In Silico Modeling For Tumor Growth Visualization

Fleur Jeanquartier, Claire Jean-Quartier, David Cemernek, Andreas Holzinger

Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

Abstract

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-cytoscape and
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
Spracheenglisch
Aufsatznummer10:59
Seiten1-5
FachzeitschriftBMC Systems Biology
Jahrgang10
Ausgabennummer1
DOIs
StatusVeröffentlicht - 4 Sep 2016

Fingerprint

Tumor Growth
Computer Simulation
Tumors
Visualization
Growth
Modeling
Neoplasms
Cancer
Potts model
Model
Graphical User Interface
Potts Model
Systems Biology
Graphical user interfaces
Web Application
Simulation Tool
Progression
Correlate
Web-based
Research

Schlagwörter

    ASJC Scopus subject areas

    • Information systems

    Fields of Expertise

    • Human- & Biotechnology
    • Information, Communication & Computing

    Treatment code (Nähere Zuordnung)

    • Basic - Fundamental (Grundlagenforschung)

    Dies zitieren

    In Silico Modeling For Tumor Growth Visualization. / Jeanquartier, Fleur; Jean-Quartier, Claire; Cemernek, David; Holzinger, Andreas.

    in: BMC Systems Biology, Jahrgang 10, Nr. 1, 10:59, 04.09.2016, S. 1-5.

    Publikation: Beitrag in einer FachzeitschriftArtikelForschungBegutachtung

    Jeanquartier, Fleur ; Jean-Quartier, Claire ; Cemernek, David ; Holzinger, Andreas. / In Silico Modeling For Tumor Growth Visualization. in: BMC Systems Biology. 2016 ; Jahrgang 10, Nr. 1. S. 1-5.
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    abstract = "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-cytoscape andhttp://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 animalexperimentation, 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",
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    N2 - 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-cytoscape andhttp://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 animalexperimentation, 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

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