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Genomic signal processing

Author: Ilya Shmulevich; Edward R Dougherty
Publisher: Princeton, N.J. : Princeton University Press, ©2007.
Series: Princeton series in applied mathematics.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical  Read more...
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Details

Genre/Form: Electronic books
Additional Physical Format: Print version:
(DLC) 2006936719
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Ilya Shmulevich; Edward R Dougherty
ISBN: 1322063273 9781322063270
OCLC Number: 888349051
Description: 1 online resource (xiii, 298 pages) : illustrations.
Contents: Frontmatter --
Contents --
Preface --
Chapter One. Biological Foundations --
Chapter Two. Deterministic Models of Gene Networks --
Chapter Three. Stochastic Models of Gene Networks --
Chapter Four. Classification --
Chapter Five. Regularization --
Chapter Six. Clustering --
Index.
Series Title: Princeton series in applied mathematics.
Responsibility: Ilya Shmulevich and Edward R. Dougherty.
More information:

Abstract:

Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine. Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention.

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