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A software application for simulation and analysis of biochemical networks and their dynamics.

COPASI (Complex Pathway Simulator) is a stand-alone software application designed for the simulation and analysis of biochemical networks and their dynamics. It supports models adhering to the SBML (Systems Biology Markup Language) standard, enabling interoperability and model sharing. COPASI simulates model behavior using ordinary differential equations (ODEs), stochastic differential equations (SDEs), and Gillespie's stochastic simulation algorithm, catering to both deterministic and stochastic modeling needs. It allows inclusion of arbitrary discrete events within simulations, increasing flexibility. The software provides a range of analysis methods, including parameter estimation, metabolic control analysis, and linear noise approximation. COPASI uses a graphical user interface (CopasiUI) for model construction and result visualization. It also provides command-line tools and language bindings for integration with other software. The sbmodelr tool, a python-based command line utility, helps to construct large models composed of repeating units.
COPASI (Complex Pathway Simulator) is a stand-alone software application designed for the simulation and analysis of biochemical networks and their dynamics.
Explore all tools that specialize in parameter estimation. This domain focus ensures COPASI delivers optimized results for this specific requirement.
Uses Gillespie's algorithm for stochastic simulation of biochemical networks, accounting for molecular noise.
Estimates model parameters by fitting simulation results to experimental data using various optimization algorithms.
Calculates control coefficients to quantify the influence of individual reactions on system fluxes and metabolite concentrations.
Supports the Systems Biology Markup Language (SBML) standard for model exchange and interoperability.
Provides Python (basiCO) and R (CoRC) bindings for programmatic access to COPASI functionalities.
Download the latest version of COPASI from the download page.
Install COPASI on your operating system (Windows, macOS, Linux).
Load a sample SBML model or create a new model using the COPASI UI.
Define the simulation task (e.g., Time Course, Steady State) and configure simulation parameters.
Run the simulation and analyze the results using COPASI's built-in analysis tools.
Explore parameter estimation and optimization functionalities to calibrate your model against experimental data.
Utilize language bindings (basiCO, CoRC) to integrate COPASI with Python or R scripts for custom analysis workflows.
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"COPASI is highly regarded for its accuracy and comprehensive feature set for biochemical network modeling and simulation, but the UI can be complex for new users."
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