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Application of computational approaches to study signalling networks of nuclear and Tyrosine kinase receptors

Overview of attention for article published in Biology Direct, October 2010
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Title
Application of computational approaches to study signalling networks of nuclear and Tyrosine kinase receptors
Published in
Biology Direct, October 2010
DOI 10.1186/1745-6150-5-58
Pubmed ID
Authors

Mouna Choura, Ahmed Rebaï

Abstract

Nuclear receptors (NRs) and Receptor tyrosine kinases (RTKs) are essential proteins in many cellular processes and sequence variations in their genes have been reported to be involved in many diseases including cancer. Although crosstalk between RTK and NR signalling and their contribution to the development of endocrine regulated cancers have been areas of intense investigation, the direct coupling of their signalling pathways remains elusive. In our understanding of the role and function of nuclear receptors on the cell membrane the interactions between nuclear receptors and tyrosine kinase receptors deserve further attention.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
Unknown 27 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 32%
Professor 7 25%
Student > Bachelor 3 11%
Student > Ph. D. Student 3 11%
Student > Master 2 7%
Other 3 11%
Unknown 1 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 68%
Biochemistry, Genetics and Molecular Biology 4 14%
Medicine and Dentistry 3 11%
Unspecified 1 4%
Unknown 1 4%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 October 2022.
All research outputs
#22,758,309
of 25,371,288 outputs
Outputs from Biology Direct
#487
of 537 outputs
Outputs of similar age
#102,518
of 107,960 outputs
Outputs of similar age from Biology Direct
#6
of 6 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 537 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 107,960 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one.