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Genomic signal processing / Ilya Shmulevich and Edward R. Dougherty.

De Gruyter Princeton University Press eBook-Package Backlist 2000-2013 Available online

De Gruyter Princeton University Press eBook-Package Backlist 2000-2013

EBSCOhost Academic eBook Collection (North America) Available online

EBSCOhost Academic eBook Collection (North America)

Ebook Central Academic Complete Available online

Ebook Central Academic Complete

Ebscohost Ebooks University Press Collection (North America) Available online

Ebscohost Ebooks University Press Collection (North America)
Format:
Book
Author/Creator:
Shmulevich, Ilya, 1969- author.
Dougherty, Edward R., author.
Series:
Princeton series in applied mathematics.
Princeton Series in Applied Mathematics
Language:
English
Subjects (All):
Cellular signal transduction.
Genetic regulation.
Genomics--Mathematical models.
Gene regulatory networks.
Physical Description:
1 online resource (314 p.)
Edition:
1st ed.
Place of Publication:
Princeton, New Jersey ; Oxfordshire, England : Princeton University Press, 2007.
Language Note:
English
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 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.
Contents:
Front matter
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
Notes:
Description based upon print version of record.
Includes bibliographical references and index.
Description based on print version record.
ISBN:
9781400865260
1400865263
OCLC:
888743988

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