Abstract
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-B signaling is a crucial pathway in the process of aging. The NF-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-B signaling in aged organisms in comparison to young ones.
Highlights
Systems Biology, the study of complex biological systems, is an emerging field in science.Many different disciplines like biology, chemistry, physics and computer sciences among others are employed to analyze biological systems
The method to investigate the changing stability during aging via Boolean networks can be separated into several steps (Figure 1)
The results show that both the network representing the young phenotype and the one representing the aged phenotype were reconstructed with about the same mean input for each gene (Figure 3A)
Summary
Systems Biology, the study of complex biological systems, is an emerging field in science.Many different disciplines like biology, chemistry, physics and computer sciences among others are employed to analyze biological systems. Systems Biology, the study of complex biological systems, is an emerging field in science. Traditional life science follows a reductionist approach. This approach has successfully identified many components and their interactions [1]. It does not describe system properties emerging from the interactions of these components. In Systems Biology, dynamic models allow for simulation of the behavior of such systems. The simulation gives valuable insights into the behavior of complex systems and hypotheses about the system can be extracted [2]. Boolean networks are one kind of dynamic models that can be used to simulate, for instance, signaling pathways [3]
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