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RNA profiling reveals familial aggregation of molecular subtypes in non-BRCA1/2 breast cancer families

Overview of attention for article published in BMC Medical Genomics, January 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
1 news outlet
twitter
4 tweeters

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
31 Mendeley
citeulike
1 CiteULike
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Title
RNA profiling reveals familial aggregation of molecular subtypes in non-BRCA1/2 breast cancer families
Published in
BMC Medical Genomics, January 2014
DOI 10.1186/1755-8794-7-9
Pubmed ID
Authors

Martin J Larsen, Mads Thomassen, Qihua Tan, Anne-Vibeke Lænkholm, Martin Bak, Kristina P Sørensen, Mette Klarskov Andersen, Torben A Kruse, Anne-Marie Gerdes

Abstract

In more than 70% of families with a strong history of breast and ovarian cancers, pathogenic mutation in BRCA1 or BRCA2 cannot be identified, even though hereditary factors are expected to be involved. It has been proposed that tumors with similar molecular phenotypes also share similar underlying pathophysiological mechanisms. In the current study, the aim was to investigate if global RNA profiling can be used to identify functional subgroups within breast tumors from families tested negative for BRCA1/2 germline mutations and how these subgroupings relate to different breast cancer patients within the same family.

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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Denmark 1 3%
Egypt 1 3%
Unknown 28 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 19%
Researcher 6 19%
Student > Master 5 16%
Student > Doctoral Student 2 6%
Student > Bachelor 2 6%
Other 6 19%
Unknown 4 13%
Readers by discipline Count As %
Medicine and Dentistry 8 26%
Agricultural and Biological Sciences 8 26%
Biochemistry, Genetics and Molecular Biology 6 19%
Computer Science 3 10%
Psychology 1 3%
Other 0 0%
Unknown 5 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 12 March 2015.
All research outputs
#1,724,419
of 15,821,424 outputs
Outputs from BMC Medical Genomics
#71
of 826 outputs
Outputs of similar age
#28,054
of 256,970 outputs
Outputs of similar age from BMC Medical Genomics
#1
of 16 outputs
Altmetric has tracked 15,821,424 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 826 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 91% 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 256,970 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.