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Design and analysis of a tunable synchronized oscillator

Overview of attention for article published in Journal of Biological Engineering, November 2013
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  • Good Attention Score compared to outputs of the same age (71st percentile)

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Title
Design and analysis of a tunable synchronized oscillator
Published in
Journal of Biological Engineering, November 2013
DOI 10.1186/1754-1611-7-26
Pubmed ID
Authors

Brendan M Ryback, Dorett I Odoni, Ruben GA van Heck, Youri van Nuland, Matthijn C Hesselman, Vítor AP Martins dos Santos, Mark WJ van Passel, Floor Hugenholtz

Abstract

The use of in silico simulations as a basis for designing artificial biological systems (and experiments to characterize them) is one of the tangible differences between Synthetic Biology and "classical" Genetic Engineering. To this end, synthetic biologists have adopted approaches originating from the traditionally non-biological fields of Nonlinear Dynamics and Systems & Control Theory. However, due to the complex molecular interactions affecting the emergent properties of biological systems, mechanistic descriptions of even the simplest genetic circuits (transcriptional feedback oscillators, bi-stable switches) produced by these methods tend to be either oversimplified, or numerically intractable. More comprehensive and realistic models can be approximated by constructing "toy" genetic circuits that provide the experimenter with some degree of control over the transcriptional dynamics, and allow for experimental set-ups that generate reliable data reflecting the intracellular biochemical state in real time. To this end, we designed two genetic circuits (basic and tunable) capable of exhibiting synchronized oscillatory green fluorescent protein (GFP) expression in small populations of Escherichia coli cells. The functionality of the basic circuit was verified microscopically. High-level visualizations of computational simulations were analyzed to determine whether the reliability and utility of a synchronized transcriptional oscillator could be enhanced by the introduction of chemically inducible repressors.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
United States 1 2%
China 1 2%
Unknown 41 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 34%
Researcher 6 14%
Student > Bachelor 5 11%
Student > Doctoral Student 4 9%
Professor > Associate Professor 4 9%
Other 7 16%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 36%
Biochemistry, Genetics and Molecular Biology 11 25%
Computer Science 3 7%
Immunology and Microbiology 2 5%
Engineering 2 5%
Other 6 14%
Unknown 4 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 February 2018.
All research outputs
#6,932,484
of 22,731,677 outputs
Outputs from Journal of Biological Engineering
#104
of 258 outputs
Outputs of similar age
#82,008
of 302,168 outputs
Outputs of similar age from Journal of Biological Engineering
#6
of 8 outputs
Altmetric has tracked 22,731,677 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 258 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.5. This one has gotten more attention than average, scoring higher than 57% 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 302,168 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.