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Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems
In this work, a method is established to calibrate a model that describes the basic dynamics of DNA damage and repair. The model can be used to extend planning for radiotherapy and hyperthermia in order to include the biological effects. In contrast to “syntactic” models (e.g., describing molecular...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7361897/ https://www.ncbi.nlm.nih.gov/pubmed/32695215 http://dx.doi.org/10.1155/2020/5972594 |
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author | Weyland, Mathias S. Thumser-Henner, Pauline Nytko, Katarzyna J. Rohrer Bley, Carla Ulzega, Simone Petri-Fink, Alke Lattuada, Marco Füchslin, Rudolf M. Scheidegger, Stephan |
author_facet | Weyland, Mathias S. Thumser-Henner, Pauline Nytko, Katarzyna J. Rohrer Bley, Carla Ulzega, Simone Petri-Fink, Alke Lattuada, Marco Füchslin, Rudolf M. Scheidegger, Stephan |
author_sort | Weyland, Mathias S. |
collection | PubMed |
description | In this work, a method is established to calibrate a model that describes the basic dynamics of DNA damage and repair. The model can be used to extend planning for radiotherapy and hyperthermia in order to include the biological effects. In contrast to “syntactic” models (e.g., describing molecular kinetics), the model used here describes radiobiological semantics, resulting in a more powerful model but also in a far more challenging calibration. Model calibration is attempted from clonogenic assay data (doses of 0–6 Gy) and from time-resolved comet assay data obtained within 6 h after irradiation with 6 Gy. It is demonstrated that either of those two sources of information alone is insufficient for successful model calibration, and that both sources of information combined in a holistic approach are necessary to find viable model parameters. Approximate Bayesian computation (ABC) with simulated annealing is used for parameter search, revealing two aspects that are beneficial to resolving the calibration problem: (1) assessing posterior parameter distributions instead of point-estimates and (2) combining calibration runs from different assays by joining posterior distributions instead of running a single calibration run with a combined, computationally very expensive objective function. |
format | Online Article Text |
id | pubmed-7361897 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-73618972020-07-20 Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems Weyland, Mathias S. Thumser-Henner, Pauline Nytko, Katarzyna J. Rohrer Bley, Carla Ulzega, Simone Petri-Fink, Alke Lattuada, Marco Füchslin, Rudolf M. Scheidegger, Stephan Comput Math Methods Med Research Article In this work, a method is established to calibrate a model that describes the basic dynamics of DNA damage and repair. The model can be used to extend planning for radiotherapy and hyperthermia in order to include the biological effects. In contrast to “syntactic” models (e.g., describing molecular kinetics), the model used here describes radiobiological semantics, resulting in a more powerful model but also in a far more challenging calibration. Model calibration is attempted from clonogenic assay data (doses of 0–6 Gy) and from time-resolved comet assay data obtained within 6 h after irradiation with 6 Gy. It is demonstrated that either of those two sources of information alone is insufficient for successful model calibration, and that both sources of information combined in a holistic approach are necessary to find viable model parameters. Approximate Bayesian computation (ABC) with simulated annealing is used for parameter search, revealing two aspects that are beneficial to resolving the calibration problem: (1) assessing posterior parameter distributions instead of point-estimates and (2) combining calibration runs from different assays by joining posterior distributions instead of running a single calibration run with a combined, computationally very expensive objective function. Hindawi 2020-07-06 /pmc/articles/PMC7361897/ /pubmed/32695215 http://dx.doi.org/10.1155/2020/5972594 Text en Copyright © 2020 Mathias S. Weyland et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Weyland, Mathias S. Thumser-Henner, Pauline Nytko, Katarzyna J. Rohrer Bley, Carla Ulzega, Simone Petri-Fink, Alke Lattuada, Marco Füchslin, Rudolf M. Scheidegger, Stephan Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems |
title | Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems |
title_full | Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems |
title_fullStr | Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems |
title_full_unstemmed | Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems |
title_short | Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems |
title_sort | holistic view on cell survival and dna damage: how model-based data analysis supports exploration of dynamics in biological systems |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7361897/ https://www.ncbi.nlm.nih.gov/pubmed/32695215 http://dx.doi.org/10.1155/2020/5972594 |
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