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Attention Score in Context
Title |
Predicting outcomes of steady-state 13C isotope tracing experiments using Monte Carlo sampling
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Published in |
BMC Systems Biology, January 2012
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DOI | 10.1186/1752-0509-6-9 |
Pubmed ID | |
Authors |
Jan Schellenberger, Daniel C Zielinski, Wing Choi, Sunthosh Madireddi, Vasiliy Portnoy, David A Scott, Jennifer L Reed, Andrei L Osterman, Bernhard ∅ Palsson |
Abstract |
Carbon-13 (13C) analysis is a commonly used method for estimating reaction rates in biochemical networks. The choice of carbon labeling pattern is an important consideration when designing these experiments. We present a novel Monte Carlo algorithm for finding the optimal substrate input label for a particular experimental objective (flux or flux ratio). Unlike previous work, this method does not require assumption of the flux distribution beforehand. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 5% |
Germany | 2 | 2% |
Czechia | 1 | 1% |
Sweden | 1 | 1% |
Thailand | 1 | 1% |
Denmark | 1 | 1% |
Unknown | 85 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 33 | 34% |
Researcher | 23 | 24% |
Student > Master | 8 | 8% |
Student > Bachelor | 5 | 5% |
Professor > Associate Professor | 5 | 5% |
Other | 15 | 16% |
Unknown | 7 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 37 | 39% |
Biochemistry, Genetics and Molecular Biology | 20 | 21% |
Engineering | 9 | 9% |
Chemical Engineering | 5 | 5% |
Environmental Science | 4 | 4% |
Other | 8 | 8% |
Unknown | 13 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 31 January 2012.
All research outputs
#15,241,801
of 22,662,201 outputs
Outputs from BMC Systems Biology
#644
of 1,142 outputs
Outputs of similar age
#163,441
of 246,941 outputs
Outputs of similar age from BMC Systems Biology
#31
of 40 outputs
Altmetric has tracked 22,662,201 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 32nd percentile – i.e., 32% 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 246,941 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.