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Phenotypes on demand via switchable target protein degradation in multicellular organisms

Overview of attention for article published in Nature Communications, January 2016
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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)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

news
3 news outlets
twitter
94 tweeters
facebook
1 Facebook page

Citations

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8 Dimensions

Readers on

mendeley
63 Mendeley
Title
Phenotypes on demand via switchable target protein degradation in multicellular organisms
Published in
Nature Communications, January 2016
DOI 10.1038/ncomms12202
Pubmed ID
Authors

Frederik Faden, Thomas Ramezani, Stefan Mielke, Isabel Almudi, Knud Nairz, Marceli S. Froehlich, Jörg Höckendorff, Wolfgang Brandt, Wolfgang Hoehenwarter, R. Jürgen Dohmen, Arp Schnittger, Nico Dissmeyer, Faden, Frederik, Ramezani, Thomas, Mielke, Stefan, Almudi, Isabel, Nairz, Knud, Froehlich, Marceli S, Höckendorff, Jörg, Brandt, Wolfgang, Hoehenwarter, Wolfgang, Dohmen, R Jürgen, Schnittger, Arp, Dissmeyer, Nico

Abstract

Phenotypes on-demand generated by controlling activation and accumulation of proteins of interest are invaluable tools to analyse and engineer biological processes. While temperature-sensitive alleles are frequently used as conditional mutants in microorganisms, they are usually difficult to identify in multicellular species. Here we present a versatile and transferable, genetically stable system based on a low-temperature-controlled N-terminal degradation signal (lt-degron) that allows reversible and switch-like tuning of protein levels under physiological conditions in vivo. Thereby, developmental effects can be triggered and phenotypes on demand generated. The lt-degron was established to produce conditional and cell-type-specific phenotypes and is generally applicable in a wide range of organisms, from eukaryotic microorganisms to plants and poikilothermic animals. We have successfully applied this system to control the abundance and function of transcription factors and different enzymes by tunable protein accumulation.

Twitter Demographics

The data shown below were collected from the profiles of 94 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 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 3%
Netherlands 2 3%
Chile 1 2%
United Kingdom 1 2%
Taiwan 1 2%
Japan 1 2%
United States 1 2%
Unknown 54 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 29%
Researcher 12 19%
Student > Bachelor 10 16%
Student > Master 7 11%
Other 3 5%
Other 13 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 57%
Biochemistry, Genetics and Molecular Biology 18 29%
Unspecified 4 6%
Chemical Engineering 3 5%
Social Sciences 1 2%
Other 1 2%

Attention Score in Context

This research output has an Altmetric Attention Score of 82. 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 29 August 2018.
All research outputs
#156,501
of 11,708,747 outputs
Outputs from Nature Communications
#2,903
of 18,128 outputs
Outputs of similar age
#7,729
of 265,277 outputs
Outputs of similar age from Nature Communications
#174
of 830 outputs
Altmetric has tracked 11,708,747 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 18,128 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 47.3. This one has done well, scoring higher than 83% 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 265,277 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 830 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.