↓ Skip to main content

CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations

Overview of attention for article published in BMC Bioinformatics, November 2013
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
43 Mendeley
citeulike
3 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
CoMAGC: a corpus with multi-faceted annotations of gene-cancer relations
Published in
BMC Bioinformatics, November 2013
DOI 10.1186/1471-2105-14-323
Pubmed ID
Authors

Hee-Jin Lee, Sang-Hyung Shim, Mi-Ryoung Song, Hyunju Lee, Jong C Park

Abstract

In order to access the large amount of information in biomedical literature about genes implicated in various cancers both efficiently and accurately, the aid of text mining (TM) systems is invaluable. Current TM systems do target either gene-cancer relations or biological processes involving genes and cancers, but the former type produces information not comprehensive enough to explain how a gene affects a cancer, and the latter does not provide a concise summary of gene-cancer relations.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
United States 1 2%
Canada 1 2%
Australia 1 2%
Unknown 39 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 21%
Student > Bachelor 7 16%
Student > Ph. D. Student 6 14%
Student > Master 6 14%
Professor > Associate Professor 3 7%
Other 4 9%
Unknown 8 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 28%
Computer Science 12 28%
Engineering 3 7%
Medicine and Dentistry 3 7%
Linguistics 2 5%
Other 4 9%
Unknown 7 16%

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 27 February 2015.
All research outputs
#13,340,081
of 21,353,728 outputs
Outputs from BMC Bioinformatics
#4,499
of 6,926 outputs
Outputs of similar age
#114,614
of 209,757 outputs
Outputs of similar age from BMC Bioinformatics
#243
of 380 outputs
Altmetric has tracked 21,353,728 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 6,926 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 209,757 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 380 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.