Global quantification of mammalian gene expression control

By Björn Schwanhäusser, Dorothea Busse, Na Li, G. Dittmar, J. Schuchhardt, J. Wolf, Wei Chen, Matthias Selbach. Nature, 2011

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Deep proteome and transcriptome mapping of a human cancer cell line (2011, methodology): “High-resolution mass spectrometry (MS)-based proteomics has improved at a rapid pace in recent years (Aebersold and Mann, 2003; Mallick and Kuster, 2010; Schwanhausser et al, 2011).”
Polyploidy, the Nucleotype, and Novelty: The Impact of Genome Doubling on the Biology of the Cell (2019, background): “Due to multiple levels of posttranscriptional regulation, the correlation between transcriptome and proteome is often quite weak (e.g., Schwanhausser et al. 2011; Marguerat et al. 2012; Bauernfeind and Babbitt 2017).”
Insights into the regulation of protein abundance from proteomic and transcriptomic analyses (2012, neutral): “Both techniques enable the absolute quantification of proteins in the sample, providing that the resulting intensities or counts are suitably calibrated to molecular concentration”
Human protein interaction networks across tissues and diseases (2015, background): “Since the correlation between transcript and protein levels is partial (Schwanhausser et al., 2011), proteome profiling opens a more direct way to identify feasible PPIs.”
The in silico human surfaceome (2018, background): “Although it has been shown that this derivation is possible with a gene-specific conversion factor (64), it was also demonstrated that the mRNA–protein correlation is less accurate for cell surface than for cytoplasmic proteins (44).”