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Biology 2017, 6(4), 46;

Stability of Signaling Pathways during Aging—A Boolean Network Approach

Institute of Medical Systems Biology, Ulm University, 89069 Ulm, Germany
International Graduate School of Molecular Medicine, Ulm University, 89069 Ulm, Germany
Institute of Biochemistry and Molecular Biology, Ulm University, 89069 Ulm, Germany
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Holger Fröhlich
Received: 31 October 2017 / Revised: 10 December 2017 / Accepted: 14 December 2017 / Published: 18 December 2017
(This article belongs to the Special Issue Systems Biology of Aging)
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Biological pathways are thought to be robust against a variety of internal and external perturbations. Fail-safe mechanisms allow for compensation of perturbations to maintain the characteristic function of a pathway. Pathways can undergo changes during aging, which may lead to changes in their stability. Less stable or less robust pathways may be consequential to or increase the susceptibility of the development of diseases. Among others, NF- κ B signaling is a crucial pathway in the process of aging. The NF- κ B system is involved in the immune response and dealing with various internal and external stresses. Boolean networks as models of biological pathways allow for simulation of signaling behavior. They can help to identify which proposed mechanisms are biologically representative and which ones function but do not mirror physical processes—for instance, changes of signaling pathways during the aging process. Boolean networks can be inferred from time-series of gene expression data. This allows us to get insights into the changes of behavior of pathways such as NF- κ B signaling in aged organisms in comparison to young ones. View Full-Text
Keywords: Boolean networks; aging; reconstruction; stability Boolean networks; aging; reconstruction; stability

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Schwab, J.D.; Siegle, L.; Kühlwein, S.D.; Kühl, M.; Kestler, H.A. Stability of Signaling Pathways during Aging—A Boolean Network Approach. Biology 2017, 6, 46.

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