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Philipp Thomas

Researcher at Imperial College London

Publications -  58
Citations -  1999

Philipp Thomas is an academic researcher from Imperial College London. The author has contributed to research in topics: Master equation & Population. The author has an hindex of 24, co-authored 55 publications receiving 1618 citations. Previous affiliations of Philipp Thomas include Humboldt State University & University of Edinburgh.

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Phenotypic switching in gene regulatory networks

TL;DR: It is shown that intrinsic noise can induce multimodality in a wide class of regulatory networks whose corresponding deterministic description lacks multistability, thus offering a plausible alternative mechanism for phenotypic switching without the need for ultrasensitivity or highly cooperative interactions.
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The slow-scale linear noise approximation: an accurate, reduced stochastic description of biochemical networks under timescale separation conditions

TL;DR: A new general method is derived and shown to correctly describe the statistics of intrinsic noise about the macroscopic concentrations under timescale separation conditions, which is expected to be of widespread utility in studying the dynamics of large noisy reaction networks.
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How accurate are the non-linear chemical Fokker-Planck and chemical Langevin equations?

TL;DR: The system-size expansion is used to show that chemical Fokker-Planck estimates of the mean concentrations and of the variance of the concentration fluctuations about the mean are accurate to order Ω(-3∕2) for reaction systems which do not obey detailed balance and at least accurate for systems obeying detailed balance.
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How accurate are the nonlinear chemical Fokker-Planck and chemical Langevin equations?

TL;DR: In this paper, it was shown that the chemical Fokker-planck equation is more accurate than the linear-noise approximation of the chemical Langevin equation, which leads to mean concentration estimates accurate to order Ω(-1∕2) and variance estimates accurate for reaction systems which do not obey detailed balance, where Ω is the characteristic size of the system.
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Inference for Stochastic Chemical Kinetics Using Moment Equations and System Size Expansion.

TL;DR: In this paper, moment-closure approximation (MA) and system size expansion (SSE) are used to approximate the statistical moments of stochastic processes and tend to be more precise than macroscopic descriptions.