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- 520 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Book details
Table of contents
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About This Book
Microarray Image and Data Analysis: Theory and Practice is a compilation of the latest and greatest microarray image and data analysis methods from the multidisciplinary international research community. Delivering a detailed discussion of the biological aspects and applications of microarrays, the book:
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- Describes the key stages of image processing, gridding, segmentation, compression, quantification, and normalization
- Features cutting-edge approaches to clustering, biclustering, and the reconstruction of regulatory networks
- Covers different types of microarrays such as DNA, protein, tissue, and low- and high-density oligonucleotide arrays
- Examines the current state of various microarray technologies, including their availability and affordability
- Explains how data generated by microarray experiments are analyzed to obtain meaningful biological conclusions
An essential reference for academia and industry, Microarray Image and Data Analysis: Theory and Practice provides readers with valuable tools and techniques that extend to a wide range of biological studies and microarray platforms.
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Yes, you can access Microarray Image and Data Analysis by Luis Rueda in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Biology. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Dedication
- Table of Contents
- Preface
- Editor
- Contributors
- Chapter 1 Introduction to Microarrays
- Chapter 2 Biological Aspects: Types and Applications of Microarrays
- Chapter 3 Gridding Methods for DNA Microarray Images
- Chapter 4 Machine Learning-Based DNA Microarray Image Gridding
- Chapter 5 Non-Statistical Segmentation Methods for DNA Microarray Images
- Chapter 6 Statistical Segmentation Methods for DNA Microarray Images
- Chapter 7 Microarray Image Restoration and Noise Filtering
- Chapter 8 Compression of DNA Microarray Images
- Chapter 9 Image Processing of Affymetrix Microarrays
- Chapter 10 Treatment of Noise and Artifacts in Affymetrix Arrays
- Chapter 11 Quality Control and Analysis Algorithms for Tissue Microarrays as Biomarker Validation Tools
- Chapter 12 CNV-Interactome-Transcriptome Integration to Detect Driver Genes in Cancerology
- Chapter 13 Mining Gene-Sample-Time Microarray Data
- Chapter 14 Systematic and Stochastic Biclustering Algorithms for Microarray Data Analysis
- Chapter 15 Reconstruction of Regulatory Networks from Microarray Data
- Chapter 16 Multidimensional Visualization of Microarray Data
- Chapter 17 Bioconductor Tools for Microarray Data Analysis
- Index