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Mendeley readers
Attention Score in Context
| Title |
Ligand scaffold hopping combining 3D maximal substructure search and molecular similarity
|
|---|---|
| Published in |
BMC Bioinformatics, August 2009
|
| DOI | 10.1186/1471-2105-10-245 |
| Pubmed ID | |
| Authors |
Flavien Quintus, Olivier Sperandio, Julien Grynberg, Michel Petitjean, Pierre Tuffery |
| Abstract |
Virtual screening methods are now well established as effective to identify hit and lead candidates and are fully integrated in most drug discovery programs. Ligand-based approaches make use of physico-chemical, structural and energetics properties of known active compounds to search large chemical libraries for related and novel chemotypes. While 2D-similarity search tools are known to be fast and efficient, the use of 3D-similarity search methods can be very valuable to many research projects as integration of "3D knowledge" can facilitate the identification of not only related molecules but also of chemicals possessing distant scaffolds as compared to the query and therefore be more inclined to scaffolds hopping. To date, very few methods performing this task are easily available to the scientific community. |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 4% |
| Netherlands | 1 | 2% |
| United Kingdom | 1 | 2% |
| Unknown | 44 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 38% |
| Student > Ph. D. Student | 12 | 25% |
| Student > Bachelor | 5 | 10% |
| Other | 5 | 10% |
| Student > Master | 2 | 4% |
| Other | 4 | 8% |
| Unknown | 2 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 16 | 33% |
| Agricultural and Biological Sciences | 13 | 27% |
| Biochemistry, Genetics and Molecular Biology | 7 | 15% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 4% |
| Computer Science | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 3 | 6% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 28 November 2014.
All research outputs
#5,493,611
of 22,772,779 outputs
Outputs from BMC Bioinformatics
#1,981
of 7,273 outputs
Outputs of similar age
#29,339
of 111,804 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 37 outputs
Altmetric has tracked 22,772,779 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 72% 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 111,804 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.