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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RMol: a toolset for transforming SD/Molfile structure information into R objects
|
|---|---|
| Published in |
Source Code for Biology and Medicine, November 2012
|
| DOI | 10.1186/1751-0473-7-12 |
| Pubmed ID | |
| Authors |
Martin Grabner, Kurt Varmuza, Matthias Dehmer |
| Abstract |
The graph-theoretical analysis of molecular networks has a long tradition in chemoinformatics. As demonstrated frequently, a well designed format to encode chemical structures and structure-related information of organic compounds is the Molfile format. But when it comes to use modern programming languages for statistical data analysis in Bio- and Chemoinformatics, R as one of the most powerful free languages lacks tools to process Molfile data collections and import molecular network data into R. |
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 % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 7% |
| Unknown | 13 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 43% |
| Librarian | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Other | 1 | 7% |
| Student > Ph. D. Student | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 3 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 3 | 21% |
| Chemistry | 3 | 21% |
| Computer Science | 2 | 14% |
| Mathematics | 1 | 7% |
| Medicine and Dentistry | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 3 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 27 December 2012.
All research outputs
#4,487,593
of 25,079,131 outputs
Outputs from Source Code for Biology and Medicine
#23
of 127 outputs
Outputs of similar age
#30,807
of 184,305 outputs
Outputs of similar age from Source Code for Biology and Medicine
#2
of 2 outputs
Altmetric has tracked 25,079,131 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done well, scoring higher than 82% 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 184,305 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.