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Extending pathways and processes using molecular interaction networks to analyse cancer genome data

Overview of attention for article published in BMC Bioinformatics, December 2010
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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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
15 X users

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
112 Mendeley
citeulike
10 CiteULike
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Title
Extending pathways and processes using molecular interaction networks to analyse cancer genome data
Published in
BMC Bioinformatics, December 2010
DOI 10.1186/1471-2105-11-597
Pubmed ID
Authors

Enrico Glaab, Anaïs Baudot, Natalio Krasnogor, Alfonso Valencia

Abstract

Cellular processes and pathways, whose deregulation may contribute to the development of cancers, are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus. However, recent functional genomic experiments have identified thousands of interactions for the signalling canonical proteins, challenging the traditional view of pathways as independent functional entities. Combining information from pathway databases and interaction networks obtained from functional genomic experiments is therefore a promising strategy to obtain more robust pathway and process representations, facilitating the study of cancer-related pathways.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 6 5%
France 5 4%
United States 4 4%
Luxembourg 4 4%
Spain 3 3%
Germany 2 2%
Sweden 1 <1%
Canada 1 <1%
Mexico 1 <1%
Other 5 4%
Unknown 80 71%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 32%
Student > Ph. D. Student 31 28%
Other 8 7%
Student > Master 6 5%
Student > Postgraduate 5 4%
Other 18 16%
Unknown 8 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 56%
Computer Science 18 16%
Biochemistry, Genetics and Molecular Biology 7 6%
Medicine and Dentistry 7 6%
Mathematics 3 3%
Other 2 2%
Unknown 12 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 February 2018.
All research outputs
#3,542,696
of 24,143,470 outputs
Outputs from BMC Bioinformatics
#1,269
of 7,506 outputs
Outputs of similar age
#21,304
of 187,724 outputs
Outputs of similar age from BMC Bioinformatics
#10
of 53 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,506 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 83% 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 187,724 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 88% of its contemporaries.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.