Approximation and inference methods for stochastic biochemical kinetics—a tutorial review

D Schnoerr, G Sanguinetti… - Journal of Physics A …, 2017 - iopscience.iop.org
Stochastic fluctuations of molecule numbers are ubiquitous in biological systems. Important
examples include gene expression and enzymatic processes in living cells. Such systems …

Misuse of the Michaelis–Menten rate law for protein interaction networks and its remedy

JK Kim, JJ Tyson - PLoS Computational Biology, 2020 - journals.plos.org
For over a century, the Michaelis–Menten (MM) rate law has been used to describe the rates
of enzyme-catalyzed reactions and gene expression. Despite the ubiquity of the MM rate …

Linear mapping approximation of gene regulatory networks with stochastic dynamics

Z Cao, R Grima - Nature communications, 2018 - nature.com
The presence of protein–DNA binding reactions often leads to analytically intractable
models of stochastic gene expression. Here we present the linear-mapping approximation …

Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parameters

B Choi, GA Rempala, JK Kim - Scientific reports, 2017 - nature.com
Examining enzyme kinetics is critical for understanding cellular systems and for using
enzymes in industry. The Michaelis-Menten equation has been widely used for over a …

Markovian approaches to modeling intracellular reaction processes with molecular memory

J Zhang, T Zhou - Proceedings of the National Academy of …, 2019 - National Acad Sciences
Many cellular processes are governed by stochastic reaction events. These events do not
necessarily occur in single steps of individual molecules, and, conversely, each birth or …

Markovian dynamics on complex reaction networks

J Goutsias, G Jenkinson - Physics reports, 2013 - Elsevier
Complex networks, comprised of individual elements that interact with each other through
reaction channels, are ubiquitous across many scientific and engineering disciplines …

Nonmodular oscillator and switch based on RNA decay drive regeneration of multimodal gene expression

B Nordick, PY Yu, G Liao, T Hong - Nucleic Acids Research, 2022 - academic.oup.com
Periodic gene expression dynamics are key to cell and organism physiology. Studies of
oscillatory expression have focused on networks with intuitive regulatory negative feedback …

Comprehensive review of models and methods for inferences in bio-chemical reaction networks

P Loskot, K Atitey, L Mihaylova - Frontiers in genetics, 2019 - frontiersin.org
The key processes in biological and chemical systems are described by networks of
chemical reactions. From molecular biology to biotechnology applications, computational …

Stochastic simulation of biomolecular networks in dynamic environments

M Voliotis, P Thomas, R Grima… - PLoS computational …, 2016 - journals.plos.org
Simulation of biomolecular networks is now indispensable for studying biological systems,
from small reaction networks to large ensembles of cells. Here we present a novel approach …

Small protein number effects in stochastic models of autoregulated bursty gene expression

C Jia, R Grima - The Journal of chemical physics, 2020 - pubs.aip.org
A stochastic model of autoregulated bursty gene expression by Kumar et al.[Phys. Rev. Lett.
113, 268105 (2014)] has been exactly solved in steady-state conditions under the implicit …