Quantifying heterogeneity of stochastic gene expression

DOI10.1016/j.jtbi.2019.01.003zbMath1406.92187OpenAlexW2950766381MaRDI QIDQ1721791

Nobuaki Obata, Keita Iida, Yoshitaka Kimura

Publication date: 13 February 2019

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2019.01.003

zbMATH Keywords

stochastic processmaster equationMetropolis algorithm\textit{lac} operon

Mathematics Subject Classification ID

PDEs in connection with biology, chemistry and other natural sciences (35Q92) Biochemistry, molecular biology (92C40) Stochastic partial differential equations (aspects of stochastic analysis) (60H15)

Cites Work

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• Exact and approximate distributions of protein and mRNA levels in the low-copy regime of gene expression
• Relative convexity and its applications
• A geometric analysis of fast-slow models for stochastic gene expression
• Generalized Fokker-Planck equation: derivation and exact solutions
• Markovian modelling of gene product synthesis
• Deterministic and stochastic descriptions of gene expression dynamics
• Using Gene Expression Noise to Understand Gene Regulation
• A General Mechanism for Network-Dosage Compensation in Gene Circuits
• Equation of State Calculations by Fast Computing Machines

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