S. cerevisiae

Protein name:

e.g. CDC14, OAF3, YFR028C

Protein name:

e.g. CDC14, OAF3, YFR028C

Protein name:

e.g. CDC14, OAF3, YFR028C

Protein name:

e.g. CDC14, OAF3, YFR028C

Protein name:

e.g. CDC14, OAF3, YFR028C

Protein name:

e.g. CDC14, OAF3, YFR028C

Protein name:

e.g. CDC14, OAF3, YFR028C

Modeling proteome dynamics using gene expression data


Proteins levels are most relevant physiologically but measuring them genome-wide, unlike mRNA levels, remains a challenge. Therefore, mRNA levels are often implicitly used as the proxies for corresponding protein levels, even though the protein abundance is known to depend also on its half-life, which cannot be predicted from its mRNA level. Here, we propose a simple, yet very effective, method to estimate genome wide changes in protein abundances based on corresponding time-course gene expression data. The method requires, beyond gene expression data, that average proteins abundances and proteins half-lives are known or proteomic time-course data are available.