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RegaDB: community-driven data management and analysis for infectious diseases

Overview of attention for article published in Bioinformatics, May 2013
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3 X users
reddit
1 Redditor

Citations

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30 Dimensions

Readers on

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51 Mendeley
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3 CiteULike
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Title
RegaDB: community-driven data management and analysis for infectious diseases
Published in
Bioinformatics, May 2013
DOI 10.1093/bioinformatics/btt162
Pubmed ID
Authors

Pieter Libin, Gertjan Beheydt, Koen Deforche, Stijn Imbrechts, Fossie Ferreira, Kristel Van Laethem, Kristof Theys, Ana Patricia Carvalho, Joana Cavaco-Silva, Giuseppe Lapadula, Carlo Torti, Matthias Assel, Stefan Wesner, Joke Snoeck, Jean Ruelle, Annelies De Bel, Patrick Lacor, Paul De Munter, Eric Van Wijngaerden, Maurizio Zazzi, Rolf Kaiser, Ahidjo Ayouba, Martine Peeters, Tulio de Oliveira, Luiz C. J. Alcantara, Zehava Grossman, Peter Sloot, Dan Otelea, Simona Paraschiv, Charles Boucher, Ricardo J. Camacho, Anne-Mieke Vandamme

Abstract

RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface. Availability and implementation: Source code, binaries and documentation are available on http://rega.kuleuven.be/cev/regadb. RegaDB is written in the Java programming language, using a web-service-oriented architecture.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 2%
Germany 1 2%
Tanzania, United Republic of 1 2%
Netherlands 1 2%
Sweden 1 2%
Belgium 1 2%
United States 1 2%
Unknown 44 86%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 33%
Student > Ph. D. Student 7 14%
Student > Master 6 12%
Professor > Associate Professor 5 10%
Student > Doctoral Student 3 6%
Other 7 14%
Unknown 6 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 25%
Computer Science 10 20%
Biochemistry, Genetics and Molecular Biology 5 10%
Medicine and Dentistry 5 10%
Engineering 3 6%
Other 7 14%
Unknown 8 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 10 November 2013.
All research outputs
#16,048,009
of 25,374,917 outputs
Outputs from Bioinformatics
#9,769
of 12,809 outputs
Outputs of similar age
#118,747
of 204,142 outputs
Outputs of similar age from Bioinformatics
#108
of 167 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,809 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 20th percentile – i.e., 20% 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 204,142 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 167 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.