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Modeling stochasticity and variability in gene regulatory networks

Overview of attention for article published in EURASIP Journal on Bioinformatics & Systems Biology, June 2012
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Mentioned by

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3 tweeters

Citations

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52 Dimensions

Readers on

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46 Mendeley
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1 CiteULike
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Title
Modeling stochasticity and variability in gene regulatory networks
Published in
EURASIP Journal on Bioinformatics & Systems Biology, June 2012
DOI 10.1186/1687-4153-2012-5
Pubmed ID
Authors

David Murrugarra, Alan Veliz-Cuba, Boris Aguilar, Seda Arat, Reinhard Laubenbacher

Abstract

Modeling stochasticity in gene regulatory networks is an important and complex problem in molecular systems biology. To elucidate intrinsic noise, several modeling strategies such as the Gillespie algorithm have been used successfully. This article contributes an approach as an alternative to these classical settings. Within the discrete paradigm, where genes, proteins, and other molecular components of gene regulatory networks are modeled as discrete variables and are assigned as logical rules describing their regulation through interactions with other components. Stochasticity is modeled at the biological function level under the assumption that even if the expression levels of the input nodes of an update rule guarantee activation or degradation there is a probability that the process will not occur due to stochastic effects. This approach allows a finer analysis of discrete models and provides a natural setup for cell population simulations to study cell-to-cell variability. We applied our methods to two of the most studied regulatory networks, the outcome of lambda phage infection of bacteria and the p53-mdm2 complex.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 7%
United Kingdom 1 2%
Portugal 1 2%
Unknown 41 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 26%
Student > Master 7 15%
Student > Ph. D. Student 7 15%
Student > Bachelor 5 11%
Professor > Associate Professor 5 11%
Other 8 17%
Unknown 2 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 41%
Biochemistry, Genetics and Molecular Biology 6 13%
Mathematics 6 13%
Computer Science 6 13%
Physics and Astronomy 3 7%
Other 2 4%
Unknown 4 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 27 August 2013.
All research outputs
#7,496,264
of 12,434,464 outputs
Outputs from EURASIP Journal on Bioinformatics & Systems Biology
#18
of 51 outputs
Outputs of similar age
#109,814
of 220,844 outputs
Outputs of similar age from EURASIP Journal on Bioinformatics & Systems Biology
#1
of 1 outputs
Altmetric has tracked 12,434,464 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 51 research outputs from this source. They receive a mean Attention Score of 1.7. This one has gotten more attention than average, scoring higher than 58% 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 220,844 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them