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Evolutionary and Biochemical Aspects of Chemical Stress Resistance in Saccharomyces cerevisiae

Overview of attention for article published in Frontiers in Genetics, January 2012
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Title
Evolutionary and Biochemical Aspects of Chemical Stress Resistance in Saccharomyces cerevisiae
Published in
Frontiers in Genetics, January 2012
DOI 10.3389/fgene.2012.00047
Pubmed ID
Authors

Thiago Motta Venancio, Daniel Bellieny-Rabelo, L. Aravind

Abstract

Large-scale chemical genetics screens (chemogenomics) in yeast have been widely used to find drug targets, understand the mechanism-of-action of compounds, and unravel the biochemistry of drug resistance. Chemogenomics is based on the comparison of growth of gene deletants in the presence and absence of a chemical substance. Such studies showed that more than 90% of the yeast genes are required for growth in the presence of at least one chemical. Analysis of these data, using computational approaches, has revealed non-trivial features of the natural chemical tolerance systems. As a result two non-overlapping sets of genes are seen to respectively impart robustness and evolvability in the context of natural chemical resistance. The former is composed of multidrug-resistance genes, whereas the latter comprises genes sharing chemical genetic profiles with many others. Recent publications showing the potential applications chemogenomics in studying the pharmacological basis of various drugs are discussed, as well as the expansion of chemogenomics to other organisms. Finally, integration of chemogenomics with sensitive sequence analysis and ubiquitination/phosphorylation data led to the discovery of a new conserved domain and important post-translational modification pathways involved in stress resistance.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 8%
Unknown 23 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 36%
Student > Ph. D. Student 6 24%
Professor > Associate Professor 2 8%
Student > Master 2 8%
Other 1 4%
Other 3 12%
Unknown 2 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 64%
Computer Science 2 8%
Biochemistry, Genetics and Molecular Biology 2 8%
Unknown 5 20%
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 17 April 2012.
All research outputs
#15,249,959
of 22,675,759 outputs
Outputs from Frontiers in Genetics
#5,376
of 11,737 outputs
Outputs of similar age
#163,175
of 244,088 outputs
Outputs of similar age from Frontiers in Genetics
#155
of 255 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,737 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 48th percentile – i.e., 48% 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 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 255 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.