About this book
This book provides a comprehensive, interdisciplinary collection of the main, up-to-date methods, tools, and techniques for microarray data analysis, covering the necessary steps for the acquisition of the data, its preprocessing, and its posterior analysis. Featuring perspectives from biology, computer science, and statistics, the volume explores machine learning methods such as clustering, feature selection, classification, data normalization, and missing value imputation, as well as the statistical analysis of the data and the most popular computer tools to analyze microarray data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will aid researchers in getting successful results.
Cutting-edge and authoritative, Microarray Bioinformatics serves as an ideal guide for researchers and graduate students in bioinformatics, with basic knowledge in biology and computer science, and with a view to work with microarray datasets.
DNA microarrays Datasets Data warehousing Machine learning Statistical analysis Computer science
Editors and affiliations
- DOI https://doi.org/10.1007/978-1-4939-9442-7
- Copyright Information Springer Science+Business Media, LLC, part of Springer Nature 2019
- Publisher Name Humana, New York, NY
- eBook Packages Springer Protocols
- Print ISBN 978-1-4939-9441-0
- Online ISBN 978-1-4939-9442-7
- Series Print ISSN 1064-3745
- Series Online ISSN 1940-6029
- Buy this book on publisher's site