Literature DB >> 11316483

Quantitative aspects of metabolic organization: a discussion of concepts.

S A Kooijman1.   

Abstract

Metabolic organization of individual organisms follows simple quantitative rules that can be understood from basic physical chemical principles. Dynamic energy budget (DEB) theory identifies these rules, which quantify how individuals acquire and use energy and nutrients. The theory provides constraints on the metabolic organization of subcellular processes. Together with rules for interaction between individuals, it also provides a basis to understand population and ecosystem dynamics. The theory, therefore, links various levels of biological organization. It applies to all species of organisms and offers explanations for body-size scaling relationships of natural history parameters that are otherwise difficult to understand. A considerable number of popular empirical models turn out to be special cases of the DEB model, or very close numerical approximations. Strong and weak homeostasis and the partitionability of reserve kinetics are cornerstones of the theory and essential for understanding the evolution of metabolic organization.

Mesh:

Year:  2001        PMID: 11316483      PMCID: PMC1088431          DOI: 10.1098/rstb.2000.0771

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  24 in total

Review 1.  Dynamic energy budget theory restores coherence in biology.

Authors:  Tânia Sousa; Tiago Domingos; J-C Poggiale; S A L M Kooijman
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-11-12       Impact factor: 6.237

2.  Making sense of ecotoxicological test results: towards application of process-based models.

Authors:  Tjalling Jager; Evelyn H W Heugens; Sebastiaan A L M Kooijman
Journal:  Ecotoxicology       Date:  2006-04-20       Impact factor: 2.823

Review 3.  From empirical patterns to theory: a formal metabolic theory of life.

Authors:  Tânia Sousa; Tiago Domingos; S A L M Kooijman
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2008-07-27       Impact factor: 6.237

Review 4.  Interactions between oil-spill pollutants and natural stressors can compound ecotoxicological effects.

Authors:  Andrew Whitehead
Journal:  Integr Comp Biol       Date:  2013-07-10       Impact factor: 3.326

5.  Temperature is the key factor explaining interannual variability of Daphnia development in spring: a modelling study.

Authors:  Kristine Schalau; Karsten Rinke; Dietmar Straile; Frank Peeters
Journal:  Oecologia       Date:  2008-06-24       Impact factor: 3.225

6.  Benchmarks in organism performance and their use in comparative analyses.

Authors:  Peter J Edmunds; Hollie M Putnam; Roger M Nisbet; Erik B Muller
Journal:  Oecologia       Date:  2011-05-08       Impact factor: 3.225

7.  A biology-based approach for mixture toxicity of multiple endpoints over the life cycle.

Authors:  Tjalling Jager; Tine Vandenbrouck; Jan Baas; Wim M De Coen; Sebastiaan A L M Kooijman
Journal:  Ecotoxicology       Date:  2009-09-22       Impact factor: 2.823

8.  Linking toxicant physiological mode of action with induced gene expression changes in Caenorhabditis elegans.

Authors:  Suresh Swain; Jodie F Wren; Stephen R Stürzenbaum; Peter Kille; A John Morgan; Tjalling Jager; Martijs J Jonker; Peter K Hankard; Claus Svendsen; Jenifer Owen; B Ann Hedley; Mark Blaxter; David J Spurgeon
Journal:  BMC Syst Biol       Date:  2010-03-23

9.  Sublethal toxicant effects with dynamic energy budget theory: application to mussel outplants.

Authors:  Erik B Muller; Craig W Osenberg; Russell J Schmitt; Sally J Holbrook; Roger M Nisbet
Journal:  Ecotoxicology       Date:  2009-07-24       Impact factor: 2.823

Review 10.  Nutritional systems biology modeling: from molecular mechanisms to physiology.

Authors:  Albert A de Graaf; Andreas P Freidig; Baukje De Roos; Neema Jamshidi; Matthias Heinemann; Johan A C Rullmann; Kevin D Hall; Martin Adiels; Ben van Ommen
Journal:  PLoS Comput Biol       Date:  2009-11-26       Impact factor: 4.475

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