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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Analytics for Metabolic Engineering
|
|---|---|
| Published in |
Frontiers in Bioengineering and Biotechnology, September 2015
|
| DOI | 10.3389/fbioe.2015.00135 |
| Pubmed ID | |
| Authors |
Christopher J. Petzold, Leanne Jade G. Chan, Melissa Nhan, Paul D. Adams |
| Abstract |
Realizing the promise of metabolic engineering has been slowed by challenges related to moving beyond proof-of-concept examples to robust and economically viable systems. Key to advancing metabolic engineering beyond trial-and-error research is access to parts with well-defined performance metrics that can be readily applied in vastly different contexts with predictable effects. As the field now stands, research depends greatly on analytical tools that assay target molecules, transcripts, proteins, and metabolites across different hosts and pathways. Screening technologies yield specific information for many thousands of strain variants, while deep omics analysis provides a systems-level view of the cell factory. Efforts focused on a combination of these analyses yield quantitative information of dynamic processes between parts and the host chassis that drive the next engineering steps. Overall, the data generated from these types of assays aid better decision-making at the design and strain construction stages to speed progress in metabolic engineering research. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 248 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | <1% |
| Lithuania | 1 | <1% |
| Canada | 1 | <1% |
| United Kingdom | 1 | <1% |
| Belgium | 1 | <1% |
| New Zealand | 1 | <1% |
| Unknown | 241 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 53 | 21% |
| Researcher | 46 | 19% |
| Student > Bachelor | 30 | 12% |
| Student > Master | 27 | 11% |
| Student > Doctoral Student | 12 | 5% |
| Other | 33 | 13% |
| Unknown | 47 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 76 | 31% |
| Agricultural and Biological Sciences | 56 | 23% |
| Engineering | 17 | 7% |
| Chemical Engineering | 11 | 4% |
| Chemistry | 9 | 4% |
| Other | 24 | 10% |
| Unknown | 55 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 30 November 2021.
All research outputs
#2,696,285
of 26,233,885 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#344
of 8,700 outputs
Outputs of similar age
#33,751
of 279,839 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#2
of 64 outputs
Altmetric has tracked 26,233,885 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,700 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 96% 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 279,839 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.