Literature DB >> 21676967

A composite computational model of liver glucose homeostasis. I. Building the composite model.

J Hetherington1, T Sumner, R M Seymour, L Li, M Varela Rey, S Yamaji, P Saffrey, O Margoninski, I D L Bogle, A Finkelstein, A Warner.   

Abstract

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.

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Year:  2011        PMID: 21676967      PMCID: PMC3284126          DOI: 10.1098/rsif.2011.0141

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  36 in total

1.  Activation of the liver glycogen phosphorylase by Ca(2+)oscillations: a theoretical study.

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Journal:  J Theor Biol       Date:  2000-12-21       Impact factor: 2.691

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Journal:  Trends Biochem Sci       Date:  2002-01       Impact factor: 13.807

3.  Liver kinetics of glucose analogs measured in pigs by PET: importance of dual-input blood sampling.

Authors:  O L Munk; L Bass; K Roelsgaard; D Bender; S B Hansen; S Keiding
Journal:  J Nucl Med       Date:  2001-05       Impact factor: 10.057

4.  Switching from simple to complex oscillations in calcium signaling.

Authors:  U Kummer; L F Olsen; C J Dixon; A K Green; E Bornberg-Bauer; G Baier
Journal:  Biophys J       Date:  2000-09       Impact factor: 4.033

5.  A mathematical model of metabolic insulin signaling pathways.

Authors:  Ahmad R Sedaghat; Arthur Sherman; Michael J Quon
Journal:  Am J Physiol Endocrinol Metab       Date:  2002-11       Impact factor: 4.310

6.  Mathematical modelling of the urea cycle. A numerical investigation into substrate channelling.

Authors:  Anthony D Maher; Philip W Kuchel; Fernando Ortega; Pedro de Atauri; Josep Centelles; Marta Cascante
Journal:  Eur J Biochem       Date:  2003-10

Review 7.  Computer model for mechanisms underlying ultradian oscillations of insulin and glucose.

Authors:  J Sturis; K S Polonsky; E Mosekilde; E Van Cauter
Journal:  Am J Physiol       Date:  1991-05

8.  Modeling a simplified regulatory system of blood glucose at molecular levels.

Authors:  Weijiu Liu; Fusheng Tang
Journal:  J Theor Biol       Date:  2008-02-23       Impact factor: 2.691

9.  Identification of common and distinct residues involved in the interaction of alphai2 and alphas with adenylyl cyclase.

Authors:  G Grishina; C H Berlot
Journal:  J Biol Chem       Date:  1997-08-15       Impact factor: 5.157

10.  Diabetic control after total pancreatectomy.

Authors:  P Jethwa; M Sodergren; A Lala; J Webber; J A C Buckels; S R Bramhall; D F Mirza
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  9 in total

1.  A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

Authors:  T Sumner; E Shephard; I D L Bogle
Journal:  J R Soc Interface       Date:  2012-04-04       Impact factor: 4.118

2.  A composite computational model of liver glucose homeostasis. II. Exploring system behaviour.

Authors:  T Sumner; J Hetherington; R M Seymour; L Li; M Varela Rey; S Yamaji; P Saffrey; O Margoninski; I D L Bogle; A Finkelstein; A Warner
Journal:  J R Soc Interface       Date:  2012-02-08       Impact factor: 4.118

3.  A computer model simulating human glucose absorption and metabolism in health and metabolic disease states.

Authors:  Richard J Naftalin
Journal:  F1000Res       Date:  2016-04-12

4.  A Kinetic-Model-Based Approach to Identify Malfunctioning Components in Signal Transduction Pathways from Artificial Clinical Data.

Authors:  Xianhua Li; Nicholas Ribaudo; Zuyi Jacky Huang
Journal:  Biomed Res Int       Date:  2015-11-29       Impact factor: 3.411

5.  A Computational Model of Hepatic Energy Metabolism: Understanding Zonated Damage and Steatosis in NAFLD.

Authors:  William B Ashworth; Nathan A Davies; I David L Bogle
Journal:  PLoS Comput Biol       Date:  2016-09-15       Impact factor: 4.475

6.  Model-based virtual patient analysis of human liver regeneration predicts critical perioperative factors controlling the dynamic mode of response to resection.

Authors:  Babita K Verma; Pushpavanam Subramaniam; Rajanikanth Vadigepalli
Journal:  BMC Syst Biol       Date:  2019-01-16

7.  A Generic Integrated Physiologically based Whole-body Model of the Glucose-Insulin-Glucagon Regulatory System.

Authors:  S Schaller; S Willmann; J Lippert; L Schaupp; T R Pieber; A Schuppert; T Eissing
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2013-08-14

8.  The impact of mathematical modeling on the understanding of diabetes and related complications.

Authors:  I Ajmera; M Swat; C Laibe; N Le Novère; V Chelliah
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2013-07-10

Review 9.  Computational Modeling in Liver Surgery.

Authors:  Bruno Christ; Uta Dahmen; Karl-Heinz Herrmann; Matthias König; Jürgen R Reichenbach; Tim Ricken; Jana Schleicher; Lars Ole Schwen; Sebastian Vlaic; Navina Waschinsky
Journal:  Front Physiol       Date:  2017-11-14       Impact factor: 4.566

  9 in total

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