Multifidelity Analysis for Predicting Rare Events in Stochastic Computational Models of Complex Biological Systems.

ABSTRACT: Rare events such as genetic mutations or cell-cell interactions are important contributors to dynamics in complex biological systems, eg, in drug-resistant infections. Computational approaches can help analyze rare events that are difficult to study experimentally. However, analyzing the frequency and dynamics of rare events in computational models can also be challenging due to high computational resource demands, especially for high-fidelity stochastic computational models. To facilitate analysis of rare events in complex biological systems, we present a multifidelity analysis approach that uses medium-fidelity analysis (Monte Carlo simulations) and/or low-fidelity analysis (Markov chain models) to analyze high-fidelity stochastic model results. Medium-fidelity analysis can produce large

SUBMITTER: Pienaar E 

PROVIDER: S-EPMC6077899 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature