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Mendeley readers
Attention Score in Context
| Title |
Modeling framework for isotopic labeling of heteronuclear moieties
|
|---|---|
| Published in |
Journal of Cheminformatics, March 2017
|
| DOI | 10.1186/s13321-017-0201-7 |
| Pubmed ID | |
| Authors |
Mark I. Borkum, Patrick N. Reardon, Ronald C. Taylor, Nancy G. Isern |
| Abstract |
Isotopic labeling is an analytic technique that is used to track the movement of isotopes through reaction networks. In general, the applicability of isotopic labeling techniques is limited to the investigation of reaction networks that consider homonuclear moieties, whose atoms are of one tracer element with two isotopes, distinguished by the presence of one additional neutron. This article presents a reformulation of the modeling framework for isotopic labeling, generalized to arbitrarily large, heteronuclear moieties, arbitrary numbers of isotopic tracer elements, and arbitrary numbers of isotopes per element, distinguished by arbitrary numbers of additional neutrons. With this work, it is now possible to simulate the isotopic labeling states of metabolites in completely arbitrary biochemical reaction networks. |
X Demographics
The data shown below were collected from the profiles of 3 X users 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 | 33% |
| India | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 7% |
| Unknown | 14 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 40% |
| Student > Ph. D. Student | 2 | 13% |
| Professor | 2 | 13% |
| Student > Master | 2 | 13% |
| Other | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 1 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 33% |
| Biochemistry, Genetics and Molecular Biology | 3 | 20% |
| Computer Science | 2 | 13% |
| Immunology and Microbiology | 1 | 7% |
| Engineering | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 3 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 07 March 2017.
All research outputs
#15,654,688
of 24,903,209 outputs
Outputs from Journal of Cheminformatics
#763
of 934 outputs
Outputs of similar age
#181,288
of 315,872 outputs
Outputs of similar age from Journal of Cheminformatics
#22
of 22 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 934 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 18th percentile – i.e., 18% 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 315,872 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.