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Nonparametric Simulation of Signal Transduction Networks with Semi-Synchronized Update

Overview of attention for article published in PLOS ONE, June 2012
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Title
Nonparametric Simulation of Signal Transduction Networks with Semi-Synchronized Update
Published in
PLOS ONE, June 2012
DOI 10.1371/journal.pone.0039643
Pubmed ID
Authors

Isar Nassiri, Ali Masoudi-Nejad, Mahdi Jalili, Ali Moeini

Abstract

Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational framework to describe the profile of the evolving process and the time course of the proportion of active form of molecules in the signal transduction networks. The model is also capable of incorporating perturbations. The model was validated on four signaling networks showing that it can effectively uncover the activity levels and trends of response during signal transduction process.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 8%
Netherlands 1 4%
Denmark 1 4%
United States 1 4%
Unknown 19 79%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 33%
Student > Doctoral Student 5 21%
Researcher 4 17%
Lecturer 2 8%
Other 1 4%
Other 2 8%
Unknown 2 8%
Readers by discipline Count As %
Computer Science 8 33%
Biochemistry, Genetics and Molecular Biology 4 17%
Agricultural and Biological Sciences 2 8%
Business, Management and Accounting 1 4%
Mathematics 1 4%
Other 4 17%
Unknown 4 17%
Attention Score in Context

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 22 June 2012.
All research outputs
#18,308,895
of 22,668,244 outputs
Outputs from PLOS ONE
#153,778
of 193,511 outputs
Outputs of similar age
#126,114
of 164,033 outputs
Outputs of similar age from PLOS ONE
#3,060
of 3,922 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 193,511 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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