References of "Snoep, Jacky L"
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See detailDesign principles of nuclear receptor signalling: How complex networking improves signal transduction
Kolodkin, Alexey UL; Bruggeman, Frank J.; Plant, Nick et al

in Toxicology (2011), 290(2-3), 131-132

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See detailDesign principles of nuclear receptor signaling: how complex networking improves signal transduction.
Kolodkin, Alexey UL; Bruggeman, Frank J.; Plant, Nick et al

in Molecular Systems Biology (2010), 6

The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of 'design' aspects of the topology of these networks that ... [more ▼]

The topology of nuclear receptor (NR) signaling is captured in a systems biological graphical notation. This enables us to identify a number of 'design' aspects of the topology of these networks that might appear unnecessarily complex or even functionally paradoxical. In realistic kinetic models of increasing complexity, calculations show how these features correspond to potentially important design principles, e.g.: (i) cytosolic 'nuclear' receptor may shuttle signal molecules to the nucleus, (ii) the active export of NRs may ensure that there is sufficient receptor protein to capture ligand at the cytoplasmic membrane, (iii) a three conveyor belts design dissipating GTP-free energy, greatly aids response, (iv) the active export of importins may prevent sequestration of NRs by importins in the nucleus and (v) the unspecific nature of the nuclear pore may ensure signal-flux robustness. In addition, the models developed are suitable for implementation in specific cases of NR-mediated signaling, to predict individual receptor functions and differential sensitivity toward physiological and pharmacological ligands. [less ▲]

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See detailSystems biology towards life in silico: mathematics of the control of living cells.
Westerhoff, Hans V.; Kolodkin, Alexey UL; Conradie, Riaan et al

in Journal of Mathematical Biology (2009), 58(1-2), 7-34

Systems Biology is the science that aims to understand how biological function absent from macromolecules in isolation, arises when they are components of their system. Dedicated to the memory of Reinhart ... [more ▼]

Systems Biology is the science that aims to understand how biological function absent from macromolecules in isolation, arises when they are components of their system. Dedicated to the memory of Reinhart Heinrich, this paper discusses the origin and evolution of the new part of systems biology that relates to metabolic and signal-transduction pathways and extends mathematical biology so as to address postgenomic experimental reality. Various approaches to modeling the dynamics generated by metabolic and signal-transduction pathways are compared. The silicon cell approach aims to describe the intracellular network of interest precisely, by numerically integrating the precise rate equations that characterize the ways macromolecules' interact with each other. The non-equilibrium thermodynamic or 'lin-log' approach approximates the enzyme rate equations in terms of linear functions of the logarithms of the concentrations. Biochemical Systems Analysis approximates in terms of power laws. Importantly all these approaches link system behavior to molecular interaction properties. The latter two do this less precisely but enable analytical solutions. By limiting the questions asked, to optimal flux patterns, or to control of fluxes and concentrations around the (patho)physiological state, Flux Balance Analysis and Metabolic/Hierarchical Control Analysis again enable analytical solutions. Both the silicon cell approach and Metabolic/Hierarchical Control Analysis are able to highlight where and how system function derives from molecular interactions. The latter approach has also discovered a set of fundamental principles underlying the control of biological systems. The new law that relates concentration control to control by time is illustrated for an important signal transduction pathway, i.e. nuclear hormone receptor signaling such as relevant to bone formation. It is envisaged that there is much more Mathematical Biology to be discovered in the area between molecules and Life. [less ▲]

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