Developing Itô stochastic differential equation models for neuronal signal transduction path\-ways

DOI10.1016/j.compbiolchem.2006.04.002zbMath1098.92035OpenAlexW2055613433WikidataQ51936340 ScholiaQ51936340MaRDI QIDQ849530

Tiina Manninen, Marja-Leena Linne, Keijo Ruohonen

Publication date: 31 October 2006

Published in: Computational Biology and Chemistry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.compbiolchem.2006.04.002

zbMATH Keywords

Itô stochastic differential equationchemical Langevin equationGillespie stochastic simulation algorithmneuronal signal transduction

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Neural biology (92C20) Biomedical imaging and signal processing (92C55) Kinetics in biochemical problems (pharmacokinetics, enzyme kinetics, etc.) (92C45) Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.) (60J70)

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Uses Software

• STOCHSIM

Cites Work

• The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behavior
• Stochastic approaches for modelling in vivo reactions
• An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations
• Numerical methods for strong solutions of stochastic differential equations: an overview
• The multivariate Langevin and Fokker–Planck equations
• Balanced Implicit Methods for Stiff Stochastic Systems
• Computational Methods in Systems Biology
• Stochastic differential equations. An introduction with applications.