Linking stochastic dynamics to population distribution: an analytical framework of gene expression.

By Nir Friedman, Long Cai, X. S. Xie. Physical Review Letters, 2006

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Stochastic gene expression and its consequences (2008, background): “…models of transcriptional bursting add another important source of stochasticity beyond random events in transcription and translation, which have now been analyzed theoretically in some detail (Friedman et al., 2006; Karmakar and Bose, 2004; Kepler and Elston, 2001; Pedraza and Paulsson, 2008).”
Analytical distributions for stochastic gene expression (2008, background): “They derived a gamma distribution for steadystate protein numbers [19].”
Stochastic switching in biology: from genotype to phenotype (2017, methodology): “It is also possible to incorporate autoregulatory feedback into the CK equation by allowing the burst rate to depend on the current level of protein x, which acts as its own transcription factor [101, 171, 172, 257]:”