Cellular noise

This measure is dimensionless, allowing a relative comparison of the importance of noise, without necessitating knowledge of the absolute mean.

Other quantities often used for mathematical convenience are the Fano factor: and the normalized variance: The first experimental account and analysis of gene expression noise in prokaryotes is from Becskei & Serrano [4] and from Alexander van Oudenaarden's lab.

[5] The first experimental account and analysis of gene expression noise in eukaryotes is from James J. Collins's lab.

Intrinsic and extrinsic noise levels are often compared in dual reporter studies, in which the expression levels of two identically regulated genes (often fluorescent reporters like GFP and YFP) are plotted for each cell in a population.

In fact, any deviation of the dual-reporter scatter plot from circular symmetry indicates extrinsic noise.

[8] Note: These lists are illustrative, not exhaustive, and identification of noise sources is an active and expanding area of research.

[17] Note: These lists are illustrative, not exhaustive, and identification of noise effects is an active and expanding area of research.

As many quantities of cell biological interest are present in discrete copy number within the cell (single DNAs, dozens of mRNAs, hundreds of proteins), tools from discrete stochastic mathematics are often used to analyse and model cellular noise.

A canonical model for noise gene expression, where the processes of DNA activation, transcription and translation are all represented as Poisson processes with given rates, gives a master equation which may be solved exactly (with generating functions) under various assumptions or approximated with stochastic tools like Van Kampen's system size expansion.

The problem of inferring the values of parameters in stochastic models (parametric inference) for biological processes, which are typically characterised by sparse and noisy experimental data, is an active field of research, with methods including Bayesian MCMC and approximate Bayesian computation proving adaptable and robust.

A schematic illustration of a dual reporter study. Each data point corresponds to a measurement of the expression level of two identically regulated genes in a single cell: the scatter reflects measurements of a population of cells. Extrinsic noise is characterised by expression levels of both genes covarying between cells, intrinsic by internal differences.
A canonical model for stochastic gene expression, known as the two-state or telegraph [ 30 ] model. DNA flips between "inactive" and "active" states (involving, for example, chromatin remodelling and transcription factor binding). Active DNA is transcribed to produce mRNA which is translated to produce protein, both of which are degraded. All processes are Poissonian with given rates.