Optimal Design of Single-Cell Experiments within Temporally Fluctuating Environments.

ABSTRACT: Modern biological experiments are becoming increasingly complex, and designing these experiments to yield the greatest possible quantitative insight is an open challenge. Increasingly, computational models of complex stochastic biological systems are being used to understand and predict biological behaviors or to infer biological parameters. Such quantitative analyses can also help to improve experiment designs for particular goals, such as to learn more about specific model mechanisms or to reduce prediction errors in certain situations. A classic approach to experiment design is to use the Fisher information matrix (FIM), which quantifies the expected information a particular experiment will reveal about model parameters. The Finite State Projection based FIM (FSP-FIM) was recently devel

SUBMITTER: Fox ZR 

PROVIDER: S-EPMC7515449 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature