Towards building the silicon cell: a modular approach.
Systems Biology aims to understand quantitatively how properties of biological systems can be understood as functions of the characteristics of, and interactions between their macromolecular components. Whereas, traditional biochemistry focused on isolation and characterization of cellular components, the challenge for Systems Biology lies in integration of this knowledge and the knowledge about molecular interactions. Computer models play an important role in this integration. We here discuss an approach with which we aim to link kinetic models on small parts of metabolism together, so as to form detailed kinetic models of larger chunks of metabolism, and ultimately of the entire living cell. Specifically, we will discuss techniques that can be used to model a sub-network in isolation of a larger network of which it is a part, while still maintaining the dynamics of the larger complete network. We will start by outlining the JWS online system, the silicon cell project, and the type of models we propose. JWS online is a model repository, which can be used for the storage, simulation and analysis of kinetic models. We advocate to integrate a top-down approach, where measurements on the complete system are used to derive fluxes in a detailed structural model, with a bottom-up approach, consisting of the integration of molecular mechanism-based detailed kinetic models into the structural model.
Snoep
Jacky L
JL
Department of Biochemistry, University of Stellenbosch, Triple-J Group for Molecular Cell Physiology, Private Bag X1, Matieland 7602, South Africa. jls@sun.ac.za
Bruggeman
Frank
F
Olivier
Brett G
BG
Westerhoff
Hans V
HV
D000818:Animals; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D003628:Database Management Systems; D016208:Databases, Factual; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008954:Models, Biological; D009862:Online Systems; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*; D049490:Systems Biology / Q000379:methods; D018511:Systems Integration
D020543:Proteome