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Engineering Gene Regulatory Networks: A Reductionist Approach to Systems Biology

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Research in Computational Molecular Biology (RECOMB 2005)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 3500))

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Abstract

Many fundamental cellular processes are governed by genetic programs which employ protein-DNA interactions in regulating function. Owing to recent technological advances, it is now possible to design synthetic gene regulatory networks, and the stage is set for the notion of engineered cellular control at the DNA level. Theoretically, the biochemistry of the feedback loops associated with protein-DNA interactions often leads to nonlinear equations, and the tools of nonlinear analysis become invaluable. In this talk, we describe how techniques from nonlinear dynamics and molecular biology can be utilized to model, design and construct synthetic gene regulatory networks. We present examples in which we integrate the development of a theoretical model with the construction of an experimental system. We also discuss the implications of synthetic gene networks for gene therapy, biotechnology, biocomputing and nanotechnology. In particular, we describe how engineered gene networks can be used to reverse-engineer naturally occurring gene regulatory networks. Such methods may prove useful in identifying and validating specific drug targets and in deconvolving the effects of chemical compounds.

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© 2005 Springer-Verlag Berlin Heidelberg

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Collins, J.J. (2005). Engineering Gene Regulatory Networks: A Reductionist Approach to Systems Biology. In: Miyano, S., Mesirov, J., Kasif, S., Istrail, S., Pevzner, P.A., Waterman, M. (eds) Research in Computational Molecular Biology. RECOMB 2005. Lecture Notes in Computer Science(), vol 3500. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11415770_38

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  • DOI: https://doi.org/10.1007/11415770_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25866-7

  • Online ISBN: 978-3-540-31950-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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