Summing up the noise in gene networks

By Johan Paulsson. Nature, 2004

1,321 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/00a71fdbce915152daf7034f7e34fe788a3bd068

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Citations in the corpus

Real-time kinetics of gene activity in individual bacteria. (2005, background): “This is in principal a valid approach and has produced many important insights, but a serious problem is that the same type of response in the variance tends to be consistent with very different kinetic explanations (Paulsson, 2004).”
Stochastic gene expression and its consequences (2008, background): “, 2005) and theoretical analyses of the effects that it might have (Shahrezaei et al., 2008; Paulsson, 2004), understanding”
Fundamental Limits to Cellular Sensing (2015, background): “This means that while the network is removing the receptor input noise,which is extrinsic to the network, itwill also add its own intrinsic noise to the transmitted signal [30,61,76].”
Roles for microRNAs in conferring robustness to biological processes. (2012, neutral): “Transcription occurs in stochastic bursts (Blake et al., 2006; Raj et al., 2006), and higher transcription rates correlate with lower noise (Paulsson, 2004).”
Convergence of stochastic gene networks to hybrid piecewise deterministic processes (2011, background): “…various types of steady-state distributions of RNA and protein numbers (Kaern et al. (2005)), noise ampliﬁcation or reduction by network propagation (Paulsson (2004); Warren et al. (2006)), clock de-synchronization (Barkai and Leibler (2000)), stochastic transitions in cellular memory storage…”
Network resilience (2020, background): “For example, negative feedbacks could suppresses noise [359] and positive feedbacks could stabilized differentiated states in cells [349].”
Current approaches to gene regulatory network modelling (2007, background): “Lately experimental studies have tried to measure the level of intrinsic noise in eukaryotic cells (e.g., [95,96]).”
Quantifying intrinsic and extrinsic noise in gene transcription using the linear noise approximation: An application to single cell data (2013, background): “This stochasticity has important consequences for cellular function and it is therefore important to quantify it [Thattai and van Oudenaarden (2001), Paulsson (2004, 2005), Swain, Elowitz and Siggia (2002)].”