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Complex-based analysis of dysregulated cellular processes in cancer

Overview of attention for article published in BMC Systems Biology, December 2014
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Title
Complex-based analysis of dysregulated cellular processes in cancer
Published in
BMC Systems Biology, December 2014
DOI 10.1186/1752-0509-8-s4-s1
Pubmed ID
Authors

Sriganesh Srihari, Piyush B Madhamshettiwar, Sarah Song, Chao Liu, Peter T Simpson, Kum Kum Khanna, Mark A Ragan

Abstract

Differential expression analysis of (individual) genes is often used to study their roles in diseases. However, diseases such as cancer are a result of the combined effect of multiple genes. Gene products such as proteins seldom act in isolation, but instead constitute stable multi-protein complexes performing dedicated functions. Therefore, complexes aggregate the effect of individual genes (proteins) and can be used to gain a better understanding of cancer mechanisms. Here, we observe that complexes show considerable changes in their expression, in turn directed by the concerted action of transcription factors (TFs), across cancer conditions. We seek to gain novel insights into cancer mechanisms through a systematic analysis of complexes and their transcriptional regulation.

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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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Russia 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 32%
Researcher 3 16%
Student > Ph. D. Student 2 11%
Professor > Associate Professor 2 11%
Student > Master 1 5%
Other 1 5%
Unknown 4 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 21%
Medicine and Dentistry 3 16%
Computer Science 3 16%
Biochemistry, Genetics and Molecular Biology 2 11%
Engineering 2 11%
Other 1 5%
Unknown 4 21%
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 19 December 2014.
All research outputs
#22,758,309
of 25,371,288 outputs
Outputs from BMC Systems Biology
#1,004
of 1,132 outputs
Outputs of similar age
#314,300
of 368,077 outputs
Outputs of similar age from BMC Systems Biology
#38
of 47 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 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. 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 368,077 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 47 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.