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.
