Tutorials

• #1: Working with Boolean Functions
  • What you will learn
  • 0. Setup
  • 1. Create a Boolean function
    • 1.1 Create Boolean functions from a truth table
    • 1.2 Create Boolean functions from text
    • 1.3 Combining BooleanFunction objects
  • 2. Attributes of BooleanFunction
  • 3. Basic properties of Boolean functions
  • 4. Logical and polynomial representations
  • 5. Summary of Key Concepts
    • Boolean functions
    • Representations of Boolean functions
    • Variable names and ordering
    • Basic properties of Boolean functions
    • Conversions and interoperability
• Frequently Asked Questions (FAQ)
• BoolForge Tutorial 2: Advanced Concepts for Boolean Functions
  • What you will learn
  • 0. Setup
  • 1. Symmetries in Boolean Functions
    • 1.1 What is a symmetry?
    • 1.2 Examples
  • 2. Degenerate functions
  • 3. Activities and Sensitivities
    • 3.1 Activity
    • 3.2 Average sensitivity
    • 3.3 Exact vs Monte Carlo computation
    • 3.4 Computing activities and sensitivities
    • Example: random 25-input function
  • 4. Summary
• BoolForge Tutorial 3: Canalization
  • What you will learn
  • 0. Setup
  • 1. Canalizing variables and layers
    • 1.1 Examples
    • 1.2 Canalizing depth and nested canalization
    • 1.3 Canalizing layer structure
  • 2. Collective canalization
    • 2.1 Canalizing strength
    • 2.2. Distribution of canalizing strength
  • 3. Canalization as a measure of input redundancy
  • 4. Summary and next steps
• BoolForge Tutorial 4: Random Boolean Function Generation
  • What you will learn
  • 0. Setup
  • 1. Generating random Boolean functions
  • 2. Linear functions
  • 3. Functions with prescribed canalizing properties
  • 4. Allowing degenerate functions
  • 5. Functions with prescribed Hamming weight
  • 6. Biased and absolutely biased functions
  • 7. Summary, interpretation, and outlook
  • 8. Common pitfalls
• BoolForge Tutorial 5: Example Use Cases of the Random Function Generator
  • What you will learn
  • 0. Setup
  • 1. Prevalence of canalization
    • Restricting to canalizing functions
  • 2. Collective canalization vs degree
    • Stratification by canalizing depth
    • Correlation between canalizing strength and input redundancy
  • 3. Correlation between canalization and bias
    • Degeneracy vs bias
  • 4. Analyzing functions with specific canalizing layer structure
  • 5. Summary and outlook
• BoolForge Tutorial 6: Working with Boolean Networks
  • What you will learn
  • 0. Setup
  • 1. Boolean network theory
  • 2. Wiring diagrams
    • Example with constants and unequal degrees
  • 3. Creating Boolean networks
    • Creating networks from strings
    • Interoperability with CANA
  • 4. Boolean networks with constants
    • Effect of constant value = 1
  • 5. Boolean network properties
  • Outlook
• BoolForge Tutorial 7: Dynamics of Boolean Networks
  • 0. Setup
  • 1. State space of a Boolean network
  • 2. Dynamics of synchronous Boolean networks
    • 2.1 Exact computation
    • Exhaustive attractor computation
    • 2.2 Monte Carlo simulation
  • 3. Dynamics of asynchronous Boolean networks
    • 3.1 Steady states under general asynchronous update
    • Monte Carlo approximation
    • Sampling from a fixed initial condition
  • Summary and outlook
• BoolForge Tutorial #8: Perturbation and sensitivity analysis of Boolean networks
  • 0. Setup
  • 1. A running example Boolean network
  • 2. Exact attractors and robustness measures
  • 3. Basin-level and attractor-level robustness
  • 4. Visualization of basin robustness
  • 5. Approximate robustness for larger networks
  • 6. Derrida value: dynamical sensitivity
  • 7. Summary and outlook