title: Control, responses and modularity of cellular regulatory networks: a control analysis perspective.
abstract: Cells adapt to changes in environmental conditions through the concerted action of signalling, gene expression and metabolic subsystems. The authors will discuss a theoretical framework addressing such integrated systems. This 'hierarchical analysis' was first developed as an extension to a metabolic control analysis. It builds on the phenomenon that often the communication between signalling, gene expression and metabolic subsystems is almost exclusively via regulatory interactions and not via mass flow interactions. This allows for the treatment of the said subsystems as 'levels' in a hierarchical view of the organisation of the molecular reaction network of cells. Such a hierarchical approach has as a major advantage that levels can be analysed conceptually in isolation of each other (from a local intra-level perspective) and at a later stage integrated via their interactions (from a global inter-level perspective). Hereby, it allows for a modular approach with variable scope. A number of different approaches have been developed for the analysis of hierarchical systems, for example hierarchical control analysis and modular response analysis. The authors, here, review these methods and illustrate the strength of these types of analyses using a core model of a system with gene expression, metabolic and signal transduction levels.
authors.affiliation: Vrije Universiteit, Molecular Cell Physiology, Faculty of Earth and Life sciences, Amsterdam, The Netherlands. frank.bruggeman@sysbio.nl
authors.forename: F J
authors.initials: FJ
authors.lastname: Bruggeman
authors.forename: J L
authors.initials: JL
authors.lastname: Snoep
authors.forename: H V
authors.initials: HV
authors.lastname: Westerhoff
mesh_terms: D000818:Animals; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D005246:Feedback / Q000502:physiology; D005786:Gene Expression Regulation / Q000502:physiology*; D006801:Humans; D055442:Metabolome / Q000502:physiology*; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*; D049490:Systems Biology / Q000379:methods