Parameter inference for biochemical systems that undergo a Hopf bifurcation.

Abstract:

:The increasingly widespread use of parametric mathematical models to describe biological systems means that the ability to infer model parameters is of great importance. In this study, we consider parameter inferability in nonlinear ordinary differential equation models that undergo a bifurcation, focusing on a simple but generic biochemical reaction model. We systematically investigate the shape of the likelihood function for the model's parameters, analyzing the changes that occur as the model undergoes a Hopf bifurcation. We demonstrate that there exists an intrinsic link between inference and the parameters' impact on the modeled system's dynamical stability, which we hope will motivate further research in this area.

journal_name

Biophys J

journal_title

Biophysical journal

authors

Kirk PD,Toni T,Stumpf MP

doi

10.1529/biophysj.107.126086

subject

Has Abstract

pub_date

2008-07-01 00:00:00

pages

540-9

issue

2

eissn

0006-3495

issn

1542-0086

pii

S0006-3495(08)70231-5

journal_volume

95

pub_type

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