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Table of contents (17 chapters)
Keywords
About this book
- overviews of the role of supercomputers in genomics research, the existing challenges and directions in image processing for microarray technology, and web-based tools for microarray data analysis;
- approaches to the global modeling and analysis of gene regulatory networks and transcriptional control, using methods, theories, and tools from signal processing, machine learning, information theory, and control theory;
- state-of-the-art tools in Boolean function theory, time-frequency analysis, pattern recognition, and unsupervised learning, applied to cancer classification, identification of biologically active sites, and visualization of gene expression data;
- crucial issues associated with statistical analysis of microarray data, statistics and stochastic analysis of gene expression levels in a single cell, statistically sound design of microarray studies and experiments; and
- biological and medical implications of genomics research.
Editors and Affiliations
About the editors
Bibliographic Information
Book Title: Computational and Statistical Approaches to Genomics
Editors: Wei Zhang, Ilya Shmulevich
DOI: https://doi.org/10.1007/b101927
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media Dordrecht 2002
eBook ISBN: 978-0-306-47825-3Published: 08 May 2007
Edition Number: 1
Number of Pages: XIV, 329
Number of Illustrations: 68 b/w illustrations, 20 illustrations in colour
Topics: Animal Anatomy / Morphology / Histology, Cancer Research, Biotechnology, Signal, Image and Speech Processing, Statistics, general