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Advanced Analysis of Gene Expression Microarray Data
Contributor(s): Zhang, Aidong (Author)

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 ISBN: 9812566457     ISBN-13: 9789812566454
Publisher: World Scientific Publishing Company
OUR PRICE: $93.10  

Binding Type: Hardcover
Published: October 2006
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Annotation: This book focuses on the development and application of the latest advanced data mining, machine learning, and visualization techniques for the identification of interesting, significant, and novel patterns in gene expression microarray data.
Biomedical researchers will find this book invaluable for learning the cutting-edge methods for analyzing gene expression microarray data. Specifically, the coverage includes the following state-of-the-art methods:
- Gene-based analysis: the latest novel clustering algorithms to identify co-expressed genes and coherent patterns in gene expression microarray data sets
- Sample-based analysis: supervised and unsupervised methods for the reduction of the gene dimensionality to select significant genes. A series of approaches to disease classification and discovery are also described
- Pattern-based analysis: methods for ascertaining the relationship between (subsets of) genes and (subsets of) samples. Various novel pattern-based clustering algorithms to find the coherent patterns embedded in the sub-attribute spaces are discussed
- Visualization tools: various methods for gene expression data visualization. The visualization process is intended to transform the gene expression data set from high-dimensional space into a more easily understood two- or three-dimensional space.

Click for more in this series: Science, Engineering, and Biology Informatics
Additional Information
BISAC Categories:
- Science | Life Sciences - Genetics & Genomics
- Medical | Genetics
Dewey: 572.863
Series: Science, Engineering, and Biology Informatics
Physical Information: 0.95" H x 6.28" W x 9.08" L (1.46 lbs) 356 pages
Features: Bibliography, Illustrated, Index, Table of Contents
 
Descriptions, Reviews, Etc.
Publisher Description:
This book focuses on the development and application of the latest advanced data mining, machine learning, and visualization techniques for the identification of interesting, significant, and novel patterns in gene expression microarray data.Biomedical researchers will find this book invaluable for learning the cutting-edge methods for analyzing gene expression microarray data. Specifically, the coverage includes the following state-of-the-art methods: - Gene-based analysis: the latest novel clustering algorithms to identify co-expressed genes and coherent patterns in gene expression microarray data sets- Sample-based analysis: supervised and unsupervised methods for the reduction of the gene dimensionality to select significant genes. A series of approaches to disease classification and discovery are also described- Pattern-based analysis: methods for ascertaining the relationship between (subsets of) genes and (subsets of) samples. Various novel pattern-based clustering algorithms to find the coherent patterns embedded in the sub-attribute spaces are discussed- Visualization tools: various methods for gene expression data visualization. The visualization process is intended to transform the gene expression data set from high-dimensional space into a more easily understood two- or three-dimensional space.
 
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