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A Structural Systems Biology Approach for Quantifying the Systemic Consequences of Missense Mutations in Proteins

Overview of attention for article published in PLoS Computational Biology, October 2012
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Title
A Structural Systems Biology Approach for Quantifying the Systemic Consequences of Missense Mutations in Proteins
Published in
PLoS Computational Biology, October 2012
DOI 10.1371/journal.pcbi.1002738
Pubmed ID
Authors

Tammy M. K. Cheng, Lucas Goehring, Linda Jeffery, Yu-En Lu, Jacqueline Hayles, Béla Novák, Paul A. Bates

Abstract

Gauging the systemic effects of non-synonymous single nucleotide polymorphisms (nsSNPs) is an important topic in the pursuit of personalized medicine. However, it is a non-trivial task to understand how a change at the protein structure level eventually affects a cell's behavior. This is because complex information at both the protein and pathway level has to be integrated. Given that the idea of integrating both protein and pathway dynamics to estimate the systemic impact of missense mutations in proteins remains predominantly unexplored, we investigate the practicality of such an approach by formulating mathematical models and comparing them with experimental data to study missense mutations. We present two case studies: (1) interpreting systemic perturbation for mutations within the cell cycle control mechanisms (G2 to mitosis transition) for yeast; (2) phenotypic classification of neuron-related human diseases associated with mutations within the mitogen-activated protein kinase (MAPK) pathway. We show that the application of simplified mathematical models is feasible for understanding the effects of small sequence changes on cellular behavior. Furthermore, we show that the systemic impact of missense mutations can be effectively quantified as a combination of protein stability change and pathway perturbation.

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The data shown below were collected from the profiles of 3 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 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 3%
Germany 1 1%
France 1 1%
Colombia 1 1%
Canada 1 1%
United Kingdom 1 1%
Iran, Islamic Republic of 1 1%
United States 1 1%
Unknown 62 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 30%
Student > Ph. D. Student 11 15%
Student > Master 10 14%
Professor 6 8%
Student > Bachelor 5 7%
Other 12 17%
Unknown 6 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 39%
Biochemistry, Genetics and Molecular Biology 19 27%
Computer Science 5 7%
Chemistry 4 6%
Medicine and Dentistry 2 3%
Other 5 7%
Unknown 8 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 06 November 2012.
All research outputs
#16,063,069
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#6,970
of 8,964 outputs
Outputs of similar age
#117,894
of 193,801 outputs
Outputs of similar age from PLoS Computational Biology
#69
of 109 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 19th percentile – i.e., 19% 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 193,801 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.