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Small molecules enable highly efficient neuronal conversion of human fibroblasts

Overview of attention for article published in Nature Methods, April 2012
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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)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Citations

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284 Dimensions

Readers on

mendeley
411 Mendeley
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1 CiteULike
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Title
Small molecules enable highly efficient neuronal conversion of human fibroblasts
Published in
Nature Methods, April 2012
DOI 10.1038/nmeth.1972
Pubmed ID
Authors

Julia Ladewig, Jerome Mertens, Jaideep Kesavan, Jonas Doerr, Daniel Poppe, Finnja Glaue, Stefan Herms, Peter Wernet, Gesine Kögler, Franz-Josef Müller, Philipp Koch, Oliver Brüstle

Abstract

Forced expression of proneural transcription factors has been shown to direct neuronal conversion of fibroblasts. Because neurons are postmitotic, conversion efficiencies are an important parameter for this process. We present a minimalist approach combining two-factor neuronal programming with small molecule-based inhibition of glycogen synthase kinase-3β and SMAD signaling, which converts postnatal human fibroblasts into functional neuron-like cells with yields up to >200% and neuronal purities up to >80%.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 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 411 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 1%
Korea, Republic of 3 <1%
Japan 3 <1%
Portugal 2 <1%
Germany 2 <1%
Australia 2 <1%
France 1 <1%
Peru 1 <1%
Switzerland 1 <1%
Other 4 <1%
Unknown 386 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 110 27%
Researcher 84 20%
Student > Master 49 12%
Student > Bachelor 42 10%
Student > Doctoral Student 22 5%
Other 55 13%
Unknown 49 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 169 41%
Biochemistry, Genetics and Molecular Biology 79 19%
Neuroscience 57 14%
Medicine and Dentistry 25 6%
Engineering 11 3%
Other 16 4%
Unknown 54 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 54. 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 2023.
All research outputs
#805,243
of 25,882,826 outputs
Outputs from Nature Methods
#1,042
of 5,429 outputs
Outputs of similar age
#3,731
of 174,539 outputs
Outputs of similar age from Nature Methods
#4
of 75 outputs
Altmetric has tracked 25,882,826 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,429 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.6. This one has done well, scoring higher than 80% 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 174,539 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 75 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 94% of its contemporaries.