A Practical Approach to Microarray Data Analysis

Daniel P. Berrar

ISBN 10: 1441912266 / ISBN 13: 9781441912268

Published by SPRINGER NATURE Aug 2009, 2009

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -The book addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and tools. It is intended for students, teachers, researchers, and research managers who want to understand the state of the art and of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. The book is designed to be used by the practicing professional tasked with the design and analysis of microarray experiments or as a text for a senior undergraduate- or graduate level course in analytical genetics, biology, bioinformatics, computational biology, statistics and data mining, or applied computer science. 368 pp. Englisch.

Seller Inventory # 9781441912268

Bibliographic Details

• Title: A Practical Approach to Microarray Data Analysis
• Publisher: SPRINGER NATURE Aug 2009
• Publication Date: 2009
• Language: English
• ISBN 10: 1441912266
• ISBN 13: 9781441912268
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 237W x 159H x 25D millimeters 237 millimeters width by 159 millimeters height by 25 millimeters depth
• Weight: 562 grams

About this title

Synopsis

The book addresses the requirement of scientists and researchers to gain a basic understanding of microarray analysis methodologies and tools. It is intended for students, teachers, researchers, and research managers who want to understand the state of the art and of the presented methodologies and the areas in which gaps in our knowledge demand further research and development. The book is designed to be used by the practicing professional tasked with the design and analysis of microarray experiments or as a text for a senior undergraduate- or graduate level course in analytical genetics, biology, bioinformatics, computational biology, statistics and data mining, or applied computer science.