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The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside

Overview of attention for article published in Journal of Biomedical Semantics, May 2011
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1 X user

Citations

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71 Dimensions

Readers on

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180 Mendeley
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9 CiteULike
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Title
The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside
Published in
Journal of Biomedical Semantics, May 2011
DOI 10.1186/2041-1480-2-s2-s1
Pubmed ID
Authors

Joanne S Luciano, Bosse Andersson, Colin Batchelor, Olivier Bodenreider, Tim Clark, Christine K Denney, Christopher Domarew, Thomas Gambet, Lee Harland, Anja Jentzsch, Vipul Kashyap, Peter Kos, Julia Kozlovsky, Timothy Lebo, Scott M Marshall, Jamie P McCusker, Deborah L McGuinness, Chimezie Ogbuji, Elgar Pichler, Robert L Powers, Eric Prud’hommeaux, Matthias Samwald, Lynn Schriml, Peter J Tonellato, Patricia L Whetzel, Jun Zhao, Susie Stephens, Michel Dumontier

Abstract

Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 180 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 13 7%
Germany 5 3%
United Kingdom 3 2%
Brazil 3 2%
Netherlands 2 1%
Canada 2 1%
Spain 2 1%
Portugal 1 <1%
Iceland 1 <1%
Other 3 2%
Unknown 145 81%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 23%
Researcher 40 22%
Student > Master 22 12%
Professor > Associate Professor 12 7%
Student > Doctoral Student 11 6%
Other 38 21%
Unknown 15 8%
Readers by discipline Count As %
Computer Science 62 34%
Agricultural and Biological Sciences 32 18%
Medicine and Dentistry 30 17%
Engineering 6 3%
Biochemistry, Genetics and Molecular Biology 5 3%
Other 21 12%
Unknown 24 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 27 June 2013.
All research outputs
#18,341,369
of 22,713,403 outputs
Outputs from Journal of Biomedical Semantics
#299
of 364 outputs
Outputs of similar age
#96,076
of 111,858 outputs
Outputs of similar age from Journal of Biomedical Semantics
#9
of 9 outputs
Altmetric has tracked 22,713,403 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 8th percentile – i.e., 8% 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 111,858 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one.