Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Jeanquartier, F; Jean-Quartier, C; Cemernek, D; Holzinger, A.
In silico modeling for tumor growth visualization.
BMC Syst Biol. 2016; 10(1):59-59
Doi: 10.1186/s12918-016-0318-8
[OPEN ACCESS]
Web of Science
PubMed
FullText
FullText_MUG
- Führende Autor*innen der Med Uni Graz
- Holzinger Andreas
- Co-Autor*innen der Med Uni Graz
- Jean-Quartier Claire
- Altmetrics:
- Dimensions Citations:
- Plum Analytics:
- Scite (citation analytics):
- Abstract:
- 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. 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-cytoscape and http://styx.cgv.tugraz.at:8080/cpm-cytoscape/ . 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.
- Find related publications in this database (using NLM MeSH Indexing)
- Cell Proliferation -
- Computer Graphics -
- Computer Simulation -
- Internet -
- Models, Biological -
- Neoplasms - pathology
- User-Computer Interface -
- Find related publications in this database (Keywords)
- Cancer
- Tumor growth
- In silico
- In silico medicine
- Visualization
- Visual analysis
- Computational biology
- Cellular Potts model
- Glazier and Graner model
- Cell proliferation