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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, June 2011
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  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
61 Dimensions

Readers on

mendeley
169 Mendeley
citeulike
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, June 2011
DOI 10.1186/2041-1480-2-s2-s1
Pubmed ID
Authors

Luciano JS, Andersson B, Batchelor C, Bodenreider O, Clark T, Denney CK, Domarew C, Gambet T, Harland L, Jentzsch A, Kashyap V, Kos P, Kozlovsky J, Lebo T, Marshall SM, McCusker JP, McGuinness DL, Ogbuji C, Pichler E, Powers RL, Prud'hommeaux E, Samwald M, Schriml L, Tonellato PJ, Whetzel PL, Zhao J, Stephens S, Dumontier M

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.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 169 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 13 8%
Germany 5 3%
Brazil 3 2%
United Kingdom 3 2%
Spain 2 1%
Netherlands 2 1%
Canada 2 1%
United Arab Emirates 1 <1%
Iceland 1 <1%
Other 3 2%
Unknown 134 79%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 42 25%
Researcher 39 23%
Student > Master 21 12%
Professor > Associate Professor 12 7%
Student > Doctoral Student 11 7%
Other 37 22%
Unknown 7 4%
Readers by discipline Count As %
Computer Science 61 36%
Agricultural and Biological Sciences 32 19%
Medicine and Dentistry 31 18%
Engineering 6 4%
Social Sciences 4 2%
Other 19 11%
Unknown 16 9%

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
#2,309,114
of 4,510,149 outputs
Outputs from Journal of Biomedical Semantics
#124
of 192 outputs
Outputs of similar age
#44,372
of 89,610 outputs
Outputs of similar age from Journal of Biomedical Semantics
#2
of 4 outputs
Altmetric has tracked 4,510,149 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 192 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 19th percentile – i.e., 19% 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 89,610 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.