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Probing the role of stochasticity in a model of the embryonic stem cell – heterogeneous gene expression and reprogramming efficiency

Overview of attention for article published in BMC Systems Biology, August 2012
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Mentioned by

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1 tweeter
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1 Facebook page

Citations

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25 Dimensions

Readers on

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70 Mendeley
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Title
Probing the role of stochasticity in a model of the embryonic stem cell – heterogeneous gene expression and reprogramming efficiency
Published in
BMC Systems Biology, August 2012
DOI 10.1186/1752-0509-6-98
Pubmed ID
Authors

Vijay Chickarmane, Vijay Chickarmane, Victor Olariu, Carsten Peterson

Abstract

Embryonic stem cells (ESC) have the capacity to self-renew and remain pluripotent, while continuously providing a source of a variety of differentiated cell types. Understanding what governs these properties at the molecular level is crucial for stem cell biology and its application to regenerative medicine. Of particular relevance is to elucidate those molecular interactions which govern the reprogramming of somatic cells into ESC. A computational approach can be used as a framework to explore the dynamics of a simplified network of the ESC with the aim to understand how stem cells differentiate and also how they can be reprogrammed from somatic cells.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 4%
Portugal 1 1%
Germany 1 1%
Czechia 1 1%
Unknown 64 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 31%
Researcher 18 26%
Student > Master 10 14%
Student > Bachelor 5 7%
Student > Doctoral Student 5 7%
Other 10 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 54%
Engineering 7 10%
Biochemistry, Genetics and Molecular Biology 6 9%
Computer Science 5 7%
Mathematics 4 6%
Other 10 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 16 August 2012.
All research outputs
#3,352,685
of 5,038,248 outputs
Outputs from BMC Systems Biology
#484
of 731 outputs
Outputs of similar age
#45,287
of 72,664 outputs
Outputs of similar age from BMC Systems Biology
#26
of 38 outputs
Altmetric has tracked 5,038,248 research outputs across all sources so far. This one is in the 29th percentile – i.e., 29% of other outputs scored the same or lower than it.
So far Altmetric has tracked 731 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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 72,664 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.