Literature DB >> 9781383

Compartmental models: theory and practice using the SAAM II software system.

C Cobelli1, D M Foster.   

Abstract

Understanding in vivo the functioning of metabolic systems at the whole-body or regional level requires one to make some assumptions on how the system works and to describe them mathematically, that is, to postulate a model of the system. Models of systems can have different characteristics depending on the properties of the system and the database available for their study; they can be deterministic or stochastic, dynamic or static, with lumped or distributed parameters. Metabolic systems are dynamic systems and we focus here on the most widely used class of dynamic (differential equation) models: compartmental models. This is a class of models for which the governing law is conservation of mass. It is a very attractive class to users because it formalizes physical intuition in a simple and reasonable way. Compartmental models are lumped parameter models, in that the events in the system are described by a finite number of changing variables, and are thus described by ordinary differential equations. While stochastic compartment models can also be defined, we discuss here the deterministic versions--those that can work with exact relationships between model variables. These are the models most widely used in discussions of endocrinology and metabolism. In this chapter, we will discuss the theory of compartmental models, and then discuss how the SAAM II software system, a system designed specifically to aid in the development and testing of multicompartmental models, can be used.

Mesh:

Substances:

Year:  1998        PMID: 9781383     DOI: 10.1007/978-1-4899-1959-5_5

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  9 in total

1.  GLUT4 is retained by an intracellular cycle of vesicle formation and fusion with endosomes.

Authors:  Ola Karylowski; Anja Zeigerer; Alona Cohen; Timothy E McGraw
Journal:  Mol Biol Cell       Date:  2003-10-31       Impact factor: 4.138

2.  Global nature of dynamic protein-chromatin interactions in vivo: three-dimensional genome scanning and dynamic interaction networks of chromatin proteins.

Authors:  Robert D Phair; Paola Scaffidi; Cem Elbi; Jaromíra Vecerová; Anup Dey; Keiko Ozato; David T Brown; Gordon Hager; Michael Bustin; Tom Misteli
Journal:  Mol Cell Biol       Date:  2004-07       Impact factor: 4.272

3.  Insulin activation of plasma nonesterified fatty acid uptake in metabolic syndrome.

Authors:  Maria A Ramos-Roman; Smadar A Lapidot; Robert D Phair; Elizabeth J Parks
Journal:  Arterioscler Thromb Vasc Biol       Date:  2012-06-21       Impact factor: 8.311

Review 4.  Studying apolipoprotein turnover with stable isotope tracers: correct analysis is by modeling enrichments.

Authors:  Rajasekhar Ramakrishnan
Journal:  J Lipid Res       Date:  2006-09-01       Impact factor: 5.922

5.  Pharmacokinetics and safety of intravenous cidofovir for life-threatening viral infections in pediatric hematopoietic stem cell transplant recipients.

Authors:  Amy E Caruso Brown; Mindy N Cohen; Suhong Tong; Rebecca S Braverman; James F Rooney; Roger Giller; Myron J Levin
Journal:  Antimicrob Agents Chemother       Date:  2015-03-02       Impact factor: 5.191

6.  PET-based compartmental modeling of (124)I-A33 antibody: quantitative characterization of patient-specific tumor targeting in colorectal cancer.

Authors:  Pat Zanzonico; Jorge A Carrasquillo; Neeta Pandit-Taskar; Joseph A O'Donoghue; John L Humm; Peter Smith-Jones; Shutian Ruan; Chaitanya Divgi; Andrew M Scott; Nancy E Kemeny; Yuman Fong; Douglas Wong; David Scheinberg; Gerd Ritter; Achem Jungbluth; Lloyd J Old; Steven M Larson
Journal:  Eur J Nucl Med Mol Imaging       Date:  2015-07-21       Impact factor: 9.236

7.  Comparative multiple dose plasma kinetics of lycopene administered in tomato juice, tomato soup or lycopene tablets.

Authors:  William Cohn; Petra Thürmann; Ute Tenter; Claude Aebischer; Josef Schierle; Wolfgang Schalch
Journal:  Eur J Nutr       Date:  2004-01-26       Impact factor: 5.614

8.  Using mass measurements in tracer studies--a systematic approach to efficient modeling.

Authors:  Rajasekhar Ramakrishnan; Janak D Ramakrishnan
Journal:  Metabolism       Date:  2008-08       Impact factor: 8.694

9.  A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems.

Authors:  D L Cook; J F Farley; S J Tapscott
Journal:  Genome Biol       Date:  2001-03-22       Impact factor: 13.583

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.