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Subtypes of primary colorectal tumors correlate with response to targeted treatment in colorectal cell lines

Overview of attention for article published in BMC Medical Genomics, December 2012
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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 (81st percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

twitter
1 tweeter
patent
2 patents

Citations

dimensions_citation
163 Dimensions

Readers on

mendeley
213 Mendeley
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Title
Subtypes of primary colorectal tumors correlate with response to targeted treatment in colorectal cell lines
Published in
BMC Medical Genomics, December 2012
DOI 10.1186/1755-8794-5-66
Pubmed ID
Authors

Andreas Schlicker, Garry Beran, Christine M Chresta, Gael McWalter, Alison Pritchard, Susie Weston, Sarah Runswick, Sara Davenport, Kerry Heathcote, Denis Alferez Castro, George Orphanides, Tim French, Lodewyk FA Wessels

Abstract

Colorectal cancer (CRC) is a heterogeneous and biologically poorly understood disease. To tailor CRC treatment, it is essential to first model this heterogeneity by defining subtypes of patients with homogeneous biological and clinical characteristics and second match these subtypes to cell lines for which extensive pharmacological data is available, thus linking targeted therapies to patients most likely to respond to treatment.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 213 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 <1%
France 2 <1%
Italy 1 <1%
Korea, Republic of 1 <1%
Netherlands 1 <1%
South Africa 1 <1%
Canada 1 <1%
Spain 1 <1%
United States 1 <1%
Other 0 0%
Unknown 202 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 59 28%
Student > Ph. D. Student 49 23%
Student > Master 25 12%
Student > Bachelor 16 8%
Professor > Associate Professor 12 6%
Other 31 15%
Unknown 21 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 62 29%
Medicine and Dentistry 56 26%
Biochemistry, Genetics and Molecular Biology 46 22%
Computer Science 6 3%
Engineering 3 1%
Other 13 6%
Unknown 27 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 17 May 2017.
All research outputs
#3,351,937
of 17,367,552 outputs
Outputs from BMC Medical Genomics
#170
of 915 outputs
Outputs of similar age
#48,044
of 264,175 outputs
Outputs of similar age from BMC Medical Genomics
#7
of 45 outputs
Altmetric has tracked 17,367,552 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 915 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 81% 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 264,175 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 81% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.