Stochastic protein expression in individual cells at the single molecule level

By Long Cai, Nir Friedman, Xiaohui S. Xie. Nature, 2006

1,160 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/cf49070da10cf1d6c8e0c86322f657a02cd210ef

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Citations in the corpus

Stochastic switching in biology: from genotype to phenotype (2017, background): “The latter is a consequence of the fact that lifetime of mRNA is usually much shorter than the expressed proteins [32, 59, 178], whereas the former tends to be associated with the switching between active and inactive states of a gene.”
Convergence of stochastic gene networks to hybrid piecewise deterministic processes (2011, background): “…ideas of Delbr¨uck ( M. Delbr¨uck (1940)), capture diverse features of the experimentally observed expression variability, such as bursting (Cai et al. (2006)), various types of steady-state distributions of RNA and protein numbers (Kaern et al. (2005)), noise ampliﬁcation or reduction…”
Stochastic gene expression and its consequences (2008, methodology): “That such models are required to explain eukaryotic data but not most prokaryotic data (Cai et al., 2006; Maamar et al., 2007; Yu et al., 2006), with an important exception (Golding et al., 2005), strongly suggests that some regulator of gene expression specific to eukaryotes is responsible.”
SINGLE-PARTICLE TRACKING (2009, background): “Furthermore, even if the system can be synchronized initially, the initial synchronization is lost quickly in a multistep reaction [3].”
Toward single-molecule nanomechanical mass spectrometry (2005, methodology): “Furthermore, to reliably detect the expression of low-level signals and to understand the fundamental biological processes, it is important to develop techniques capable of single-cell or single-molecule analyse”
Analytical distributions for stochastic gene expression (2008, methodology): “Such bursts of gene expression have been measured in bacteria and eukaryotes [12, 13, 14, 28, 29].”
Stochastic modelling for quantitative description of heterogeneous biological systems (2009, background): “Experimental technology has developed to the extent that, in special cases, one can even observe stochasticity at the single-molecule leve”
Single-Cell Metabolomics: Analytical and Biological Perspectives (2013, background): “This has been shown for proteins in individual cells that were handled through microfluidics (1, 73)”