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Modelling Gene Regulatory Networks:
Systems Biology to Complex Systems

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• Note to the reader...
• Overview
• Introduction
• Biological background
  • The basics of gene expression
    • Transcription
    • Translation
  • The control tasks of the genome
  • Further reading
  
  
• A diversity of models
  • Why build models?
  • Complex systems and systems biology
  • Key features of dynamic systems
  • Logical, continuous and stochastic models
  • Different motivations for building models
    • Crafted models of specific systems
    • Phenomenological models of biological mechanisms
    • General models of classes of networks
    • Network models inferred from experimental data
  • Further reading
  
  
• Logical models
  • Boolean networks
    • Assumptions
    • Model description
    • Theoretical results and hypotheses
      • Classes of behaviour
      • Attractors as cell types
    • Extensions and applications
      • Updating rules
      • Network structure
      • Timing
      • Applications
    • Strengths and limitations
  • Generalised logic
    • Assumptions
    • Model Description
    • Theoretical results and Applications
    • Strengths and limitations
  • Continuous logic
    • Assumptions
    • Applications
  • Further reading
  
  
• Continuous models
  • Ordinary Differential Equations
    • Assumptions
    • Model description
    • Applications
      • Model systems
      • Reverse engineering of network structure
      • Forward engineering of novel networks
  • Neural network models
  • Hybrid models
  • Spatial models
    • Intercellular communication
    • Mechanisms of development
  • Further reading
  
  
• Stochastic models
  • Noise from within and without
  • Stochastic modelling approaches
  • Further reading
  
  
• Network models
  • Small world and scale-free networks
  • Modularity, motifs and other structural features
  • Further reading
  
  
• Bibliography
• About this document ...

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Nic Geard 2004-05-06