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Analyzing negative feedback using a synthetic gene network expressed in the Drosophila melanogaster embryo

Overview of attention for article published in BMC Systems Biology, August 2016
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Title
Analyzing negative feedback using a synthetic gene network expressed in the Drosophila melanogaster embryo
Published in
BMC Systems Biology, August 2016
DOI 10.1186/s12918-016-0330-z
Pubmed ID
Authors

Ashley A. Jermusyk, Nicholas P. Murphy, Gregory T. Reeves

Abstract

A complex network of gene interactions controls gene regulation throughout development and the life of the organisms. Insights can be made into these processes by studying the functional interactions (or "motifs") which make up these networks. We sought to understand the functionality of one of these network motifs, negative feedback, in a multi-cellular system. This was accomplished using a synthetic network expressed in the Drosophila melanogaster embryo using the yeast proteins Gal4 (a transcriptional activator) and Gal80 (an inhibitor of Gal4 activity). This network is able to produce an attenuation or shuttling phenotype depending on the Gal80/Gal4 ratio. This shuttling behavior was validated by expressing Gal3, which inhibits Gal80, to produce a localized increase in free Gal4 and therefore signaling. Mathematical modeling was used to demonstrate the capacity for negative feedback to produce these varying outputs. The capacity of a network motif to exhibit different phenotypes due to minor changes to the network in multi-cellular systems was shown. This work demonstrates the importance of studying network motifs in multi-cellular systems.

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The data shown below were collected from the profiles of 3 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 9%
Unknown 10 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 27%
Student > Ph. D. Student 3 27%
Student > Bachelor 2 18%
Student > Master 2 18%
Professor 1 9%
Other 1 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 36%
Biochemistry, Genetics and Molecular Biology 3 27%
Computer Science 2 18%
Chemical Engineering 1 9%
Engineering 1 9%
Other 0 0%
Attention Score in Context

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 01 September 2016.
All research outputs
#15,330,390
of 23,577,654 outputs
Outputs from BMC Systems Biology
#601
of 1,139 outputs
Outputs of similar age
#208,064
of 339,543 outputs
Outputs of similar age from BMC Systems Biology
#15
of 32 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,139 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 43rd percentile – i.e., 43% 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 339,543 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.