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In silico modeling for tumor growth visualization
BACKGROUND: Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolate...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4977902/ https://www.ncbi.nlm.nih.gov/pubmed/27503052 http://dx.doi.org/10.1186/s12918-016-0318-8 |
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author | Jeanquartier, Fleur Jean-Quartier, Claire Cemernek, David Holzinger, Andreas |
author_facet | Jeanquartier, Fleur Jean-Quartier, Claire Cemernek, David Holzinger, Andreas |
author_sort | Jeanquartier, Fleur |
collection | PubMed |
description | BACKGROUND: Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biologists and clinical scientists are often overwhelmed by the mathematical background knowledge necessary to grasp and to apply a model to their own research. RESULTS: We aim to provide a comprehensive and expandable simulation tool to visualizing tumor growth. This novel Web-based application offers the advantage of a user-friendly graphical interface with several manipulable input variables to correlate different aspects of tumor growth. By refining model parameters we highlight the significance of heterogeneous intercellular interactions on tumor progression. Within this paper we present the implementation of the Cellular Potts Model graphically presented through Cytoscape.js within a Web application. The tool is available under the MIT license at https://github.com/davcem/cpm-cytoscapeand http://styx.cgv.tugraz.at:8080/cpm-cytoscape/. CONCLUSION: In-silico methods overcome the lack of wet experimental possibilities and as dry method succeed in terms of reduction, refinement and replacement of animal experimentation, also known as the 3R principles. Our visualization approach to simulation allows for more flexible usage and easy extension to facilitate understanding and gain novel insight. We believe that biomedical research in general and research on tumor growth in particular will benefit from the systems biology perspective. |
format | Online Article Text |
id | pubmed-4977902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49779022016-08-10 In silico modeling for tumor growth visualization Jeanquartier, Fleur Jean-Quartier, Claire Cemernek, David Holzinger, Andreas BMC Syst Biol Research Article BACKGROUND: Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models. Research on tumor growth involves a plethora of models each emphasizing isolated aspects of benign and malignant neoplasms. Biologists and clinical scientists are often overwhelmed by the mathematical background knowledge necessary to grasp and to apply a model to their own research. RESULTS: We aim to provide a comprehensive and expandable simulation tool to visualizing tumor growth. This novel Web-based application offers the advantage of a user-friendly graphical interface with several manipulable input variables to correlate different aspects of tumor growth. By refining model parameters we highlight the significance of heterogeneous intercellular interactions on tumor progression. Within this paper we present the implementation of the Cellular Potts Model graphically presented through Cytoscape.js within a Web application. The tool is available under the MIT license at https://github.com/davcem/cpm-cytoscapeand http://styx.cgv.tugraz.at:8080/cpm-cytoscape/. CONCLUSION: In-silico methods overcome the lack of wet experimental possibilities and as dry method succeed in terms of reduction, refinement and replacement of animal experimentation, also known as the 3R principles. Our visualization approach to simulation allows for more flexible usage and easy extension to facilitate understanding and gain novel insight. We believe that biomedical research in general and research on tumor growth in particular will benefit from the systems biology perspective. BioMed Central 2016-08-08 /pmc/articles/PMC4977902/ /pubmed/27503052 http://dx.doi.org/10.1186/s12918-016-0318-8 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Jeanquartier, Fleur Jean-Quartier, Claire Cemernek, David Holzinger, Andreas In silico modeling for tumor growth visualization |
title | In silico modeling for tumor growth visualization |
title_full | In silico modeling for tumor growth visualization |
title_fullStr | In silico modeling for tumor growth visualization |
title_full_unstemmed | In silico modeling for tumor growth visualization |
title_short | In silico modeling for tumor growth visualization |
title_sort | in silico modeling for tumor growth visualization |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4977902/ https://www.ncbi.nlm.nih.gov/pubmed/27503052 http://dx.doi.org/10.1186/s12918-016-0318-8 |
work_keys_str_mv | AT jeanquartierfleur insilicomodelingfortumorgrowthvisualization AT jeanquartierclaire insilicomodelingfortumorgrowthvisualization AT cemernekdavid insilicomodelingfortumorgrowthvisualization AT holzingerandreas insilicomodelingfortumorgrowthvisualization |