Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study
Abstract Background Contemporary biological observations have revealed a large variety of mechanisms acting during the expansion of a tumor. However, there are still many qualitative and quantitative aspects of the phenomenon that remain largely unknown. In this context, mathematical and computation...
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doaj-ae2fc51865f84acd84454d513ded5e062020-11-25T03:54:03ZengBMCBMC Bioinformatics1471-21052019-08-0120113610.1186/s12859-019-2997-9Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical studyMarkos Antonopoulos0Dimitra Dionysiou1Georgios Stamatakos2Nikolaos Uzunoglu3Institute of Communication and Computer Systems, National Technical University of AthensInstitute of Communication and Computer Systems, National Technical University of AthensInstitute of Communication and Computer Systems, National Technical University of AthensInstitute of Communication and Computer Systems, National Technical University of AthensAbstract Background Contemporary biological observations have revealed a large variety of mechanisms acting during the expansion of a tumor. However, there are still many qualitative and quantitative aspects of the phenomenon that remain largely unknown. In this context, mathematical and computational modeling appears as an invaluable tool providing the means for conducting in silico experiments, which are cheaper and less tedious than real laboratory experiments. Results This paper aims at developing an extensible and computationally efficient framework for in silico modeling of tumor growth in a 3-dimensional, inhomogeneous and time-varying chemical environment. The resulting model consists of a set of mathematically derived and algorithmically defined operators, each one addressing the effects of a particular biological mechanism on the state of the system. These operators may be extended or re-adjusted, in case a different set of starting assumptions or a different simulation scenario needs to be considered. Conclusion In silico modeling provides an alternative means for testing hypotheses and simulating scenarios for which exact biological knowledge remains elusive. However, finer tuning of pertinent methods presupposes qualitative and quantitative enrichment of available biological evidence. Validation in a strict sense would further require comprehensive, case-specific simulations and detailed comparisons with biomedical observations.http://link.springer.com/article/10.1186/s12859-019-2997-9Tumor growthCellular diffusionChemical diffusionIn silico modelingComputational modeling |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Markos Antonopoulos Dimitra Dionysiou Georgios Stamatakos Nikolaos Uzunoglu |
spellingShingle |
Markos Antonopoulos Dimitra Dionysiou Georgios Stamatakos Nikolaos Uzunoglu Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study BMC Bioinformatics Tumor growth Cellular diffusion Chemical diffusion In silico modeling Computational modeling |
author_facet |
Markos Antonopoulos Dimitra Dionysiou Georgios Stamatakos Nikolaos Uzunoglu |
author_sort |
Markos Antonopoulos |
title |
Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study |
title_short |
Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study |
title_full |
Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study |
title_fullStr |
Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study |
title_full_unstemmed |
Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study |
title_sort |
three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2019-08-01 |
description |
Abstract Background Contemporary biological observations have revealed a large variety of mechanisms acting during the expansion of a tumor. However, there are still many qualitative and quantitative aspects of the phenomenon that remain largely unknown. In this context, mathematical and computational modeling appears as an invaluable tool providing the means for conducting in silico experiments, which are cheaper and less tedious than real laboratory experiments. Results This paper aims at developing an extensible and computationally efficient framework for in silico modeling of tumor growth in a 3-dimensional, inhomogeneous and time-varying chemical environment. The resulting model consists of a set of mathematically derived and algorithmically defined operators, each one addressing the effects of a particular biological mechanism on the state of the system. These operators may be extended or re-adjusted, in case a different set of starting assumptions or a different simulation scenario needs to be considered. Conclusion In silico modeling provides an alternative means for testing hypotheses and simulating scenarios for which exact biological knowledge remains elusive. However, finer tuning of pertinent methods presupposes qualitative and quantitative enrichment of available biological evidence. Validation in a strict sense would further require comprehensive, case-specific simulations and detailed comparisons with biomedical observations. |
topic |
Tumor growth Cellular diffusion Chemical diffusion In silico modeling Computational modeling |
url |
http://link.springer.com/article/10.1186/s12859-019-2997-9 |
work_keys_str_mv |
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