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ToxPi Graphical User Interface 2.0: Dynamic exploration, visualization, and sharing of integrated data models

Overview of attention for article published in BMC Bioinformatics, March 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
8 tweeters

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
28 Mendeley
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Title
ToxPi Graphical User Interface 2.0: Dynamic exploration, visualization, and sharing of integrated data models
Published in
BMC Bioinformatics, March 2018
DOI 10.1186/s12859-018-2089-2
Pubmed ID
Authors

Skylar W. Marvel, Kimberly To, Fabian A. Grimm, Fred A. Wright, Ivan Rusyn, David M. Reif

Abstract

Drawing integrated conclusions from diverse source data requires synthesis across multiple types of information. The ToxPi (Toxicological Prioritization Index) is an analytical framework that was developed to enable integration of multiple sources of evidence by transforming data into integrated, visual profiles. Methodological improvements have advanced ToxPi and expanded its applicability, necessitating a new, consolidated software platform to provide functionality, while preserving flexibility for future updates. We detail the implementation of a new graphical user interface for ToxPi (Toxicological Prioritization Index) that provides interactive visualization, analysis, reporting, and portability. The interface is deployed as a stand-alone, platform-independent Java application, with a modular design to accommodate inclusion of future analytics. The new ToxPi interface introduces several features, from flexible data import formats (including legacy formats that permit backward compatibility) to similarity-based clustering to options for high-resolution graphical output. We present the new ToxPi interface for dynamic exploration, visualization, and sharing of integrated data models. The ToxPi interface is freely-available as a single compressed download that includes the main Java executable, all libraries, example data files, and a complete user manual from http://toxpi.org .

Twitter Demographics

The data shown below were collected from the profiles of 8 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 14%
Researcher 4 14%
Student > Master 3 11%
Other 2 7%
Professor 2 7%
Other 5 18%
Unknown 8 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 14%
Pharmacology, Toxicology and Pharmaceutical Science 3 11%
Environmental Science 3 11%
Computer Science 2 7%
Agricultural and Biological Sciences 2 7%
Other 4 14%
Unknown 10 36%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 26 March 2018.
All research outputs
#7,118,144
of 13,791,430 outputs
Outputs from BMC Bioinformatics
#2,512
of 5,139 outputs
Outputs of similar age
#114,505
of 273,331 outputs
Outputs of similar age from BMC Bioinformatics
#5
of 25 outputs
Altmetric has tracked 13,791,430 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,139 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 48th percentile – i.e., 48% 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 273,331 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 57% of its contemporaries.
We're also able to compare this research output to 25 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.