To Sobol or not to Sobol? The effects of sampling schemes in systems biology applications.

ABSTRACT: Computational and mathematical models in biology rely heavily on the parameters that characterize them. However, robust estimates for their values are typically elusive and thus a large parameter space becomes necessary for model study, particularly to make translationally impactful predictions. Sampling schemes exploring parameter spaces for models are used for a variety of purposes in systems biology, including model calibration and sensitivity analysis. Typically, random sampling is used; however, when models have a high number of unknown parameters or the models are highly complex, computational cost becomes an important factor. This issue can be reduced through the use of efficient sampling schemes such as Latin hypercube sampling (LHS) and Sobol sequences. In this work, we compare an

SUBMITTER: Renardy M 

PROVIDER: S-EPMC8184610 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature