Towards a genome-scale kinetic model of cellular metabolism

Smallbone, Kieran and Simeonidis, Evangelos and Swainston, Neil and Mendes, Pedro (2009) Towards a genome-scale kinetic model of cellular metabolism. BMC Systems Biology. (Submitted)

Warning
There is a more recent version of this item available.
[thumbnail of vangelis.pdf] PDF
vangelis.pdf
Restricted to Repository staff only

Download (470kB)

Abstract

Background: Advances in bioinformatic techniques and analyses have led to the availability of genome-scale metabolic reconstructions. The size and complexity of such networks often means that their potential behaviour can only be analysed with constraint-based methods. Whilst requiring minimal experimental data, such methods are unable to give insight into cellular substrate concentrations. Instead, the long-term goal of systems biology is to use kinetic modelling to characterize fully the mechanics of each enzymatic reaction, and to combine such knowledge to predict system behaviour. Results: We describe a method for building a parameterized genome-scale kinetic model of a metabolic network. Simplified linlog kinetics are used and the parameters are extracted from a kinetic model repository. We demonstrate our methodology by applying it to yeast metabolism. The resultant model has 956 metabolic reactions involving 820 metabolites, and, whilst approximative, has considerably broader remit than any existing models of its type. Control analysis is used to identify key steps within the system. Conclusions: Our modelling framework may be considered a stepping-stone toward the long-term goal of a fully-parameterized model of yeast metabolism. The model is available in SBML format from the BioModels database and at http://www.mcisb.org/resources/genomescale/.

Item Type: Article
Subjects: MSC 2010, the AMS's Mathematics Subject Classification > 92 Biology and other natural sciences
Depositing User: Dr Kieran Smallbone
Date Deposited: 14 Dec 2009
Last Modified: 20 Oct 2017 14:12
URI: https://eprints.maths.manchester.ac.uk/id/eprint/1371

Available Versions of this Item

Actions (login required)

View Item View Item