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Synthetic circuits that process multiple light and chemical signal inputs

Overview of attention for article published in BMC Systems Biology, January 2017
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Title
Synthetic circuits that process multiple light and chemical signal inputs
Published in
BMC Systems Biology, January 2017
DOI 10.1186/s12918-016-0384-y
Pubmed ID
Authors

Lizhong Liu, Wei Huang, Jian-Dong Huang

Abstract

Multi-signal processing circuits are essential for rational design of sophisticated synthetic systems with good controllability and modularity, therefore, enable construction of high-level networks. Moreover, light-inducible systems provide fast and reversible means for spatiotemporal control of gene expression. Here, in HEK 293 cells, we present combinatory genetic circuits responding to light and chemical signals, simultaneously. We first constructed a dual input circuit converting different light intensities into varying of the sensitivity of the promoter to a chemical inducer (doxycycline). Next, we generated a ternary input circuit, which responded to light, doxycycline and cumate. This circuit allowed us to use different combinations of blue light and the two chemical inducers to generate gradual output values over two orders of magnitude. Overall, in this study, we devise genetic circuits sensing and processing light and chemical inducers. Our work may provide insights into bio-computation and fine-tuning expression of the transgene.

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The data shown below were collected from the profiles of 4 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 2%
Unknown 42 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 26%
Researcher 6 14%
Student > Doctoral Student 5 12%
Student > Bachelor 5 12%
Other 3 7%
Other 4 9%
Unknown 9 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 37%
Agricultural and Biological Sciences 7 16%
Engineering 3 7%
Chemical Engineering 2 5%
Mathematics 1 2%
Other 5 12%
Unknown 9 21%
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 19 October 2017.
All research outputs
#14,638,545
of 23,881,329 outputs
Outputs from BMC Systems Biology
#516
of 1,126 outputs
Outputs of similar age
#226,043
of 421,928 outputs
Outputs of similar age from BMC Systems Biology
#7
of 17 outputs
Altmetric has tracked 23,881,329 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 1,126 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 52% 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 421,928 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 17 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 64% of its contemporaries.