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Scaling of intrinsic noise in an autocratic reaction network

Das, Soutrick; Barik, Debashis; (2021) Scaling of intrinsic noise in an autocratic reaction network. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics , 103 (4-1) , Article 042403. 10.1103/PhysRevE.103.042403. Green open access

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Abstract

Biochemical reactions in living cells often produce stochastic trajectories due to the fluctuations of the finite number of the macromolecular species present inside the cell. A significant number of computational and theoretical studies have previously investigated stochasticity in small regulatory networks to understand its origin and regulation. At the systems level regulatory networks have been determined to be hierarchical resembling social networks. In order to determine the stochasticity in networks with hierarchical architecture, here we computationally investigated intrinsic noise in an autocratic reaction network in which only the upstream regulators regulate the downstream regulators. We studied the effects of the qualitative and quantitative nature of regulatory interactions on the stochasticity in the network. We established an unconventional scaling of noise with average abundance in which the noise passes through a minimum indicating that the network can be noisy both in the low and high abundance regimes. We determined that the bursty kinetics of the trajectories are responsible for such scaling. The scaling of noise remains intact for a mixed network that includes democratic subnetworks within the autocratic network.

Type: Article
Title: Scaling of intrinsic noise in an autocratic reaction network
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1103/PhysRevE.103.042403
Publisher version: https://doi.org/10.1103/PhysRevE.103.042403
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Science & Technology, Physical Sciences, Physics, Fluids & Plasmas, Physics, Mathematical, Physics, STOCHASTIC GENE-EXPRESSION, TO-CELL VARIABILITY, REGULATORY NETWORKS, HIERARCHICAL STRUCTURE, GENOMIC ANALYSIS, FEEDBACK LOOPS, PROPAGATION, FLUCTUATIONS, STABILITY, REVEALS
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Cell and Developmental Biology
URI: https://discovery.ucl.ac.uk/id/eprint/10171237
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