Description
Microarray Bioinformatics, 1st ed. 2019
Methods in Molecular Biology Series, Vol. 1986
Language: English
Microarray Bioinformatics
Publication date: 08-2020
Support: Print on demand
Publication date: 08-2020
Support: Print on demand
Microarray Bioinformatics
299 p. · 17.8x25.4 cm · Hardback
299 p. · 17.8x25.4 cm · Hardback
Description
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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.
- Introduction to Bioinformatics
- Introduction to DNA microarrays
- Data Warehousing
- Microarray Annotation A review of microarray datasets: where to find them and specific characteristics
- Statistical analysis of microarray data
- Feature selection applied to microarray data
- Cluster analysis of microarray data
- Classification of microarray data
- Microarray data normalization and transformation
- HPC tools to deal with microarray data
- Sequence alignment with microarray data
- Experimental design of microarrays
- ROC curves for microarrays
- Image processing and microarrays
- Challenges and future trends
Includes cutting-edge techniques
Provides step-by-step detail essential for reproducible results
Contains key implementation advice from the experts
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