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Methods of Microarray Data Analysis III

Papers from CAMDA ‘02

  • Textbook
  • © 2003

Overview

Editors:
  1. Kimberly F. Johnson

    1. Cancer Center Information Systems, Duke University Medical Center, Durham

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    You can also search for this editor in PubMed   Google Scholar

  2. Simon M. Lin

    1. Duke Bioinformatics Shared Resource, Duke University Medical Center, Durham

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    You can also search for this editor in PubMed   Google Scholar

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-xi
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  2. Introduction

    Pages 1-1

  3. Tutorials

    1. The Biology behind Gene Expression: A Basic Tutorial

      • Michael F. Ochs, Erica A. Golemis
      Pages 9-24

    2. Monitoring the Quality of Microarray Experiments

      • Kevin R. Coombes, Jing Wang, Lynne V. Abruzzo
      Pages 25-40

    3. Outliers in Microarray Data Analysis

      • Ronald K. Pearson, Gregory E. Gonye, James S. Schwaber
      Pages 41-55

  4. Best Presentation Award

    1. Organ-Specific Differences in Gene Expression and Unigene Annotations Describing Source Material

      • David N. Stivers, Jing Wang, Gary L. Rosner, Kevin R. Coombes
      Pages 59-72

  6. Normalizing Raw Data

    1. Comparison of Normalization Methods for cDNA Microarrays

      • Liling Warren, Ben Liu
      Pages 105-121

  7. Characterizing Technical and Biological Variance

    1. Simultaneous Assessment of Transcriptomic Variability and Tissue Effects in the Normal Mouse

      • Shibing Deng, Tzu-Ming Chu, Russ Wolfinger
      Pages 125-137

    2. How Many Mice and How Many Arrays? Replication in Mouse cDNA Microarray Experiments

      • Xiangqin Cui, Gary A. Churchill
      Pages 139-154

    3. Bayesian Characterization of Natural Variation in Gene Expression

      • Madhuchhanda Bhattacharjee, Colin Pritchard, Mikko J. Sillanpää, Elja Arjas
      Pages 155-172

  8. Investigating Cross Hybridization on Oligonucleotide Microarrays

    1. Quantification of Cross Hybridization on Oligonucleotide Microarrays

      • Li Zhang, Kevin R. Coombes, Lianchun Xiao
      Pages 175-184

    2. Assessing the Potential Effect of Cross-Hybridization on Oligonucleotide Microarrays

      • Seman Kachalo, Zarema Arbieva, Jie Liang
      Pages 185-198

    3. Who Are Those Strangers in the Latin Square?

      • Wen-Ping Hsieh, Tzu-Ming Chu, Russ Wolfinger
      Pages 199-208

  9. Finding Patterns and Seeking Biological Explanations

    1. Bayesian Decomposition Classification of the Project Normal Data Set

      • T. D. Moloshok, D. Datta, A. V. Kossenkov, M. F. Ochs
      Pages 211-231

    2. The Use of Go Terms to Understand the Biological Significance of Microarray Differential Gene Expression Data

      • Ramón Díaz-Uriarte, Fátima Al-Shahrour, Joaquín Dopazo
      Pages 233-247

  10. Back Matter

    Pages 249-252
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Keywords

About this book

As microarray technology has matured, data analysis methods have advanced as well. Methods Of Microarray Data Analysis III is the third book in this pioneering series dedicated to the existing new field of microarrays. While initial techniques focused on classification exercises (volume I of this series), and later on pattern extraction (volume II of this series), this volume focuses on data quality issues. Problems such as background noise determination, analysis of variance, and errors in data handling are highlighted.

Three tutorial papers are presented to assist with a basic understanding of underlying principles in microarray data analysis, and twelve new papers are highlighted analyzing the same CAMDA'02 datasets: the Project Normal data set or the Affymetrix Latin Square data set. A comparative study of these analytical methodologies brings to light problems, solutions and new ideas. This book is an excellent reference for academic and industrial researchers who want to keep abreast of the state of art of microarray data analysis.

Editors and Affiliations

  • Cancer Center Information Systems, Duke University Medical Center, Durham

    Kimberly F. Johnson

  • Duke Bioinformatics Shared Resource, Duke University Medical Center, Durham

    Simon M. Lin

About the editors

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

Bibliographic Information

  • Book Title: Methods of Microarray Data Analysis III

  • Book Subtitle: Papers from CAMDA ‘02

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

  • DOI: https://doi.org/10.1007/b105346

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 2003

  • Hardcover ISBN: 978-1-4020-7582-7Published: 30 September 2003

  • Softcover ISBN: 978-1-4757-8504-3Published: 05 May 2013

  • eBook ISBN: 978-0-306-48354-7Published: 08 May 2007

  • Edition Number: 1

  • Number of Pages: XI, 252

  • Number of Illustrations: 52 b/w illustrations, 1 illustrations in colour

  • Topics: Evolutionary Biology, Artificial Intelligence, Human Genetics, Physical Chemistry

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