin Cai, M. Julius Hossain, Jean-Karim Hériché, Antonio Z. Politi, Nike Walther, Birgit Koch, Malte Wachsmuth, Bianca Nijmeijer, Moritz Kueblbeck, Marina Martinic-Kavur, Rene Ladurner, Stephanie Alexander, Jan-Michael Peters, Jan Ellenberg

Abstract

Essential biological functions, such as mitosis, require tight coordination of hundreds of proteins in space and time. Localization, the timing of interactions and changes in cellular structure are all crucial to ensure the correct assembly, function and regulation of protein complexes1-4. Imaging of live cells can reveal protein distributions and dynamics but experimental and theoretical challenges have prevented the collection of quantitative data, which are necessary for the formulation of a model of mitosis that comprehensively integrates information and enables the analysis of the dynamic interactions between the molecular parts of the mitotic machinery within changing cellular boundaries. Here we generate a canonical model of the morphological changes during the mitotic progression of human cells on the basis of four-dimensional image data. We use this model to integrate dynamic three-dimensional concentration data of many fluorescently knocked-in mitotic proteins, imaged by fluorescence correlation spectroscopy-calibrated microscopy5. The approach taken here to generate a dynamic protein atlas of human cell division is generic; it can be applied to systematically map and mine dynamic protein localization networks that drive cell division in different cell types, and can be conceptually transferred to other cellular functions.

Twitter Demographics

The data shown below were collected from the profiles of 262 tweeters 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 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 145 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 48 33%
Student > Ph. D. Student 35 24%
Unspecified 17 12%
Other 10 7%
Student > Bachelor 9 6%
Other 26 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 63 43%
Agricultural and Biological Sciences 40 28%
Unspecified 19 13%
Engineering 7 5%
Immunology and Microbiology 4 3%
Other 12 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 258. 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 24 May 2019.
All research outputs
#48,949
of 13,645,383 outputs
Outputs from Nature
#5,291
of 70,304 outputs
Outputs of similar age
#1,989
of 264,313 outputs
Outputs of similar age from Nature
#219
of 959 outputs
Altmetric has tracked 13,645,383 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 70,304 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 77.1. This one has done particularly well, scoring higher than 92% 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 264,313 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 99% of its contemporaries.
We're also able to compare this research output to 959 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.