PyCoTools

PyCoTools provides a Python interface to COPASI for constructing, simulating, and calibrating dynamic biochemical network models, with emphasis on automated parameter estimation, model selection, and identifiability analysis.

Key Features:

• Model Construction and Simulation: Builds and simulates biochemical network models within the COPASI framework.
• Programmatic Task Execution: Executes COPASI tasks including time course simulations, parameter scans, and parameter estimations.
• Composite Tasks: Combines basic COPASI tasks to increase parameter estimation throughput, perform identifiability analysis, and support model selection.
• Exploratory Data Analysis: Analyzes parameter estimation results to evaluate model calibration and detect optimization issues.
• Model Selection Strategies: Compares alternative biochemical network models using parameter estimation results and experimental data.

Scientific Applications:

• TGF-β Signaling in Neonatal Dermal Fibroblasts: Evaluates dynamic responses to TGF-β using time-resolved experimental data to test alternative biochemical network hypotheses.

Methodology:

Leverages COPASI’s simulation and optimization engines through a Python-based interface to automate time course simulation, parameter scanning, parameter estimation, identifiability analysis, and model selection.