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Consensus queries in ligand-based virtual screening experiments

Overview of attention for article published in Journal of Cheminformatics, November 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)

Mentioned by

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5 tweeters

Citations

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8 Dimensions

Readers on

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35 Mendeley
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Title
Consensus queries in ligand-based virtual screening experiments
Published in
Journal of Cheminformatics, November 2017
DOI 10.1186/s13321-017-0248-5
Pubmed ID
Authors

Francois Berenger, Oanh Vu, Jens Meiler

Abstract

In ligand-based virtual screening experiments, a known active ligand is used in similarity searches to find putative active compounds for the same protein target. When there are several known active molecules, screening using all of them is more powerful than screening using a single ligand. A consensus query can be created by either screening serially with different ligands before merging the obtained similarity scores, or by combining the molecular descriptors (i.e. chemical fingerprints) of those ligands. We report on the discriminative power and speed of several consensus methods, on two datasets only made of experimentally verified molecules. The two datasets contain a total of 19 protein targets, 3776 known active and ~ 2 × 106 inactive molecules. Three chemical fingerprints are investigated: MACCS 166 bits, ECFP4 2048 bits and an unfolded version of MOLPRINT2D. Four different consensus policies and five consensus sizes were benchmarked. The best consensus method is to rank candidate molecules using the maximum score obtained by each candidate molecule versus all known actives. When the number of actives used is small, the same screening performance can be approached by a consensus fingerprint. However, if the computational exploration of the chemical space is limited by speed (i.e. throughput), a consensus fingerprint allows to outperform this consensus of scores.

Twitter Demographics

The data shown below were collected from the profiles of 5 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 %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 26%
Student > Master 8 23%
Student > Ph. D. Student 5 14%
Student > Doctoral Student 4 11%
Other 2 6%
Other 3 9%
Unknown 4 11%
Readers by discipline Count As %
Chemistry 15 43%
Computer Science 4 11%
Biochemistry, Genetics and Molecular Biology 3 9%
Agricultural and Biological Sciences 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Other 2 6%
Unknown 7 20%

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 04 December 2017.
All research outputs
#6,612,348
of 12,247,570 outputs
Outputs from Journal of Cheminformatics
#339
of 476 outputs
Outputs of similar age
#143,175
of 342,115 outputs
Outputs of similar age from Journal of Cheminformatics
#13
of 16 outputs
Altmetric has tracked 12,247,570 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 476 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.1. 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 342,115 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 56% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.