Journal article icon

Journal article

Designing and interpreting 4D tumour spheroid experiments

Abstract:
An enduring challenge in computational biology is to balance data quality and quantity with model complexity. Tools such as identifiability analysis and information criterion have been developed to harmonise this juxtaposition, yet cannot always resolve the mismatch between available data and the granularity required in mathematical models to answer important biological questions. Often, it is only simple phenomenological models, such as the logistic and Gompertz growth models, that are identifiable from standard experimental measurements. To draw insights from the complex, non-identifiable models that incorporate key biological mechanisms of interest, we study the geometry of a map in parameter space from the complex model to a simple, identifiable, surrogate model. By studying how non-identifiable parameters in the complex model quantitatively relate to identifiable parameters in surrogate, we introduce and exploit a layer of interpretation between the set of non-identifiable parameters and the goodness-of-fit metric or likelihood studied in typical identifiability analysis. We demonstrate our approach by analysing a hierarchy of mathematical models for multicellular tumour spheroid growth. Typical data from tumour spheroid experiments are limited and noisy, and corresponding mathematical models are very often made arbitrarily complex. Our geometric approach is able to predict non-identifiabilities, subset non-identifiable parameter spaces into identifiable parameter combinations that relate to individual data features, and overall provide additional biological insight from complex non-identifiable models
Publication status:
Published
Peer review status:
Peer reviewed

Actions

Access Document

Files:
Publisher copy:
10.1038/s42003-022-03018-3

Authors

More by this author
Role:
Author
ORCID:
0000-0002-9844-6734
More by this author
Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-8753-1538
More by this author
Role:
Author
ORCID:
0000-0003-1284-6751
More by this author
Role:
Author
ORCID:
0000-0002-3928-5360
More by this author
Role:
Author
ORCID:
0000-0001-6254-313X


Publisher:
Nature Research
Journal:
Communications Biology More from this journal
Volume:
5
Issue:
1
Pages:
91-91
Article number:
91
Publication date:
2022-01-24
DOI:
EISSN:
2399-3642
ISSN:
2399-3642


Language:
English
Keywords:
Pubs id:
1317577
Local pid:
pubs:1317577
Source identifiers:
W4221116131
Deposit date:
2026-05-01
ARK identifier:
This ORA record was generated from metadata provided by an external service. It has not been edited by the ORA Team.

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP