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Cytochrome P450 site of metabolism prediction from 2D topological fingerprints using GPU accelerated probabilistic classifiers

Overview of attention for article published in Journal of Cheminformatics, May 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

blogs
1 blog
twitter
1 X user

Citations

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29 Dimensions

Readers on

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64 Mendeley
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Title
Cytochrome P450 site of metabolism prediction from 2D topological fingerprints using GPU accelerated probabilistic classifiers
Published in
Journal of Cheminformatics, May 2014
DOI 10.1186/1758-2946-6-29
Pubmed ID
Authors

Jonathan D Tyzack, Hamse Y Mussa, Mark J Williamson, Johannes Kirchmair, Robert C Glen

Abstract

The prediction of sites and products of metabolism in xenobiotic compounds is key to the development of new chemical entities, where screening potential metabolites for toxicity or unwanted side-effects is of crucial importance. In this work 2D topological fingerprints are used to encode atomic sites and three probabilistic machine learning methods are applied: Parzen-Rosenblatt Window (PRW), Naive Bayesian (NB) and a novel approach called RASCAL (Random Attribute Subsampling Classification ALgorithm). These are implemented by randomly subsampling descriptor space to alleviate the problem often suffered by data mining methods of having to exactly match fingerprints, and in the case of PRW by measuring a distance between feature vectors rather than exact matching. The classifiers have been implemented in CUDA/C++ to exploit the parallel architecture of graphical processing units (GPUs) and is freely available in a public repository.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Netherlands 1 2%
Bulgaria 1 2%
United Kingdom 1 2%
Belgium 1 2%
Spain 1 2%
Unknown 58 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 25%
Student > Ph. D. Student 15 23%
Student > Master 5 8%
Student > Bachelor 4 6%
Professor 3 5%
Other 12 19%
Unknown 9 14%
Readers by discipline Count As %
Chemistry 15 23%
Computer Science 11 17%
Biochemistry, Genetics and Molecular Biology 7 11%
Agricultural and Biological Sciences 6 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 6%
Other 9 14%
Unknown 12 19%
Attention Score in Context

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 19 December 2014.
All research outputs
#4,316,512
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#414
of 891 outputs
Outputs of similar age
#40,687
of 230,866 outputs
Outputs of similar age from Journal of Cheminformatics
#6
of 21 outputs
Altmetric has tracked 24,143,470 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 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has gotten more attention than average, scoring higher than 53% 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 230,866 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 82% 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 has done well, scoring higher than 76% of its contemporaries.