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Towards interoperable and reproducible QSAR analyses: Exchange of datasets

Overview of attention for article published in Journal of Cheminformatics, June 2010
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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 (92nd percentile)

Mentioned by

blogs
2 blogs
twitter
2 tweeters

Citations

dimensions_citation
29 Dimensions

Readers on

mendeley
55 Mendeley
citeulike
9 CiteULike
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Title
Towards interoperable and reproducible QSAR analyses: Exchange of datasets
Published in
Journal of Cheminformatics, June 2010
DOI 10.1186/1758-2946-2-5
Pubmed ID
Authors

Ola Spjuth, Egon L Willighagen, Rajarshi Guha, Martin Eklund, Jarl ES Wikberg

Abstract

QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data.

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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 5%
Sweden 3 5%
United Kingdom 2 4%
India 1 2%
Cyprus 1 2%
Bulgaria 1 2%
Netherlands 1 2%
Iran, Islamic Republic of 1 2%
Germany 1 2%
Other 0 0%
Unknown 41 75%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 31%
Student > Ph. D. Student 15 27%
Professor > Associate Professor 6 11%
Student > Master 5 9%
Other 4 7%
Other 6 11%
Unknown 2 4%
Readers by discipline Count As %
Chemistry 14 25%
Agricultural and Biological Sciences 11 20%
Computer Science 9 16%
Pharmacology, Toxicology and Pharmaceutical Science 6 11%
Engineering 5 9%
Other 7 13%
Unknown 3 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 08 February 2018.
All research outputs
#850,686
of 12,481,741 outputs
Outputs from Journal of Cheminformatics
#85
of 500 outputs
Outputs of similar age
#6,255
of 88,882 outputs
Outputs of similar age from Journal of Cheminformatics
#1
of 4 outputs
Altmetric has tracked 12,481,741 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 500 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.0. 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 88,882 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 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them