Conditional robustness analysis for fragility discovery and target identification in biochemical networks and in cancer systems biology

• DOI: 10.1186/s12918-015-0216-5
• Publication Date: 2015-10-19T14:43:34Z
• Authors: Fortunato Bianconi; Elisa Baldelli; Vienna Luovini; Emanuel F. Petricoin; Lucio Crinò; Paolo Valigi
• Keywords: Robustness; Modelling biological systems; Identification

The study of cancer therapy is a key issue in the field oncology research and development target therapies one main problems currently under investigation. This particularly relevant different types tumor where traditional chemotherapy approaches often fail, such as lung cancer. We started from general definition robustness introduced by Kitano applied it to analysis dynamical biochemical networks, proposing new algorithm based on moment independent input/output uncertainty. framework utilizes novel computational methods which enable evaluating model fragility with respect quantitative performance measures parameters reaction rate constants initial conditions. generates small subset that can be used act complex networks obtain desired behaviors. have proposed EGFR-IGF1R signal transduction network, crucial pathway cancer, an example Cancer Systems Biology application drug discovery. Furthermore, we tested our pulse generator network Synthetic application, thus proving suitability methodology characterization synthetic circuits. achieved results are immediate practical biology, while demonstrate their use two specific examples, they fact wider class biological systems.