Introduction to stochastic models in biology

Susanne Ditlevsen, Adeline Samson

27 Citations (Scopus)

Abstract

This chapter is concerned with continuous time processes, which are often modeled as a system of ordinary differential equations (ODEs). These models assume that the observed dynamics are driven exclusively by internal, deterministic mechanisms. However, real biological systems will always be exposed to influences that are not completely understood or not feasible to model explicitly. Ignoring these phenomena in the modeling may affect the analysis of the studied biological systems. Therefore there is an increasing need to extend the deterministic models to models that embrace more complex variations in the dynamics. A way of modeling these elements is by including stochastic influences or noise. A natural extension of a deterministic differential equations model is a system of stochastic differential equations (SDEs), where relevant parameters are modeled as suitable stochastic processes, or stochastic processes are added to the driving system equations. This approach assumes that the dynamics are partly driven by noise.
Original languageEnglish
Title of host publicationStochastic Biomathematical Models : with Applications to Neuronal Modeling
EditorsMostafa Bachar, Jerry Batzel, Susanne Ditlevsen
Place of PublicationBerlin
PublisherSpringer
Publication date2013
Pages3-34
Chapter1
ISBN (Print)978-3-642-32156-6
ISBN (Electronic)978-3-642-32157-3
DOIs
Publication statusPublished - 2013
SeriesLecture Notes in Mathematics
Number2058
ISSN0075-8434

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