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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.
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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.
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2003
- ISBN 10 1402075820
- ISBN 13 9781402075827
- BindingHardcover
- LanguageEnglish
- Number of pages263
- EditorJohnson Kimberly F., Lin Simon M.
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9781402075827
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