Microarray Analysis, Mark Schena

Автор: Zhang Aidong
Название: Advanced analysis of gene expression microarray data
ISBN: 9812566457 ISBN-13(EAN): 9789812566454
Издательство: World Scientific Publishing
Рейтинг:
Цена: 59870.00 T
Наличие на складе: Есть
Описание: Focuses on the development and application of the advanced data mining, machine learning, and visualization techniques for the identification of significant patterns in gene expression microarray data. This book is suitable for biomedical researchers for learning the methods for analyzing gene expression microarray data.

Автор: Berrar Daniel P., Dubitzky Werner, Granzow Martin
Название: A Practical Approach to Microarray Data Analysis
ISBN: 1402072600 ISBN-13(EAN): 9781402072604
Издательство: Springer
Рейтинг:
Цена: 32600.00 T
Наличие на складе: Есть
Описание: A Practical Approach to Microarray Data Analysis is for all life scientists, statisticians, computer experts, technology developers, managers, and other professionals tasked with developing, deploying, and using microarray technology including the necessary computational infrastructure and analytical tools. 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. Key topics covered include: -Format of result from data analysis, analytical modeling/experimentation; -Validation of analytical results; -Data analysis/Modeling task; -Analysis/modeling tools; -Scientific questions, goals, and tasks; -Application; -Data analysis methods; -Criteria for assessing analysis methodologies, models, and tools.