↓ Skip to main content

Post-transcriptional Expression Regulation in the YeastSaccharomyces cerevisiaeon a Genomic Scale

Overview of attention for article published in Molecular and Cellular Proteomics, August 2004
Altmetric Badge

Mentioned by

f1000
1 research highlight platform

Citations

dimensions_citation
177 Dimensions

Readers on

mendeley
168 Mendeley
citeulike
5 CiteULike
connotea
1 Connotea
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Post-transcriptional Expression Regulation in the YeastSaccharomyces cerevisiaeon a Genomic Scale
Published in
Molecular and Cellular Proteomics, August 2004
DOI 10.1074/mcp.m400099-mcp200
Pubmed ID
Authors

Andreas Beyer, Jens Hollunder, Heinz-Peter Nasheuer, Thomas Wilhelm

Abstract

Based on large-scale data for the yeast Saccharomyces cerevisiae (protein and mRNA abundance, translational status, transcript length), we investigate the relation of transcription, translation, and protein turnover on a genome-wide scale. We elucidate variations between different spatial cell compartments and functional modules by comparing protein-to-mRNA ratios, translational activity, and a novel descriptor for protein-specific degradation (protein half-life descriptor). This analysis helps to understand the cell's strategy to use transcriptional and post-transcriptional regulation mechanisms for managing protein levels. For instance, it is possible to identify modules that are subject to suppressed translation under normal conditions ("translation on demand"). In order to reduce inconsistencies between the datasets, we compiled a new reference mRNA abundance dataset and we present a novel approach to correct large microarray signals for a saturation bias. Accounting for ribosome density based on transcript length rather than ORF length improves the correlation of observed protein levels to translational activity. We discuss potential causes for the deviations of these correlations. Finally, we introduce a quantitative descriptor for protein degradation (protein half-life descriptor) and compare it to measured half-lives. The study demonstrates significant post-transcriptional control of protein levels for a number of different compartments and functional modules, which is missed when exclusively focusing on transcript levels.

Mendeley readers

The data shown below were compiled from readership statistics for 168 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 4%
Germany 3 2%
Spain 2 1%
South Africa 1 <1%
Brazil 1 <1%
Australia 1 <1%
Israel 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Other 3 2%
Unknown 148 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 52 31%
Researcher 49 29%
Student > Master 14 8%
Student > Doctoral Student 9 5%
Student > Bachelor 9 5%
Other 30 18%
Unknown 5 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 100 60%
Biochemistry, Genetics and Molecular Biology 31 18%
Computer Science 7 4%
Physics and Astronomy 4 2%
Environmental Science 3 2%
Other 13 8%
Unknown 10 6%

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 December 2004.
All research outputs
#7,834,020
of 12,485,055 outputs
Outputs from Molecular and Cellular Proteomics
#1,732
of 2,335 outputs
Outputs of similar age
#7,562,465
of 11,927,625 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#1,719
of 2,318 outputs
Altmetric has tracked 12,485,055 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,335 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 18th percentile – i.e., 18% 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 11,927,625 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2,318 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.