Literature DB >> 4038284

Mathematics of organizationally complex systems.

M A Savageau.   

Abstract

Our approach to the development of an appropriate formalism for organizationally complex systems has been to search for a general formalism that would retain the essential nonlinear features (at least in approximate form) and yet would be amenable to mathematical analysis. The power-law formalism, described in detail elsewhere, leads naturally to a system of nonlinear differential equations, which is called an "S-system" because it captures the saturable and synergistic properties intrinsic to biological and other organizationally complex systems. Some of the advantages of this formalism and its implications for complex systems are discussed. Although the power-law formalism was originally developed as an "approximation", there are now several examples of "exact" representation by S-systems. In fact, a wide range of nonlinear equations can be recast in the form of S-systems. Such recasting and the use of algorithms optimized for S-systems greatly improves the efficiency of solution over that obtainable with conventional algorithms.

Mesh:

Year:  1985        PMID: 4038284

Source DB:  PubMed          Journal:  Biomed Biochim Acta        ISSN: 0232-766X


  7 in total

1.  A simplified method for calculating complex metabolic sensitivities by using matrix partitioning.

Authors:  B Crabtree; G Collins; M I Franklin
Journal:  Biochem J       Date:  1989-10-01       Impact factor: 3.857

Review 2.  Mathematical descriptions of biochemical networks: stability, stochasticity, evolution.

Authors:  Simon Rosenfeld
Journal:  Prog Biophys Mol Biol       Date:  2011-03-22       Impact factor: 3.667

3.  A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles.

Authors:  Tomoya Kitayama; Ayako Kinoshita; Masahiro Sugimoto; Yoichi Nakayama; Masaru Tomita
Journal:  Theor Biol Med Model       Date:  2006-07-17       Impact factor: 2.432

4.  Towards a theory of biological robustness.

Authors:  Hiroaki Kitano
Journal:  Mol Syst Biol       Date:  2007-09-18       Impact factor: 11.429

5.  Systematic applications of metabolomics in metabolic engineering.

Authors:  Robert A Dromms; Mark P Styczynski
Journal:  Metabolites       Date:  2012-12-14

6.  Redirector: designing cell factories by reconstructing the metabolic objective.

Authors:  Graham Rockwell; Nicholas J Guido; George M Church
Journal:  PLoS Comput Biol       Date:  2013-01-17       Impact factor: 4.475

7.  Global consensus theorem and self-organized criticality: unifying principles for understanding self-organization, swarm intelligence and mechanisms of carcinogenesis.

Authors:  Simon Rosenfeld
Journal:  Gene Regul Syst Bio       Date:  2013-02-20
  7 in total

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