Model simplification of signal transduction pathway networks via a hybrid inference strategy

Jia, Jianfang and Yue, Hong (2008) Model simplification of signal transduction pathway networks via a hybrid inference strategy. IFAC Proceedings Volumes, 41 (2). pp. 10307-10312. ISSN 1474-6670 (https://doi.org/10.3182/20080706-5-KR-1001.01744)

[thumbnail of strathprints007336]
Preview
 Text. Filename: strathprints007336.pdf
Accepted Author Manuscript
License: Strathprints license 1.0
Download (222kB)| Preview

Abstract

A full-scale mathematical model of cellular networks normally involves a large number of variables and parameters. How to effectively develop manageable and reliable models is crucial for effective computation, analysis and design of such systems. The aim of model simplification is to eliminate parts of a model that are unimportant for the properties of interest. In this work, a model reduction strategy via hybrid inference is proposed for signal pathway networks. It integrates multiple techniques including conservation analysis, local sensitivity analysis, principal component analysis and flux analysis to identify the reactions and variables that can be considered to be eliminated from the full-scale model. Using an I·B-NF-·B signalling pathway model as an example, simulation analysis demonstrates that the simplified model quantitatively predicts the dynamic behaviours of the network.

ORCID iDs

Jia, Jianfang and Yue, Hong ORCID logoORCID: https://orcid.org/0000-0003-2072-6223;
CORE (COnnecting REpositories)