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Attention Score in Context
| Title |
Atom mapping with constraint programming
|
|---|---|
| Published in |
Algorithms for Molecular Biology, November 2014
|
| DOI | 10.1186/s13015-014-0023-3 |
| Pubmed ID | |
| Authors |
Martin Mann, Feras Nahar, Norah Schnorr, Rolf Backofen, Peter F Stadler, Christoph Flamm |
| Abstract |
Chemical reactions are rearrangements of chemical bonds. Each atom in an educt molecule thus appears again in a specific position of one of the reaction products. This bijection between educt and product atoms is not reported by chemical reaction databases, however, so that the "Atom Mapping Problem" of finding this bijection is left as an important computational task for many practical applications in computational chemistry and systems biology. Elementary chemical reactions feature a cyclic imaginary transition state (ITS) that imposes additional restrictions on the bijection between educt and product atoms that are not taken into account by previous approaches. We demonstrate that Constraint Programming is well-suited to solving the Atom Mapping Problem in this setting. The performance of our approach is evaluated for a manually curated subset of chemical reactions from the KEGG database featuring various ITS cycle layouts and reaction mechanisms. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Bulgaria | 1 | 5% |
| Unknown | 20 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 29% |
| Student > Master | 4 | 19% |
| Student > Ph. D. Student | 3 | 14% |
| Student > Postgraduate | 2 | 10% |
| Professor | 2 | 10% |
| Other | 1 | 5% |
| Unknown | 3 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 29% |
| Biochemistry, Genetics and Molecular Biology | 4 | 19% |
| Chemistry | 4 | 19% |
| Agricultural and Biological Sciences | 2 | 10% |
| Physics and Astronomy | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 4 | 19% |
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 30 November 2014.
All research outputs
#17,733,724
of 22,772,779 outputs
Outputs from Algorithms for Molecular Biology
#173
of 264 outputs
Outputs of similar age
#248,079
of 361,775 outputs
Outputs of similar age from Algorithms for Molecular Biology
#2
of 7 outputs
Altmetric has tracked 22,772,779 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 264 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 25th percentile – i.e., 25% 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 361,775 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
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 5 of them.