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Systems biology beyond networks: Generating order from disorder through self-organization.

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Saetzler, Kurt, Sonnenschein, C and Soto, A. M. (2011) Systems biology beyond networks: Generating order from disorder through self-organization. Semin Cancer Biol, 21 . pp. 165-174. [Journal article]

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URL: http://dx.doi.org/10.1016/j.semcancer.2011.04.004

DOI: 10.1016/j.semcancer.2011.04.004

Abstract

Erwin Schrödinger pointed out in his 1944 book "What is Life" that one defining attribute of biological systems seems to be their tendency to generate order from disorder defying the second law of thermodynamics. Almost parallel to his findings, the science of complex systems was founded based on observations on physical and chemical systems showing that inanimate matter can exhibit complex structures although their interacting parts follow simple rules. This is explained by a process known as self-organization and it is now widely accepted that multi-cellular biological organisms are themselves self-organizing complex systems in which the relations among their parts are dynamic, contextual and interdependent. In order to fully understand such systems, we are required to computationally and mathematically model their interactions as promulgated in systems biology. The preponderance of network models in the practice of systems biology inspired by a reductionist, bottom-up view, seems to neglect, however, the importance of bidirectional interactions across spatial scales and domains. This approach introduces a shortcoming that may hinder research on emergent phenomena such as those of tissue morphogenesis and related diseases, such as cancer. Another hindrance of current modeling attempts is that those systems operate in a parameter space that seems far removed from biological reality. This misperception calls for more tightly coupled mathematical and computational models to biological experiments by creating and designing biological model systems that are accessible to a wide range of experimental manipulations. In this way, a comprehensive understanding of fundamental processes in normal development or of aberrations, like cancer, will be generated.

Item Type:Journal article
Faculties and Schools:Faculty of Life and Health Sciences
Faculty of Life and Health Sciences > School of Biomedical Sciences
Research Institutes and Groups:Biomedical Sciences Research Institute
Biomedical Sciences Research Institute > Molecular Medicine
ID Code:18827
Deposited By:Dr Kurt Saetzler
Deposited On:04 Oct 2011 10:24
Last Modified:19 Dec 2011 14:32

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