Close menu

SURE

Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

Using Emulation to Engineer and Understand Simulations of Biological Systems

Alden, Kieran, Cosgrove, Jason, Coles, Mark and Timmis, Jonathan (2018) Using Emulation to Engineer and Understand Simulations of Biological Systems. IEEE/ACM Transactions on Computational Biology and Bioinformatics. ISSN 1545-5963

Item Type: Article

Abstract

Modeling and simulation techniques have demonstrated success in studying biological systems. As the drive to better capture biological complexity leads to more sophisticated simulators, it becomes challenging to perform statistical analyses that help translate predictions into increased understanding. These analyses may require repeated executions and extensive sampling of high-dimensional parameter spaces: analyses that may become intractable due to time and resource limitations. Significant reduction in these requirements can be obtained using surrogate models, or emulators, that can rapidly and accurately predict the output of an existing simulator. We apply emulation to evaluate and enrich understanding of a previously published agent-based simulator of lymphoid tissue organogenesis, showing an ensemble of machine learning techniques can reproduce results obtained using a suite of statistical analyses within seconds. This performance improvement permits incorporation of previously intractable analyses, including multi-objective optimization to obtain parameter sets that yield a desired response, and Approximate Bayesian Computation to assess parametric uncertainty. To facilitate exploitation of emulation in simulation-focused studies, we extend our open source statistical package, spartan, to provide a suite of tools for emulator development, validation, and application. Overcoming resource limitations permits enriched evaluation and refinement, easing translation of simulator insights into increased biological understanding.

Full text not available from this repository.

More Information

Depositing User: Klaire Purvis-Shepherd

Identifiers

Item ID: 10850
Identification Number: https://doi.org/10.1109/TCBB.2018.2843339
ISSN: 1545-5963
URI: http://sure.sunderland.ac.uk/id/eprint/10850
Official URL: https://ieeexplore.ieee.org/document/8374844

Users with ORCIDS

Catalogue record

Date Deposited: 07 Jun 2019 13:55
Last Modified: 07 Jun 2019 14:53

Contributors

Author: Kieran Alden
Author: Jason Cosgrove
Author: Mark Coles
Author: Jonathan Timmis

University Divisions

Services > University Executive

Subjects

Sciences > Biomedical Sciences
Computing

Actions (login required)

View Item (Repository Staff Only) View Item (Repository Staff Only)