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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Design, Optimization and Application of Small Molecule Biosensor in Metabolic Engineering
|
|---|---|
| Published in |
Frontiers in Microbiology, October 2017
|
| DOI | 10.3389/fmicb.2017.02012 |
| Pubmed ID | |
| Authors |
Yang Liu, Ye Liu, Meng Wang |
| Abstract |
The development of synthetic biology and metabolic engineering has painted a great future for the bio-based economy, including fuels, chemicals, and drugs produced from renewable feedstocks. With the rapid advance of genome-scale modeling, pathway assembling and genome engineering/editing, our ability to design and generate microbial cell factories with various phenotype becomes almost limitless. However, our lack of ability to measure and exert precise control over metabolite concentration related phenotypes becomes a bottleneck in metabolic engineering. Genetically encoded small molecule biosensors, which provide the means to couple metabolite concentration to measurable or actionable outputs, are highly promising solutions to the bottleneck. Here we review recent advances in the design, optimization and application of small molecule biosensor in metabolic engineering, with particular focus on optimization strategies for transcription factor (TF) based biosensors. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 176 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 176 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 35 | 20% |
| Researcher | 31 | 18% |
| Student > Master | 24 | 14% |
| Student > Bachelor | 20 | 11% |
| Other | 7 | 4% |
| Other | 18 | 10% |
| Unknown | 41 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 65 | 37% |
| Agricultural and Biological Sciences | 23 | 13% |
| Engineering | 14 | 8% |
| Chemistry | 8 | 5% |
| Chemical Engineering | 5 | 3% |
| Other | 13 | 7% |
| Unknown | 48 | 27% |
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 02 November 2017.
All research outputs
#14,613,137
of 23,393,513 outputs
Outputs from Frontiers in Microbiology
#12,852
of 25,757 outputs
Outputs of similar age
#182,822
of 327,628 outputs
Outputs of similar age from Frontiers in Microbiology
#324
of 528 outputs
Altmetric has tracked 23,393,513 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 25,757 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 45th percentile – i.e., 45% 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 327,628 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 528 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.