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Computational and Theoretical Concepts for Regulating Stem Cells Using Viral and Physical Methods

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Machine Learning and Systems Engineering

Abstract

Regenerative medicine is the application of tissue, sciences, engineering, computations, related biological, and biochemical principles that restore the structure and function of damaged tissues and organs. This new field encompasses many novel approaches to treatment of disease and restoration of biological function. Scientists are one-step closer to create a gene therapy/stem cell combination to combat genetic diseases. This research may lead to not only curing the disease, but also repairing the damage left behind. However, the development of gene therapy vectors with sufficient targeting ability, efficiency, and safety must be achieved before gene therapy can be routinely used in human. Delivery systems based on both viruses and non-viral systems are being explored, characterized, and used for in vitro and in vivo gene delivery. Although advances in gene transfer technology have been made, an ideal system has not yet been constructed. The development of scalable computer systems constitutes one-step toward understanding dynamics and potential of this process. Therefore, the primary goal of this work is to develop a computer model that will support investigations of both viral and non-viral methods for gene transfer on regenerative tissues including genetically modified stem cells. Different simulation scenarios were implemented, and their results were encouraging compared to ex-vivo experiments, where, the error rate lies in the range of acceptable values in this domain of application

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Correspondence to Aya Sedky Adly .

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Adly, A.S., Kandil, O.A.D., Ibrahim, M.S., Adly, M.S., Adly, A.S., Adly, A.S. (2010). Computational and Theoretical Concepts for Regulating Stem Cells Using Viral and Physical Methods. In: Ao, SI., Rieger, B., Amouzegar, M. (eds) Machine Learning and Systems Engineering. Lecture Notes in Electrical Engineering, vol 68. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9419-3_41

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  • DOI: https://doi.org/10.1007/978-90-481-9419-3_41

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