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Combined microRNA and ER expression: a new classifier for familial and sporadic breast cancer patients

Overview of attention for article published in Journal of Translational Medicine, November 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 tweeters

Citations

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8 Dimensions

Readers on

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28 Mendeley
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Title
Combined microRNA and ER expression: a new classifier for familial and sporadic breast cancer patients
Published in
Journal of Translational Medicine, November 2014
DOI 10.1186/s12967-014-0319-6
Pubmed ID
Authors

Katia Danza, Simona De Summa, Brunella Pilato, Massimo Carella, Orazio Palumbo, Ondina Popescu, Angelo Paradiso, Rosamaria Pinto, Stefania Tommasi

Abstract

The role of miRNAs in familial breast cancer (fBC) is poorly investigated as also in the BRCA-like tumors. To identify a specific miRNA expression pattern which could allow a better fBC classification not only based on clinico-pathological and immunophenotypical parameters we analyzed miRNA profile in familial and sporadic samples. Moreover since BRCA1 tumors and sporadic triple negative (TN) breast tumors share similarities regarding clinical outcomes and some histological characteristics, we focused on TN and not TN cases.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 25%
Student > Bachelor 5 18%
Student > Master 3 11%
Professor > Associate Professor 3 11%
Professor 2 7%
Other 5 18%
Unknown 3 11%
Readers by discipline Count As %
Medicine and Dentistry 7 25%
Biochemistry, Genetics and Molecular Biology 6 21%
Agricultural and Biological Sciences 4 14%
Engineering 2 7%
Nursing and Health Professions 1 4%
Other 5 18%
Unknown 3 11%

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 20 November 2014.
All research outputs
#2,022,134
of 4,531,279 outputs
Outputs from Journal of Translational Medicine
#471
of 1,272 outputs
Outputs of similar age
#56,585
of 139,044 outputs
Outputs of similar age from Journal of Translational Medicine
#32
of 75 outputs
Altmetric has tracked 4,531,279 research outputs across all sources so far. This one has received more attention than most of these and is in the 52nd percentile.
So far Altmetric has tracked 1,272 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 55% 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 139,044 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 56% of its contemporaries.
We're also able to compare this research output to 75 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 50% of its contemporaries.