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Computational Systems Biology

Chapter 19. Applications in Cancer Research: Mathematical Models of Apoptosis

By: Stefan M. Kallenberger,Stefan Legewie,Roland Eils

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Computational Systems Biology

Chapter 19. Applications in Cancer Research: Mathematical Models of Apoptosis

By: Stefan M. Kallenberger,Stefan Legewie,Roland Eils

Apoptosis is a form of cellular suicide central to various aspects in biology including tissue homeostasis and embryonic development. It is typically dysregulated in cancer. Understanding the apoptotic signal transduction network is thus a central goal of cancer research. Quantitative modeling approaches provided valuable insights into determinants of cell fate decisions, and promise to become a valuable tool to optimize therapeutic strategies. In this chapter, we summarize modeling approaches used in systems biology of apoptosis. In addition, we give an overview of apoptosis-related research questions that can be addressed by modeling. Moreover, we review top-down and bottom-up modeling approaches applied to apoptosis, and particularly focus on ordinary differential equation (ODE) modeling. We describe bistability, temporal switching, crosstalk between death and survival, and discuss approaches to model cell-to-cell variability.

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Page Count

50

Publisher

Elsevier Inc. Chapters

Published Date

ISBN 10

012807020X

ISBN 13

9780128070208

Computational Systems Biology

Chapter 9. Databases, Standards, and Modeling Platforms for Systems Biology

By: Juergen Eilsa,Elena Herzoga,Baerbel Felder,Christian Lawerenza,Roland Eils

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Computational Systems Biology

Chapter 9. Databases, Standards, and Modeling Platforms for Systems Biology

By: Juergen Eilsa,Elena Herzoga,Baerbel Felder,Christian Lawerenza,Roland Eils

Systems biology combines experimental and computational research to facilitate understanding of complex biological processes. In this chapter we describe data repositories, data standards, modeling, and visualization tools as prerequisites for systems biology research in order to help us to better study and understand biological processes. In addition, we propose improvements of these tools providing an example application (JUMMP) developed in our laboratory. We suggest that flexibility, interoperability, and modularity of novel applications contribute to better acceptance and further development of these tools. We also emphasize that having flexible and extendable standards describing complex and incomplete biological data allow new discoveries to be incorporated in a seamless way into systems biology tools. Overall, we discuss here advances, challenges and perspectives of data, and other platforms in systems biology which we believe will continue to make an impact on biomedical research.

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Page Count

27

Publisher

Elsevier Inc. Chapters

Published Date

ISBN 10

0128070102

ISBN 13

9780128070109