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Rocker: Open source, easy-to-use tool for AUC and enrichment calculations and ROC visualization

Overview of attention for article published in Journal of Cheminformatics, September 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
7 tweeters

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
44 Mendeley
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Title
Rocker: Open source, easy-to-use tool for AUC and enrichment calculations and ROC visualization
Published in
Journal of Cheminformatics, September 2016
DOI 10.1186/s13321-016-0158-y
Pubmed ID
Authors

Sakari Lätti, Sanna Niinivehmas, Olli T. Pentikäinen

Abstract

Receiver operating characteristics (ROC) curve with the calculation of area under curve (AUC) is a useful tool to evaluate the performance of biomedical and chemoinformatics data. For example, in virtual drug screening ROC curves are very often used to visualize the efficiency of the used application to separate active ligands from inactive molecules. Unfortunately, most of the available tools for ROC analysis are implemented into commercially available software packages, or are plugins in statistical software, which are not always the easiest to use. Here, we present Rocker, a simple ROC curve visualization tool that can be used for the generation of publication quality images. Rocker also includes an automatic calculation of the AUC for the ROC curve and Boltzmann-enhanced discrimination of ROC (BEDROC). Furthermore, in virtual screening campaigns it is often important to understand the early enrichment of active ligand identification, for this Rocker offers automated calculation routine. To enable further development of Rocker, it is freely available (MIT-GPL license) for use and modifications from our web-site (http://www.jyu.fi/rocker).

Twitter Demographics

The data shown below were collected from the profiles of 7 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 23%
Researcher 9 20%
Professor 7 16%
Student > Ph. D. Student 6 14%
Student > Doctoral Student 4 9%
Other 7 16%
Unknown 1 2%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 18%
Chemistry 8 18%
Agricultural and Biological Sciences 7 16%
Computer Science 7 16%
Pharmacology, Toxicology and Pharmaceutical Science 5 11%
Other 7 16%
Unknown 2 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 12 September 2016.
All research outputs
#2,858,154
of 11,350,788 outputs
Outputs from Journal of Cheminformatics
#253
of 444 outputs
Outputs of similar age
#77,721
of 259,250 outputs
Outputs of similar age from Journal of Cheminformatics
#10
of 19 outputs
Altmetric has tracked 11,350,788 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 444 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.7. This one is in the 42nd percentile – i.e., 42% 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 259,250 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 69% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.