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Mendeley readers
Attention Score in Context
| Title |
Flux Design: In silico design of cell factories based on correlation of pathway fluxes to desired properties
|
|---|---|
| Published in |
BMC Systems Biology, December 2009
|
| DOI | 10.1186/1752-0509-3-120 |
| Pubmed ID | |
| Authors |
Guido Melzer, Manely Eslahpazir Esfandabadi, Ezequiel Franco-Lara, Christoph Wittmann |
| Abstract |
The identification of genetic target genes is a key step for rational engineering of production strains towards bio-based chemicals, fuels or therapeutics. This is often a difficult task, because superior production performance typically requires a combination of multiple targets, whereby the complex metabolic networks complicate straightforward identification. Recent attempts towards target prediction mainly focus on the prediction of gene deletion targets and therefore can cover only a part of genetic modifications proven valuable in metabolic engineering. Efficient in silico methods for simultaneous genome-scale identification of targets to be amplified or deleted are still lacking. |
Mendeley readers
The data shown below were compiled from readership statistics for 188 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 5 | 3% |
| Netherlands | 2 | 1% |
| United Kingdom | 2 | 1% |
| China | 2 | 1% |
| Iran, Islamic Republic of | 2 | 1% |
| Sweden | 2 | 1% |
| Kenya | 1 | <1% |
| India | 1 | <1% |
| Portugal | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 166 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 50 | 27% |
| Researcher | 37 | 20% |
| Student > Master | 33 | 18% |
| Student > Doctoral Student | 12 | 6% |
| Professor > Associate Professor | 8 | 4% |
| Other | 24 | 13% |
| Unknown | 24 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 95 | 51% |
| Biochemistry, Genetics and Molecular Biology | 28 | 15% |
| Engineering | 17 | 9% |
| Chemical Engineering | 4 | 2% |
| Computer Science | 4 | 2% |
| Other | 8 | 4% |
| Unknown | 32 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 23 January 2012.
All research outputs
#2,576,129
of 22,661,413 outputs
Outputs from BMC Systems Biology
#69
of 1,142 outputs
Outputs of similar age
#13,648
of 163,731 outputs
Outputs of similar age from BMC Systems Biology
#1
of 7 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has done particularly well, scoring higher than 93% 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 163,731 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them