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KinMap: a web-based tool for interactive navigation through human kinome data

Overview of attention for article published in BMC Bioinformatics, January 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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6 X users
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1 Google+ user

Citations

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238 Dimensions

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182 Mendeley
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Title
KinMap: a web-based tool for interactive navigation through human kinome data
Published in
BMC Bioinformatics, January 2017
DOI 10.1186/s12859-016-1433-7
Pubmed ID
Authors

Sameh Eid, Samo Turk, Andrea Volkamer, Friedrich Rippmann, Simone Fulle

Abstract

Annotations of the phylogenetic tree of the human kinome is an intuitive way to visualize compound profiling data, structural features of kinases or functional relationships within this important class of proteins. The increasing volume and complexity of kinase-related data underlines the need for a tool that enables complex queries pertaining to kinase disease involvement and potential therapeutic uses of kinase inhibitors. Here, we present KinMap, a user-friendly online tool that facilitates the interactive navigation through kinase knowledge by linking biochemical, structural, and disease association data to the human kinome tree. To this end, preprocessed data from freely-available sources, such as ChEMBL, the Protein Data Bank, and the Center for Therapeutic Target Validation platform are integrated into KinMap and can easily be complemented by proprietary data. The value of KinMap will be exemplarily demonstrated for uncovering new therapeutic indications of known kinase inhibitors and for prioritizing kinases for drug development efforts. KinMap represents a new generation of kinome tree viewers which facilitates interactive exploration of the human kinome. KinMap enables generation of high-quality annotated images of the human kinome tree as well as exchange of kinome-related data in scientific communications. Furthermore, KinMap supports multiple input and output formats and recognizes alternative kinase names and links them to a unified naming scheme, which makes it a useful tool across different disciplines and applications. A web-service of KinMap is freely available at http://www.kinhub.org/kinmap/ .

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 182 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 1%
Unknown 180 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 23%
Researcher 27 15%
Student > Master 13 7%
Student > Bachelor 13 7%
Other 11 6%
Other 26 14%
Unknown 51 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 57 31%
Agricultural and Biological Sciences 24 13%
Chemistry 22 12%
Pharmacology, Toxicology and Pharmaceutical Science 8 4%
Computer Science 5 3%
Other 17 9%
Unknown 49 27%
Attention Score in Context

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 15 January 2017.
All research outputs
#6,822,151
of 22,903,988 outputs
Outputs from BMC Bioinformatics
#2,597
of 7,305 outputs
Outputs of similar age
#127,075
of 420,652 outputs
Outputs of similar age from BMC Bioinformatics
#48
of 138 outputs
Altmetric has tracked 22,903,988 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 7,305 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 63% 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 420,652 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 138 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.