Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection
- Submitting institution
-
University of York
- Unit of assessment
- 12 - Engineering
- Output identifier
- 55030419
- Type
- D - Journal article
- DOI
-
10.1371/journal.pcbi.1005082
- Title of journal
- PLoS Computational Biology
- Article number
- e1005082
- First page
- -
- Volume
- 12
- Issue
- 9
- ISSN
- 1553-7358
- Open access status
- Compliant
- Month of publication
- September
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
3
- Research group(s)
-
B - Intelligent Systems and Nano-Science
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper develops a simulation framework, using multi-objective optimization, for assessing motility models describing in-vivo dynamics of cell motility. This novel approach could lead to significant impacts in cancer immunotherapy, search and rescue robotics, ecological and environmental management, and developmental biology. The work led to follow on work funded by the Australian Research Council for determining optimal search strategies for scarce targets in an environment (ARC DP180102458, A$400K) and an EPSRC funded project for assessing safety in mobile and autonomous robots (RoboTest, EP/R025479/1, £1.166M).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
