You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Similarity maps - a visualization strategy for molecular fingerprints and machine-learning methods
|
|---|---|
| Published in |
Journal of Cheminformatics, September 2013
|
| DOI | 10.1186/1758-2946-5-43 |
| Pubmed ID | |
| Authors |
Sereina Riniker, Gregory A Landrum |
| Abstract |
: Fingerprint similarity is a common method for comparing chemical structures. Similarity is an appealing approach because, with many fingerprint types, it provides intuitive results: a chemist looking at two molecules can understand why they have been determined to be similar. This transparency is partially lost with the fuzzier similarity methods that are often used for scaffold hopping and tends to vanish completely when molecular fingerprints are used as inputs to machine-learning (ML) models. Here we present similarity maps, a straightforward and general strategy to visualize the atomic contributions to the similarity between two molecules or the predicted probability of a ML model. We show the application of similarity maps to a set of dopamine D3 receptor ligands using atom-pair and circular fingerprints as well as two popular ML methods: random forests and naïve Bayes. An open-source implementation of the method is provided. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 14% |
| United States | 1 | 14% |
| Spain | 1 | 14% |
| Germany | 1 | 14% |
| Unknown | 3 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 2 | 29% |
Mendeley readers
The data shown below were compiled from readership statistics for 280 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 5 | 2% |
| Germany | 4 | 1% |
| Netherlands | 2 | <1% |
| Portugal | 2 | <1% |
| United States | 2 | <1% |
| Italy | 1 | <1% |
| China | 1 | <1% |
| Kenya | 1 | <1% |
| Japan | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 260 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 61 | 22% |
| Researcher | 55 | 20% |
| Student > Master | 34 | 12% |
| Student > Bachelor | 20 | 7% |
| Other | 14 | 5% |
| Other | 42 | 15% |
| Unknown | 54 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 71 | 25% |
| Agricultural and Biological Sciences | 32 | 11% |
| Computer Science | 30 | 11% |
| Biochemistry, Genetics and Molecular Biology | 26 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 16 | 6% |
| Other | 40 | 14% |
| Unknown | 65 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 20. 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 05 October 2022.
All research outputs
#1,626,970
of 23,482,849 outputs
Outputs from Journal of Cheminformatics
#140
of 863 outputs
Outputs of similar age
#15,304
of 204,743 outputs
Outputs of similar age from Journal of Cheminformatics
#2
of 7 outputs
Altmetric has tracked 23,482,849 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 863 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one has done well, scoring higher than 83% 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 204,743 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
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.