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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective
|
|---|---|
| Published in |
PLoS Computational Biology, January 2013
|
| DOI | 10.1371/journal.pcbi.1002882 |
| Pubmed ID | |
| Authors |
Graham Rockwell, Nicholas J. Guido, George M. Church |
| Abstract |
Advances in computational metabolic optimization are required to realize the full potential of new in vivo metabolic engineering technologies by bridging the gap between computational design and strain development. We present Redirector, a new Flux Balance Analysis-based framework for identifying engineering targets to optimize metabolite production in complex pathways. Previous optimization frameworks have modeled metabolic alterations as directly controlling fluxes by setting particular flux bounds. Redirector develops a more biologically relevant approach, modeling metabolic alterations as changes in the balance of metabolic objectives in the system. This framework iteratively selects enzyme targets, adds the associated reaction fluxes to the metabolic objective, thereby incentivizing flux towards the production of a metabolite of interest. These adjustments to the objective act in competition with cellular growth and represent up-regulation and down-regulation of enzyme mediated reactions. Using the iAF1260 E. coli metabolic network model for optimization of fatty acid production as a test case, Redirector generates designs with as many as 39 simultaneous and 111 unique engineering targets. These designs discover proven in vivo targets, novel supporting pathways and relevant interdependencies, many of which cannot be predicted by other methods. Redirector is available as open and free software, scalable to computational resources, and powerful enough to find all known enzyme targets for fatty acid production. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 17% |
| United States | 1 | 17% |
| France | 1 | 17% |
| Norway | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 67% |
| Members of the public | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 3% |
| Portugal | 3 | 2% |
| Germany | 2 | 1% |
| Switzerland | 1 | <1% |
| France | 1 | <1% |
| Colombia | 1 | <1% |
| United Kingdom | 1 | <1% |
| Canada | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Other | 5 | 4% |
| Unknown | 120 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 35 | 25% |
| Student > Ph. D. Student | 30 | 21% |
| Student > Master | 13 | 9% |
| Professor | 11 | 8% |
| Professor > Associate Professor | 9 | 6% |
| Other | 29 | 21% |
| Unknown | 13 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 65 | 46% |
| Biochemistry, Genetics and Molecular Biology | 20 | 14% |
| Engineering | 18 | 13% |
| Computer Science | 6 | 4% |
| Chemical Engineering | 4 | 3% |
| Other | 9 | 6% |
| Unknown | 18 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 14 February 2013.
All research outputs
#7,779,140
of 25,374,917 outputs
Outputs from PLoS Computational Biology
#5,160
of 8,960 outputs
Outputs of similar age
#79,228
of 292,509 outputs
Outputs of similar age from PLoS Computational Biology
#54
of 127 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 41st percentile – i.e., 41% 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 292,509 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 127 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 55% of its contemporaries.