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Listening to the noise: random fluctuations reveal gene network parameters
Authors:Brian Munsky  Brooke Trinh  Mustafa Khammash
Institution:1. Computer, Computational, and Statistical Sciences Division (CCS), and the Theoretical (T) Division at Los Alamos National Laboratory, Los Alamos, NM, USA;2. Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, CA, USA;3. Department of Mechanical Engineering and Center for Control, Dynamical Systems and Computations, University of California, Santa Barbara, CA, USA
Abstract:The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations show cell‐to‐cell variability that can manifest significant phenotypic differences. Noise‐induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever‐present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We show that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into the workings of these networks.
Keywords:gene regulatory networks  stochastic biological processes  system identification
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