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GUILDify: a web server for phenotypic characterization of genes through biological data integration and network-based prioritization algorithms

Overview of attention for article published in Bioinformatics, February 2014
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Title
GUILDify: a web server for phenotypic characterization of genes through biological data integration and network-based prioritization algorithms
Published in
Bioinformatics, February 2014
DOI 10.1093/bioinformatics/btu092
Pubmed ID
Authors

Emre Guney, Javier Garcia-Garcia, Baldo Oliva

Abstract

Determining genetic factors underlying various phenotypes is hindered by the involvement of multiple genes acting cooperatively. Over the past years, disease-gene prioritization has been central to identify genes implicated in human disorders. Special attention has been paid on using physical interactions between the proteins encoded by the genes to link them with diseases. Such methods exploit the guilt-by-association principle in the protein interaction network to uncover novel disease-gene associations. These methods rely on the proximity of a gene in the network to the genes associated with a phenotype and require a set of initial associations. Here, we present GUILDify, an easy-to-use web server for the phenotypic characterization of genes. GUILDify offers a prioritization approach based on the protein-protein interaction network where the initial phenotype-gene associations are retrieved via free text search on biological databases. GUILDify web server does not restrict the prioritization to any predefined phenotype, supports multiple species and accepts user-specified genes. It also prioritizes drugs based on the ranking of their targets, unleashing opportunities for repurposing drugs for novel therapies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 3 5%
Turkey 1 2%
Netherlands 1 2%
Unknown 55 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 32%
Student > Ph. D. Student 13 22%
Student > Master 5 8%
Student > Doctoral Student 4 7%
Professor > Associate Professor 4 7%
Other 6 10%
Unknown 9 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 22%
Biochemistry, Genetics and Molecular Biology 11 18%
Medicine and Dentistry 8 13%
Computer Science 7 12%
Business, Management and Accounting 1 2%
Other 6 10%
Unknown 14 23%
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 06 June 2019.
All research outputs
#16,048,009
of 25,374,917 outputs
Outputs from Bioinformatics
#9,770
of 12,809 outputs
Outputs of similar age
#190,763
of 330,520 outputs
Outputs of similar age from Bioinformatics
#144
of 191 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 330,520 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 191 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.