BasiCO Documentation

BasiCO is a simplified interface to using COPASI from python. It is a collection of utility python scripts, that hide the complexity of the underlying SWIG generated language bindings.

Getting started

• Getting Started
  • Installation
  • Use the package
  • Loading a Model
  • Interrogating the Model
  • Analyzing the Model
  • Saving a Model

Examples

• Accessing Models from the database
  • BioModels
  • JWS Online
• Creating and simulating a simple model
• Getting and setting reaction parameters and reactions
  • Load model
  • Getting/setting global quantities
  • Getting/setting species (metabolites)
  • Getting/setting reaction parameters
  • Getting/setting reactions
  • Setting scheme
  • Setting reaction name
• Editing reaction kinetics
• Parameter Estimation
• Parameter estimation setup
  • preparing the data
  • setting up the parameter estimation
  • Constraints
• Parameter Estimation (import / export)
  • The Format
  • Example
• Optimization
  • Model
  • The Setup
  • Running the optimization
  • Customn Output
  • Constraints
• Simple simulations and plotting
  • Load a model
  • Run time course
  • Get compartments
  • Get parameters (“global quantities”)
  • Run steady state
  • Use pandas syntax for indexing and plotting
• Simulating a model with basico
  • The run_time_course command
• Simulating with custom results
  • Simulations:
  • Custom Selection list
  • Custom Time Points
  • For expert users
• Parameter Scans
  • Modifying Scan Settings
  • Runnin a scan:
• Sensitivity Analysis
  • Settings
  • Running the Analysis
• Working with arrays of Compartments
  • Linear arrays of compartments
  • Creating 2D array of compartments
• Using callbacks
  • Timeouts
• Working with Plots
• Working with Reports
  • Retrieving Report Definitions
  • Adding Reports
  • Changing values
  • Assigning to task
• Working with SBML Ids
• Working with Annotations
  • Resource Lists / Updating
  • Displaying Annotations:
  • Setting annotations
• Working with ipyparallel
• Working with PEtab
• Model Selection
• Working with Parameter Sets
  • Looking at parameter sets
  • Creating / Modifying Parameter sets
  • Removing parameter sets
  • Parameter sets and Parameter Estimation
• Profile likelihood
  • Preparing files
  • Processing the files:
  • Looking at the results
  • Everything together
• Metabolic Control Analysis
• Working with Widgets
• Retrieving all Task / Method Settings
• Linear Noise Approximation

API

• basico
  • basico package