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GraphSAW: A web-based system for graphical analysis of drug interactions and side effects using pharmaceutical and molecular data

Overview of attention for article published in BMC Medical Informatics and Decision Making, February 2015
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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 (88th percentile)

Mentioned by

news
1 news outlet
twitter
4 tweeters
patent
1 patent

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
31 Mendeley
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Title
GraphSAW: A web-based system for graphical analysis of drug interactions and side effects using pharmaceutical and molecular data
Published in
BMC Medical Informatics and Decision Making, February 2015
DOI 10.1186/s12911-015-0139-5
Pubmed ID
Authors

Alban Shoshi, Tobias Hoppe, Benjamin Kormeier, Venus Ogultarhan, Ralf Hofestädt

Abstract

Adverse drug reactions are one of the most common causes of death in industrialized Western countries. Nowadays, empirical data from clinical studies for the approval and monitoring of drugs and molecular databases is available. The integration of database information is a promising method for providing well-based knowledge to avoid adverse drug reactions. This paper presents our web-based decision support system GraphSAW which analyzes and evaluates drug interactions and side effects based on data from two commercial and two freely available molecular databases. The system is able to analyze single and combined drug-drug interactions, drug-molecule interactions as well as single and cumulative side effects. In addition, it allows exploring associative networks of drugs, molecules, metabolic pathways, and diseases in an intuitive way. The molecular medication analysis includes the capabilities of the upper features. A statistical evaluation of the integrated data and top 20 drugs concerning drug interactions and side effects is performed. The results of the data analysis give an overview of all theoretically possible drug interactions and side effects. The evaluation shows a mismatch between pharmaceutical and molecular databases. The concordance of drug interactions was about 12% and 9% of drug side effects. An application case with prescribed data of 11 patients is presented in order to demonstrate the functionality of the system under real conditions. For each patient at least two interactions occured in every medication and about 8% of total diseases were possibly induced by drug therapy. GraphSAW ( http://tunicata.techfak.uni-bielefeld.de/graphsaw/ ) is meant to be a web-based system for health professionals and researchers. GraphSAW provides comprehensive drug-related knowledge and an improved medication analysis which may support efforts to reduce the risk of medication errors and numerous drastic side effects.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Finland 1 3%
Spain 1 3%
Unknown 29 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 26%
Researcher 5 16%
Student > Ph. D. Student 5 16%
Student > Doctoral Student 3 10%
Student > Bachelor 3 10%
Other 4 13%
Unknown 3 10%
Readers by discipline Count As %
Medicine and Dentistry 10 32%
Computer Science 6 19%
Social Sciences 3 10%
Pharmacology, Toxicology and Pharmaceutical Science 2 6%
Agricultural and Biological Sciences 2 6%
Other 5 16%
Unknown 3 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 January 2020.
All research outputs
#1,638,727
of 17,648,139 outputs
Outputs from BMC Medical Informatics and Decision Making
#120
of 1,608 outputs
Outputs of similar age
#24,807
of 222,264 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 1 outputs
Altmetric has tracked 17,648,139 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,608 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 92% 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 222,264 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 88% of its contemporaries.
We're also able to compare this research output to 1 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