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Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems (Hardcover, 2013 ed.)
Loot Price: R2,910
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Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems (Hardcover, 2013 ed.)
Series: Studies in Computational Intelligence, 428
Expected to ship within 10 - 15 working days
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Genetic Regulatory Networks (GRNs) in biological organisms are
primary engines for cells to enact their engagements with
environments, via incessant, continually active coupling. In
differentiated multicellular organisms, tremendous complexity has
arisen in the course of evolution of life on earth. Engineering and
science have so far achieved no working system that can compare
with this complexity, depth and scope of organization. Abstracting
the dynamics of genetic regulatory control to a computational
framework in which artificial GRNs in artificial simulated cells
differentiate while connected in a changing topology, it is
possible to apply Darwinian evolution in silico to study the
capacity of such developmental/differentiated GRNs to evolve. In
this volume an evolutionary GRN paradigm is investigated for its
evolvability and robustness in models of biological clocks, in
simple differentiated 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, organization, adaptive
plasticity, and evolvability of differentiated biological systems,
and may also provide a paradigm for transferring these principles
of biology's success to computational and engineering challenges at
a scale not previously conceivable.
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