17th International Symposium on
Mathematical Theory of Networks and Systems
Kyoto International Conference Hall, Kyoto, Japan, July 24-28, 2006

MTNS 2006 Paper Abstract

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Paper TuP10.5

Kitano, Hiroaki (The Systems Biology Inst.)

The Theory of Biological Robustness and Its Applications to Medicine

Scheduled for presentation during the Mini-Symposium "Genomic Signals and Systems" (TuP10), Tuesday, July 25, 2006, 17:00−17:25, Room 103

17th International Symposium on Mathematical Theory of Networks and Systems, July 24-28, 2006, Kyoto, Japan

This information is tentative and subject to change. Compiled on June 23, 2024

Keywords Biological systems analysis, Medical applications, Biological systems control

Abstract

Robustness is a ubiquitously observed property of biological systems. It is considered to be a fundamental feature of complex evolvable systems. The author wish to formulate a basic framework in which various biological properties as well as medical issues can be described and understood in a consistent manner, as the theory of biological robustness [1]. It is expected to be one of the underlying thrust of systems biology [2], [3]. It is attained by several underlying principles that are universal to both biological organisms and sophisticated engineering systems. Robustness facilitates evolvability and robust traits are often selected by evolution. Such a mutually beneficial process is made possible by specific architectural features observed in robust systems. But there are trade-offs between robustness, fragility, performance and resource demands, which explain system behaviour, including the patterns of failure. Insights into inherent properties of robust systems will provide us with a better understanding of complex diseases, such as cancer [4], [5], diabetes [6], and autoimmune disorders, and a guiding principle for therapy design.

REFERENCES [1] H. Kitano, “Biological Robustness,” Nature Review Genetics, vol. 5, 2004, pp. 826-837. [2] H. Kitano, “Systems Biology: A Brief Overview,” Science, vol. 295, 2002, pp. 1662-1664. [3] H. Kitano, “Computational Systems Biology,” Nature, vol. 420, 2002, pp. 206-210. [4] H. Kitano, “Tumour tactics,” Nature, vol. 426, 2003, pp. 125. [5] H. Kitano, “Cancer as a robust system: implications for anticancer therapy,” Nature Reviews Cancer, vol. 4, 2004, pp. 227-235. [6] H. Kitano, K. Oda, T. Kimura, Y. Matsuoka, M. Csete, J. Doyle, M. Muramatsu, “Metabolic Syndrome and Robustness Tradeoffs,” Diabetes, vol. 53, 2004, pp. S6-S15.