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Mathematical Tools in Cancer Signalling Systems Biology

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Cancer Systems Biology, Bioinformatics and Medicine

Abstract

Rather than a strictly formalized methodological framework, we here describe systems biology as a flexible approach in which the modelling strategy used depends on a trade-off between the nature of the biochemical network investigated, the biomedical question to be elucidated, and the quantity (and quality) of the experimental data available. To further substantiate this idea, we chose a number of recent scientific publications in which systems biology was used in the context of cancer cell signalling . Fundamental aspects of the strategy used to set up the mathematical models , integrate available biomedical knowledge, and specifically to generate quantitative data and analyse the system using theoretical and computational tools, are compared and discussed, but new avenues are also suggested.

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Acknowledgements

We thank the collaboration of the following people in the discussions of the papers analysed in this book chapter: A. Bittig, S. Boldt, S. Frey, J. Isaeva, X. Lai, F. Lange, A. Lao, U. Liebal, T. Millat, S. Pauleweit, P. Raasch, K. Rateischak, Y. Schmidt, U. Schmitz, F. Winter. J.V. is funded by the German Federal Ministry of Education and Research (BMBF) as part of the project CALSYS-FORSYS under contract 0315264 (http://www.sbi.uni-rostock.de/calsys). O.W. acknowledges funding through the Helmholtz Association, as part of the Systems Biology Alliance and the Stellenbosch Institute for Advanced Study (STIAS).

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Authors and Affiliations

  1. Department of Systems Biology and Bioinformatics, University of Rostock, 18051, Rostock, Germany

    Dr. Julio Vera

  2. Chair in Systems Biology and Bioinformatics, Department of Computer Science, University of Rostock, 18051, Rostock, Germany

    Prof. Dr. Olaf Wolkenhauer

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  1. Dr. Julio Vera
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Correspondence to Julio Vera .

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  1. Via vi Valcannuta 247, Rome, 00166, Italy

    Alfredo Cesario

  2. Rue Ed. Dereume 72, Rixensart, 1330, Belgium

    Frederick Marcus

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Vera, J., Wolkenhauer, O. (2011). Mathematical Tools in Cancer Signalling Systems Biology. In: Cesario, A., Marcus, F. (eds) Cancer Systems Biology, Bioinformatics and Medicine. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1567-7_7

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