Intrinsic and extrinsic contributions to stochasticity in gene expression

By Peter S. Swain, Michael B. Elowitz, Eric D. Siggia. Proceedings of the National Academy of Sciences of the United States of America, 2002

1,726 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/50e7b32cf39d030868760932d33aa1805227bff8

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Citations in the corpus

Introduction to systems biology. (2007, background): “One successful approach of synthetic biology has been the analysis of noise [104–111].”
Stochastic mRNA Synthesis in Mammalian Cells (2006, background): “Both results are inconsistent with conventional stochastic models of gene expression [3,5,15,28] that predict that noise should increase steadily as the mean level of transcription decreases.”
Real-time kinetics of gene activity in individual bacteria. (2005, background): “A second E. coli study used correlations between dual fluorescent reporters and similarly interpreted the inherent randomness of gene expression (termed ‘‘intrinsic noise’’) in terms of small-number mRNA fluctuations (Elowitz et al., 2002; Swain et al., 2002).”
Identifying global regulators in transcriptional regulatory networks in bacteria. (2003, background): “The armament for our understanding of regulatory networks, co-regulated groups, clusters and their overlapping genes, has recently increased beyond the operons, regulons and stimulons, to structurally and computationally defined motifs and modules of the network [50 ,60 ,61 ], with dynamical propert”
Droplet barcoding for single cell transcriptomics applied to embryonic stem cells (2015, neutral): “Still other expression changes appear to be stochastic in nature (Paulsson, 2005; Swain et al. 2002), and may have important consequences (Losick and Desplan, 2008).”
Bistability in bacteria (2006, background): “Two kinds of noise have been identified: intrinsic and extrinsic (Swain et al., 2002).”
Stochastic modelling for quantitative description of heterogeneous biological systems (2009, background): “Although much research effort is currently focused on stochasticity (both intrinsic and extrinsic noise”
Models of stochastic gene expression (2005, background): “, if the mechanisms are linear, the normalized covariance betwee then equals the sum of all shared noise terms [20].”