Determining parameter impact in systems biology models via sensitivity analysis: a comparative approach (opens in new tab)

Mathematical modeling is a powerful tool to understand biological phenomena, predict behavior, and guide experiments. Model parameters represent experimentally derived rates, and it can be challenging to understand how parameters affect the system’s output(s). Global sensitivity analysis (GSA) can help determine how uncertainty in model outcomes can be attributed to parameters. Methods like Sobol’ indices provide detailed analysis but at a high computational cost. Thus, it may be necessary to...