
Contents
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5.1 Overview and Applications 5.1 Overview and Applications
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5.2 Stoichiometric Networks 5.2 Stoichiometric Networks
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5.3 Conservation Relations 5.3 Conservation Relations
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5.4 Balanced Networks: The Quasi Steady State Assumption 5.4 Balanced Networks: The Quasi Steady State Assumption
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5.4.1 Metabolite Balancing Equation and Null-Space of N 5.4.1 Metabolite Balancing Equation and Null-Space of N
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5.4.2 Analysis of the Kernel Matrix 5.4.2 Analysis of the Kernel Matrix
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5.4.3 Metabolic Flux Analysis 5.4.3 Metabolic Flux Analysis
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5.5 Constraint-Based Modeling 5.5 Constraint-Based Modeling
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5.5.1 Principles of Constraint-Based Modeling 5.5.1 Principles of Constraint-Based Modeling
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5.5.2 Flux Balance Analysis 5.5.2 Flux Balance Analysis
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5.5.3 Minimization of Metabolic Adjustment (MoMA) 5.5.3 Minimization of Metabolic Adjustment (MoMA)
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5.6 Pathway Analysis 5.6 Pathway Analysis
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5.6.1 Principles of Pathway Analysis 5.6.1 Principles of Pathway Analysis
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5.6.2 Elementary Flux Modes and Extreme Pathways 5.6.2 Elementary Flux Modes and Extreme Pathways
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5.6.3 Calculation of Pathway Sets 5.6.3 Calculation of Pathway Sets
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5.6.4 Applications of Pathway Analysis 5.6.4 Applications of Pathway Analysis
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5.7 Advanced Topics and Future Directions 5.7 Advanced Topics and Future Directions
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5.7.1 Genome-Scale Network Analysis 5.7.1 Genome-Scale Network Analysis
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5.7.2 Modularity and Hierarchies 5.7.2 Modularity and Hierarchies
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5.7.3 Network Structure and Cellular Regulation 5.7.3 Network Structure and Cellular Regulation
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5.8 Conclusions 5.8 Conclusions
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5. Stoichiometric and Constraint-based Modeling
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Published:March 2006
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Abstract
This chapter explains the main concepts of stoichiometric network analysis (SNA). Stoichiometric modeling has become an important approach for understanding the function of metabolic networks. Hence, the focus is on metabolism, and extensions to cellular regulation are discussed. One aim of the chapter is to review critically virtues and limitations of the approaches with respect to their potential applications for realistic biological networks. It compares four major approaches to SNA by addressing the following issues: network consistency, functional pathways and cycles, network capabilities, importance of reactions, correlated reactions, network design, and network flexibility and robustness.
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