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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Metabolomics, Standards, and Metabolic Modeling for Synthetic Biology in Plants
|
|---|---|
| Published in |
Frontiers in Bioengineering and Biotechnology, October 2015
|
| DOI | 10.3389/fbioe.2015.00167 |
| Pubmed ID | |
| Authors |
Camilla Beate Hill, Tobias Czauderna, Matthias Klapperstück, Ute Roessner, Falk Schreiber |
| Abstract |
Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions. |
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 % |
|---|---|---|
| Germany | 1 | 17% |
| Unknown | 5 | 83% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 1% |
| Argentina | 1 | 1% |
| South Africa | 1 | 1% |
| Unknown | 71 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 22% |
| Researcher | 11 | 15% |
| Student > Master | 8 | 11% |
| Student > Bachelor | 6 | 8% |
| Professor > Associate Professor | 6 | 8% |
| Other | 16 | 22% |
| Unknown | 11 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 35% |
| Biochemistry, Genetics and Molecular Biology | 11 | 15% |
| Engineering | 5 | 7% |
| Chemistry | 4 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Other | 14 | 19% |
| Unknown | 11 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 11 October 2018.
All research outputs
#12,937,813
of 22,830,751 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#1,409
of 6,565 outputs
Outputs of similar age
#126,074
of 283,225 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#15
of 63 outputs
Altmetric has tracked 22,830,751 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,565 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 77% 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 283,225 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 54% of its contemporaries.
We're also able to compare this research output to 63 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 74% of its contemporaries.