A quantitative estimation of the global translational activity in logarithmically growing yeast cells
2008

Estimating Global Translational Activity in Yeast Cells

publication Evidence: moderate

Author Information

Author(s): Tobias von der Haar

Primary Institution: University of Kent

Hypothesis

Can genome-wide datasets accurately predict global translational activity in yeast cells?

Conclusion

The study provides a benchmark for global translational activity in yeast cells, highlighting the limitations of existing datasets.

Supporting Evidence

  • Current datasets predict a production rate of about 13,000 proteins per haploid cell per second under fast growth conditions.
  • The global translational activity of yeast cells serves as a benchmark for interpreting biochemical data on translation factors.
  • Random errors in datasets are largely averaged out when calculating global parameters.

Takeaway

This study looks at how many proteins yeast cells make and shows that we can use existing data to get a good idea of this, even if some of the data isn't perfect.

Methodology

The study analyzed genome-wide datasets for protein abundance, protein half-lives, and mRNA levels to estimate global translational activity.

Potential Biases

Potential biases arise from the systematic shifts in reported values between different studies.

Limitations

The accuracy of individual gene predictions is limited due to random and systematic errors in the datasets.

Statistical Information

Confidence Interval

6,500–19,500 proteins per cell per second

Digital Object Identifier (DOI)

10.1186/1752-0509-2-87

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