Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems

Name: Springer Nature | Genetic Regulatory Networks (GRNs) In Biological Organisms Are Primary Engines For Cells To Enact Their Engagements With Environments, Via Incessant, Continually Active Coupling.
Brand: Springer Nature
SKU: CBAH-71813
Price: 89.99 GBP
Availability: InStock

About The 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. 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

Genetic Regulatory Networks (GRNs) in biological organisms are primary engines for cells to enact their engagements with environments, via incessant, continually active coupling. 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. 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.

Books > Engineering

In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators.

One of the most surprising findings is that real networks behave very distinct from traditional assumptions of network theory.

Books > Engineering

Specifications of Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems
Category	Media > Books
Instock	instock

Last Updated January 10th, 2024 01:11 am

Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems

More Varieties

Media

Books

Rating :- 9.07 /10

Votes :- 11

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence â quickly and with a high quality.

The series contains monographs, lecture notes and edited volumes in computational intelligence spanning the areas of neural networks, connectionist systems, genetic algorithms, evolutionary computation, artificial intelligence, cellular automata, self-organizing systems, soft computing, fuzzy systems, and hybrid intelligent systems. The intent is to cover the theory, applications, and design methods of computational intelligence, as embedded in the fields of engineering, computer science, physics and life science, as well as the methodologies behind them.Computer and Information Science 2012 Critical to both contributors and readers are the short publication time and world-wide distribution - this permits a rapid and broad dissemination of research results.

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence â quickly and with a high quality.

One of the most surprising findings is that real networks behave very distinct from traditional assumptions of network theory.

But modern network research could show that the majority of nodes of real networks is very low connected, and, by contrast, there exists some nodes of very extreme connectivity (hubs).. Traditionally, real networks were supposed to have a majority of nodes of about the same number of connections around an average. This is typically modeled by random graphs.

health care, aircraft control, energy plant, management of technologies, product designs, innovations, marketing, finance etc.

Readers may urge us to list the fourth, fifth, sixth, â¦ but let us stop here and open this book.g. Second, basic technologies and sciences including sensor technologies, medical sciences, communication technologies etc. Partially because the editors Ohsawa and Abe are teaching at schools of Engineering and of Literature with sharing the interest in chance discovery, this book reflects interdisciplinary aspects of progress: First, as an interdisciplinary melting pot of cognitive science, computational intelligence, data mining/visualization, collective intelligence, â¦ etc, chance discovery came to reach new application domains e.

health care, aircraft control, energy plant, management of technologies, product designs, innovations, marketing, finance etc.

Since year 2000, scientists on artificial and natural intelligences started to study chance discovery - methods for discovering events/situations that significantly affect decision making.

Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems

Books > Engineering

Specifications of Computational Genetic Regulatory Networks: Evolvable, Self-organizing Systems

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence â quickly and with a high quality.

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence â quickly and with a high quality.

One of the most surprising findings is that real networks behave very distinct from traditional assumptions of network theory.

health care, aircraft control, energy plant, management of technologies, product designs, innovations, marketing, finance etc.

health care, aircraft control, energy plant, management of technologies, product designs, innovations, marketing, finance etc.

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence â quickly and with a high quality.

The series "Studies in Computational Intelligence" (SCI) publishes new developments and advances in the various areas of computational intelligence â quickly and with a high quality.