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Discovering functional modules by identifying recurrent and mutually exclusive mutational patterns in tumors

Overview of attention for article published in BMC Medical Genomics, April 2011
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#26 of 236)
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
1 blog
q&a
1 Q&A thread

Citations

dimensions_citation
99 Dimensions

Readers on

mendeley
85 Mendeley
citeulike
9 CiteULike
Title
Discovering functional modules by identifying recurrent and mutually exclusive mutational patterns in tumors
Published in
BMC Medical Genomics, April 2011
DOI 10.1186/1755-8794-4-34
Pubmed ID
Authors

Christopher A Miller, Stephen H Settle, Erik P Sulman, Kenneth D Aldape, Aleksandar Milosavljevic, Miller CA, Settle SH, Sulman EP, Aldape KD, Milosavljevic A

Abstract

Assays of multiple tumor samples frequently reveal recurrent genomic aberrations, including point mutations and copy-number alterations, that affect individual genes. Analyses that extend beyond single genes are often restricted to examining pathways, interactions and functional modules that are already known.

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 5%
France 2 2%
Norway 1 1%
Switzerland 1 1%
United Kingdom 1 1%
Korea, Republic of 1 1%
Germany 1 1%
Unknown 74 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 32%
Student > Ph. D. Student 22 26%
Professor > Associate Professor 8 9%
Student > Master 7 8%
Student > Doctoral Student 4 5%
Other 13 15%
Unknown 4 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 46%
Biochemistry, Genetics and Molecular Biology 16 19%
Computer Science 13 15%
Medicine and Dentistry 9 11%
Mathematics 2 2%
Other 1 1%
Unknown 5 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 09 December 2011.
All research outputs
#421,388
of 3,684,317 outputs
Outputs from BMC Medical Genomics
#26
of 236 outputs
Outputs of similar age
#348,195
of 2,768,745 outputs
Outputs of similar age from BMC Medical Genomics
#26
of 233 outputs
Altmetric has tracked 3,684,317 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 236 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done well, scoring higher than 88% 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 2,768,745 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 87% of its contemporaries.
We're also able to compare this research output to 233 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.