Methods of Microarray Data Analysis III

Simon M. Lin

ISBN 10: 1402075820 / ISBN 13: 9781402075827

Published by Springer US, Springer New York Sep 2003, 2003

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 268 pp. Englisch.

Seller Inventory # 9781402075827

Bibliographic Details

• Title: Methods of Microarray Data Analysis III
• Publisher: Springer US, Springer New York Sep 2003
• Publication Date: 2003
• Language: English
• ISBN 10: 1402075820
• ISBN 13: 9781402075827
• Binding: Buch
• Condition: Neu

About this title

Synopsis

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.

About the Author

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.