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QSAR DataBank - an approach for the digital organization and archiving of QSAR model information

Overview of attention for article published in Journal of Cheminformatics, May 2014
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Mentioned by

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1 X user

Citations

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41 Dimensions

Readers on

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67 Mendeley
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2 CiteULike
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Title
QSAR DataBank - an approach for the digital organization and archiving of QSAR model information
Published in
Journal of Cheminformatics, May 2014
DOI 10.1186/1758-2946-6-25
Pubmed ID
Authors

Villu Ruusmann, Sulev Sild, Uko Maran

Abstract

Research efforts in the field of descriptive and predictive Quantitative Structure-Activity Relationships or Quantitative Structure-Property Relationships produce around one thousand scientific publications annually. All the materials and results are mainly communicated using printed media. The printed media in its present form have obvious limitations when they come to effectively representing mathematical models, including complex and non-linear, and large bodies of associated numerical chemical data. It is not supportive of secondary information extraction or reuse efforts while in silico studies poses additional requirements for accessibility, transparency and reproducibility of the research. This gap can and should be bridged by introducing domain-specific digital data exchange standards and tools. The current publication presents a formal specification of the quantitative structure-activity relationship data organization and archival format called the QSAR DataBank (QsarDB for shorter, or QDB for shortest).

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

Geographical breakdown

Country Count As %
Germany 1 1%
Brazil 1 1%
Iran, Islamic Republic of 1 1%
Estonia 1 1%
Spain 1 1%
Unknown 62 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 18%
Student > Master 12 18%
Researcher 8 12%
Student > Bachelor 5 7%
Professor 4 6%
Other 14 21%
Unknown 12 18%
Readers by discipline Count As %
Chemistry 12 18%
Computer Science 11 16%
Biochemistry, Genetics and Molecular Biology 4 6%
Agricultural and Biological Sciences 4 6%
Engineering 3 4%
Other 17 25%
Unknown 16 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 06 June 2014.
All research outputs
#16,452,494
of 24,226,848 outputs
Outputs from Journal of Cheminformatics
#799
of 891 outputs
Outputs of similar age
#137,878
of 231,580 outputs
Outputs of similar age from Journal of Cheminformatics
#19
of 23 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
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 10.5. This one is in the 5th percentile – i.e., 5% 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 231,580 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.