Titlebook: Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems; Johannes F. Knabe Book 2013 Springer Berlin Heidelberg 2013

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978-3-642-44805-8Springer Berlin Heidelberg 2013

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On the Kinematics of Stochastic Mechanics,aped organisms, prompting [Dobzhansky(1973)] to utter his famous: “Nothing in biology makes sense except in the light of evolution”. A very general definition of evolution in nature is “change in the gene pool over time”. (Where the ‘gene’ is a hereditary unit that can be passed on unaltered for man

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https://doi.org/10.1007/978-3-540-74173-2nfluential has been the so-called “motif analysis”, a general analysis method for all kinds of networks. This might be due to its simplicity, as it only searches for patterns (subgraphs) in the static, time-independent, connectivity structure of networks. Network . “are those patterns for which the

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Optimization of a Manufacturing Systemlar organisms from a single fertilised egg cell has fascinated humans at least since Aristotle’s speculations more than 2000 years ago [Wolpert et al(2007)Wolpert, Jessell, Lawrence, Meyerowitz, Robertson, and Smith]. In the more recent past our understanding of how interacting genes direct developm

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Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems978-3-642-30296-1Series ISSN 1860-949X Series E-ISSN 1860-9503

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Book 2013differentiated multicellularity, and in evolving artificial developing ‘organisms‘ which grow and express an ontogeny starting from a single cell interacting with its environment, eventually including a changing local neighbourhood of other cells. .These methods may help us understand the genesis, o