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Phosphoproteomics-Based Systems Analysis of Signal Transduction Networks

Overview of attention for article published in Frontiers in Physiology, January 2012
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Title
Phosphoproteomics-Based Systems Analysis of Signal Transduction Networks
Published in
Frontiers in Physiology, January 2012
DOI 10.3389/fphys.2011.00113
Pubmed ID
Authors

Hiroko Kozuka-Hata, Shinya Tasaki, Masaaki Oyama

Abstract

Signal transduction systems coordinate complex cellular information to regulate biological events such as cell proliferation and differentiation. Although the accumulating evidence on widespread association of signaling molecules has revealed essential contribution of phosphorylation-dependent interaction networks to cellular regulation, their dynamic behavior is mostly yet to be analyzed. Recent technological advances regarding mass spectrometry-based quantitative proteomics have enabled us to describe the comprehensive status of phosphorylated molecules in a time-resolved manner. Computational analyses based on the phosphoproteome dynamics accelerate generation of novel methodologies for mathematical analysis of cellular signaling. Phosphoproteomics-based numerical modeling can be used to evaluate regulatory network elements from a statistical point of view. Integration with transcriptome dynamics also uncovers regulatory hubs at the transcriptional level. These omics-based computational methodologies, which have firstly been applied to representative signaling systems such as the epidermal growth factor receptor pathway, have now opened up a gate for systems analysis of signaling networks involved in immune response and cancer.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Luxembourg 1 3%
Unknown 32 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 32%
Researcher 7 21%
Student > Master 4 12%
Student > Bachelor 3 9%
Other 2 6%
Other 1 3%
Unknown 6 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 47%
Biochemistry, Genetics and Molecular Biology 4 12%
Computer Science 2 6%
Medicine and Dentistry 2 6%
Mathematics 1 3%
Other 2 6%
Unknown 7 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 03 January 2012.
All research outputs
#20,165,369
of 22,675,759 outputs
Outputs from Frontiers in Physiology
#9,270
of 13,467 outputs
Outputs of similar age
#221,176
of 244,088 outputs
Outputs of similar age from Frontiers in Physiology
#208
of 309 outputs
Altmetric has tracked 22,675,759 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 13,467 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. 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 244,088 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 309 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.