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Methods of Microarray Data Analysis II

Papers from CAMDA ’01

  • Book
  • © 2002

Overview

Editors:
  1. Simon M. Lin

    1. Duke University Medical Center, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Kimberly F. Johnson

    1. Duke University Medical Center, USA

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    You can also search for this editor in PubMed   Google Scholar

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xi
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  2. Introduction

    Pages 1-7

  3. An Introduction to DNA Microarrays

    • Patrick McConnell, Kimberly Johnson, David J. Lockhart
    Pages 9-21

  4. Experimental Design for Gene Microarray Experiments and Differential Expression Analysis

    • G. V. Bobashev, S. Das, A. Das
    Pages 23-41

  5. Microarray Data Processing and Analysis

    • Joaquín Dopazo
    Pages 43-63

  6. Biology-driven Clustering of Microarray Data

    • Kevin R. Coombes, Keith A. Baggerly, David N. Stivers, Jing Wang, David Gold, Hsi-Guang Sung et al.
    Pages 65-79

  7. Extracting Global Structure from Gene Expression Profiles

    • Charless Fowlkes, Qun Shan, Serge Belongie, Jitendra Malik
    Pages 81-90

  8. Supervised Neural Networks for Clustering Conditions in DNA Array Data After Reducing Noise by Clustering Gene Expression Profiles

    • Alvaro Mateos, Javier Herrero, Javier Tamames, Joaquín Dopazo
    Pages 91-103

  9. Bayesian Decomposition Analysis of Gene Expression in Yeast Deletion Mutants

    • Ghislain Bidaut, Thomas D. Moloshok, Jeffrey D. Grant, Frank J. Manion, Michael F. Ochs
    Pages 105-122

  10. Using Functional Genomic Units to Corroborate User Experiments with the Rosetta Compendium

    • Simon M. Lin, Xuejun Liao, Patrick McConnell, Korkut Vata, Lawrence Carin, Pascal Goldschmidt
    Pages 123-137

  11. Fishing Expedition - a Supervised Approach to Extract Patterns from a Compendium of Expression Profiles

    • Zhen Zhang, Grier Page, Hong Zhang
    Pages 139-149

  12. Modeling Pharmacogenomics of the NCI-60 Anticancer Data Set: Utilizing Kernel Pls to Correlate the Microarray Data to Therapeutic Responses

    • Nilanjan Dasgupta, Simon M. Lin, Lawrence Carin
    Pages 151-167

  13. Analysis of Gene Expression Profiles and Drug Activity Patterns by Clustering and Bayesian Network Learning

    • Jeong-Ho Chang, Kyu-Baek Hwang, Byoung-Tak Zhang
    Pages 169-184

  14. Evaluation of Current Methods of Testing Differential Gene expression and Beyond

    • Yi-Ju Li, Ling Zhang, Marcy C. Speer, Eden R. Martin
    Pages 185-194

  15. Extracting Knowledge from Genomic Experiments by Incorporating the Biomedical Literature

    • James P. Sluka
    Pages 195-209

  16. Back Matter

    Pages 211-214
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Keywords

About this book

Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis II is the second book in this pioneering series dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods, ranging from data normalization, feature selection, and discriminative analysis to machine learning techniques.

Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis II focuses on a single data set, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformatics/genomics courses in undergraduate and graduate programs.

Editors and Affiliations

  • Duke University Medical Center, USA

    Simon M. Lin, Kimberly F. Johnson

About the editors

Simon M. Lin is Manager of Duke Bioinformatics Shared Resource, Duke University Medical Center.
Kimberly F. Johnson is Director of Duke Cancer Center Information Systems and Director of Duke Bioinformatics Shared Resource, Duke University Medical Center.

Bibliographic Information

  • Book Title: Methods of Microarray Data Analysis II

  • Book Subtitle: Papers from CAMDA ’01

  • Editors: Simon M. Lin, Kimberly F. Johnson

  • DOI: https://doi.org/10.1007/b112982

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 2002

  • Hardcover ISBN: 978-1-4020-7111-9Published: 30 June 2002

  • Softcover ISBN: 978-1-4757-8831-0Published: 14 April 2013

  • eBook ISBN: 978-0-306-47598-6Published: 08 May 2007

  • Edition Number: 1

  • Number of Pages: XII, 214

  • Topics: Biochemistry, general, Human Genetics, Statistics for Life Sciences, Medicine, Health Sciences

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