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Science/Engineering Complexity in Chemistry, Biology, and Ecology

Posted on 2010-03-15




Name:Science/Engineering Complexity in Chemistry, Biology, and Ecology
ASIN/ISBN:0387232648
Language:English
File size:2.6 Mb
ISBN: 0387232648
Pages: 344 pages
File Type: PDF
File Size: 2,6 Mb
Other Info: Springer; 1 edition (October 24, 2005)
   Science/Engineering Complexity in Chemistry, Biology, and Ecology

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Danail Bonchev, Dennis H. Rouvray, "Complexity in Chemistry, Biology, and Ecology"

The contemporary scientific method is built on reductionism. The surprising finding that this paradigm has limits gave rise to the concept of complexity. This book presents the new science of complexity by presenting diverse concepts from the analyses of a wide range of real world systems (chemical, biochemical, biological, and ecological). Based on a variety of approaches ranging from cellular automata and dynamic evolutionary networks to topology and information theory, the book contains methodologies of practical importance for assessing systems complexity and network analysis in medicine and biology.

The techniques presented can be applied for comparative studies in proteomics and genomics, in the search for drugs and markers for early diagnostics, in clinical proteomics, in stability/fragility analysis of ecosystems, as well as for such analysis of fullerenes and other nanotechnology products. The volume combines original results of the authors, which are internationally recognized experts, with a broad coverage of this explosively developing area.

The book offers new concepts and ideas that broaden reader’s perception of modern science.

Internationally established experts present the inspiring new science of complexity, which discovers new general laws covering wide range of science area

The book offers a broader view on complexity based on the expertise of the related areas of chemistry, biochemistry, biology, ecology, and physics.

Contains methodologies for assessing the complexity of systems that can be directly applied to proteomics and genomics, and network analysis in biology, medicine, and ecology.

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