CRA toolbox: software package for conditional robustness analysis of cancer systems biology models in MATLAB

Area of Science:

• Systems Biology
• Computational Biology
• Cancer Research

Background:

• Investigating biochemical network robustness is crucial for developing targeted cancer therapies.
• Ordinary Differential Equation (ODE) models are standard for biological networks in systems biology.
• Robustness analysis quantifies the impact of parameter perturbations on a network's temporal behavior.

Purpose of the Study:

• Introduce the CRA Toolbox, a software package for Conditional Robustness Analysis (CRA).
• Implement CRA for ODE models to assess network robustness in cancer systems biology.
• Provide a user-friendly tool for analyzing biological network properties.

Main Methods:

• Developed an Object-Oriented MATLAB package implementing the CRA.
• Enabled importing models via Systems Biology Markup Language (SBML).
• Integrated a Graphical User Interface (GUI) for parameter perturbation, node selection, and results visualization.

Main Results:

• The CRA Toolbox facilitates robustness analysis on ODE models.
• Successfully applied the tool to three distinct nonlinear ODE models.
• Demonstrated the software's capability in analyzing complex biological networks.

Conclusions:

• The CRA Toolbox is an open-source MATLAB software for conditional robustness analysis.
• It offers a unique set of functions for the topological study of biological networks.
• Source code, examples, and documentation are freely available online.