Foundations of Systems Biology
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Foundations of Systems Biology

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ISBN-13:
9780262277204
Veröffentl:
2001
Einband:
PDF
Seiten:
314
Autor:
Hiroaki Kitano
Serie:
The MIT Press
eBook Typ:
PDF
eBook Format:
PDF
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Englisch
Beschreibung:

An overview of the methodologies and techniques of the emerging field of systems biology.The emerging field of systems biology involves the application of experimental, theoretical, and modeling techniques to the study of biological organisms at all levels, from the molecular, through the cellular, to the behavioral. Its aim is to understand biological processes as whole systems instead of as isolated parts. Developments in the field have been made possible by advances in molecular biology-in particular, new technologies for determining DNA sequence, gene expression profiles, protein-protein interactions, and so on. Foundations of Systems Biology provides an overview of the state of the art of the field. The book covers the central topics of systems biology: comprehensive and automated measurements, reverse engineering of genes and metabolic networks from experimental data, software issues, modeling and simulation, and system-level analysis.
An overview of the methodologies and techniques of the emerging field of systems biology.The emerging field of systems biology involves the application of experimental, theoretical, and modeling techniques to the study of biological organisms at all levels, from the molecular, through the cellular, to the behavioral. Its aim is to understand biological processes as whole systems instead of as isolated parts. Developments in the field have been made possible by advances in molecular biology-in particular, new technologies for determining DNA sequence, gene expression profiles, protein-protein interactions, and so on. Foundations of Systems Biology provides an overview of the state of the art of the field. The book covers the central topics of systems biology: comprehensive and automated measurements, reverse engineering of genes and metabolic networks from experimental data, software issues, modeling and simulation, and system-level analysis.

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