Hetherington, J; Sumner, T; Seymour, RM; Li, L; Rey, MV; Yamaji, S; ... Warner, A; + view all Hetherington, J; Sumner, T; Seymour, RM; Li, L; Rey, MV; Yamaji, S; Saffrey, P; Margoninski, O; Bogle, ID; Finkelstein, A; Warner, A; - view fewer (2012) A composite computational model of liver glucose homeostasis. I. Building the composite model. J R Soc Interface , 9 (69) 689 - 700. 10.1098/rsif.2011.0141.
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A computational model of the glucagon/insulin-driven liver glucohomeostasis function, focusing on the buffering of glucose into glycogen, has been developed. The model exemplifies an 'engineering' approach to modelling in systems biology, and was produced by linking together seven component models of separate aspects of the physiology. The component models use a variety of modelling paradigms and degrees of simplification. Model parameters were determined by an iterative hybrid of fitting to high-scale physiological data, and determination from small-scale in vitro experiments or molecular biological techniques. The component models were not originally designed for inclusion within such a composite model, but were integrated, with modification, using our published modelling software and computational frameworks. This approach facilitates the development of large and complex composite models, although, inevitably, some compromises must be made when composing the individual models. Composite models of this form have not previously been demonstrated.
|Title:||A composite computational model of liver glucose homeostasis. I. Building the composite model.|
|Keywords:||Algorithms, Animals, Calcium Signaling, Cyclic AMP, Feedback, Physiological, Glucose, Glycogenolysis, Homeostasis, Humans, Insulin, Liver, Liver Circulation, Liver Glycogen, Models, Biological, Pancreas, Rats, Receptors, Glucagon, Signal Transduction, Systems Biology|
|UCL classification:||UCL > Professional Services > Information Services Division|
UCL > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > School of BEAMS > Faculty of Engineering Science > Engineering Science Faculty Office
UCL > VP Research
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