Please use this identifier to cite or link to this item: https://doi.org/10.1109/BIBE.2008.4696734
Title: Systems analysis of bone mechanotransduction at cellular level
Authors: Mynampati, K.C. 
Sin, P.L.V.
Issue Date: 2008
Citation: Mynampati, K.C.,Sin, P.L.V. (2008). Systems analysis of bone mechanotransduction at cellular level. 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008 : -. ScholarBank@NUS Repository. https://doi.org/10.1109/BIBE.2008.4696734
Abstract: A 'systems-level' computational modeling approach is implemented to study the mechano-regulation of bone at cellular level. Issues addressed using this approach include - determining the intra-cellular response of bone cells to mechanical stimulus, bone response to different mechanical loading conditions, the role of intra-cellular feedback regulation in bone remodeling, and the link between reduced mechanical loading and decreased bone mass. An inter- connected network of signal transduction pathways in osteoblasts and osteoclasts is considered for modeling. The salient features of this modeling technique are Systems biology based network modeling to simulate the temporal dynamics of the signaling proteins, parameter estimation based on evolutionary Computing, and control Systems theory to model feedback in the signaling network. The results indicate that signaling networks respond uniquely to different mechanical stimuli, the stimulus signal is gradually attenuated in the signaling cascade, and the disruption of intra-cellular feedback regulation leads to decreased bone formation in osteoblasts and increased bone resorption in osteoclasts. This results in low bone mass, a phenomenon generally observed in reduced loading conditions. It is deduced that reduced mechanical loading leads to disruption in the feedback to resuit in low bone mass. The results of these simulation studies are expected to serve as useful guidelines for planning relevant experimental work to study the effect of mechanical loading on bone at cellular level.
Source Title: 8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008
URI: http://scholarbank.nus.edu.sg/handle/10635/74394
ISBN: 9781424428458
DOI: 10.1109/BIBE.2008.4696734
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