Systematic calibration of a cell signaling network model

Background: Mathematical modeling is being applied to increasingly complex biological systems and datasets; however, the process of analyzing and calibrating against experimental data is often challenging and a rate limiting step in model development. To address this problem, we developed a systematic methodology for calibrating quantitative models of dynamic biological processes and illustrate its utility by validating a model of TRAIL (Tumor necrosis factor Related Apoptosis-Inducing Ligand)-induced cell death. Results: We propose a serial framework integrating analysis and calibration modules and we compare various methods for global sensitivity analysis and global parameter estimation. First, adequacy of the network structure is checked by global sensitivity analysis to changes in concentrations of molecular species, validating that the model can reproduce qualitative features of the system behavior derived from experiments or literature surveys. Second, rate parameters are ranked...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Kyoung Ae Kim, Sabrina L. Spencer, John G. Albeck, John M. Burke, Peter K. Sorger, Suzanne Gaudet, Do Hyun Kim
• Keywords: BMCBI 2010, Global Sensitivity Analysis, Model, Parameters