Literature DB >> 11056061

The organization of metabolic reaction networks: a signal-oriented approach to cellular models.

A Kremling1, K Jahreis, J W Lengeler, E D Gilles.   

Abstract

Complex metabolic networks are characterized by a great number of elements and many regulatory loops. The description of these networks with mathematical models requires the definition of functional units that group together several cellular processes. The approach presented here is based on the idea that cellular functional units may be assigned directly to mathematical modeling objects. Because the proposed modeling objects have defined inputs and outputs, they can be connected with other modeling objects until eventually the whole metabolism is covered. This modular approach guarantees a high transparency for biologists as well as for engineers. Three criteria are introduced to demarcate functional units. The criteria consider the physiological pathways, the organization of the corresponding genes, and the observation that cellular systems can be structured into units showing a hierarchy of signal transduction and processing. As an example, the carbon catabolic reactions in Escherichia coli are discussed as members of a functional unit catabolism. Copyright 2000 Academic Press.

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Year:  2000        PMID: 11056061     DOI: 10.1006/mben.2000.0159

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  6 in total

1.  A computational framework for the topological analysis and targeted disruption of signal transduction networks.

Authors:  Madhukar S Dasika; Anthony Burgard; Costas D Maranas
Journal:  Biophys J       Date:  2006-04-14       Impact factor: 4.033

2.  Detailed map of a cis-regulatory input function.

Authors:  Y Setty; A E Mayo; M G Surette; U Alon
Journal:  Proc Natl Acad Sci U S A       Date:  2003-06-12       Impact factor: 11.205

3.  Prediction of functional modules based on comparative genome analysis and Gene Ontology application.

Authors:  Hongwei Wu; Zhengchang Su; Fenglou Mao; Victor Olman; Ying Xu
Journal:  Nucleic Acids Res       Date:  2005-05-18       Impact factor: 16.971

4.  Detecting uber-operons in prokaryotic genomes.

Authors:  Dongsheng Che; Guojun Li; Fenglou Mao; Hongwei Wu; Ying Xu
Journal:  Nucleic Acids Res       Date:  2006-05-08       Impact factor: 16.971

5.  Statistical Physics for Medical Diagnostics: Learning, Inference, and Optimization Algorithms.

Authors:  Abolfazl Ramezanpour; Andrew L Beam; Jonathan H Chen; Alireza Mashaghi
Journal:  Diagnostics (Basel)       Date:  2020-11-19

6.  PROMOT: modular modeling for systems biology.

Authors:  Sebastian Mirschel; Katrin Steinmetz; Michael Rempel; Martin Ginkel; Ernst Dieter Gilles
Journal:  Bioinformatics       Date:  2009-01-15       Impact factor: 6.937

  6 in total

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