↓ Skip to main content

A rotation-translation invariant molecular descriptor of partial charges and its use in ligand-based virtual screening

Overview of attention for article published in Journal of Cheminformatics, May 2014
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
35 Mendeley
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.
Title
A rotation-translation invariant molecular descriptor of partial charges and its use in ligand-based virtual screening
Published in
Journal of Cheminformatics, May 2014
DOI 10.1186/1758-2946-6-23
Pubmed ID
Authors

Francois Berenger, Arnout Voet, Xiao Yin Lee, Kam YJ Zhang

Abstract

Measures of similarity for chemical molecules have been developed since the dawn of chemoinformatics. Molecular similarity has been measured by a variety of methods including molecular descriptor based similarity, common molecular fragments, graph matching and 3D methods such as shape matching. Similarity measures are widespread in practice and have proven to be useful in drug discovery. Because of our interest in electrostatics and high throughput ligand-based virtual screening, we sought to exploit the information contained in atomic coordinates and partial charges of a molecule.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Poland 1 3%
Germany 1 3%
Unknown 33 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 23%
Researcher 7 20%
Other 4 11%
Student > Master 4 11%
Student > Bachelor 2 6%
Other 6 17%
Unknown 4 11%
Readers by discipline Count As %
Chemistry 11 31%
Computer Science 6 17%
Agricultural and Biological Sciences 4 11%
Engineering 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Other 4 11%
Unknown 5 14%

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 30 May 2014.
All research outputs
#2,707,586
of 6,268,168 outputs
Outputs from Journal of Cheminformatics
#228
of 314 outputs
Outputs of similar age
#59,109
of 134,007 outputs
Outputs of similar age from Journal of Cheminformatics
#12
of 21 outputs
Altmetric has tracked 6,268,168 research outputs across all sources so far. This one has received more attention than most of these and is in the 55th percentile.
So far Altmetric has tracked 314 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 26th percentile – i.e., 26% 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 134,007 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 54% of its contemporaries.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.