Geometric analysis enables biological insight from complex non-identifiable models using simple surrogates
Geometric analysis enables biological insight from complex non-identifiable models using simple surrogates
An enduring challenge in computational biology is to balance data quality and quantity with model complexity. Tools such as identifiability analysis and information criterion have been developed to harmonise this juxtaposition, yet cannot always resolve the mismatch between available data and the granularity required in mathematical models to answer important …