Microarray image and data analysis : theory and practice
著者
書誌事項
Microarray image and data analysis : theory and practice
（Digital imaging and computer vision series）
CRC Press, 2018, c2014
- : pbk
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注記
"First issued in paperback 2018"--T.p. verso
Includes bibliographical references and index
内容説明・目次
内容説明
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:
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.
目次
Introduction to Microarrays. Biological Aspects: Types and Applications of Microarrays. Gridding Methods for DNA Microarray Images. Machine Learning-Based DNA Microarray Image Gridding. Non-Statistical Segmentation Methods for DNA Microarray Images. Statistical Segmentation Methods for DNA Microarray Images. Microarray Image Restoration and Noise Filtering. Compression of DNA Microarray Images. Image Processing of Affymetrix Microarrays. Treatment of Noise and Artifacts in Affymetrix Arrays. Quality Control and Analysis Algorithms for Tissue Microarrays. CNV-Interactome-Transcriptome Integration. Mining Gene-Sample-Time Microarray Data. Systematic and Stochastic Biclustering Algorithms for Microarray Data Analysis. Reconstruction of Regulatory Networks from Microarray Data. Multidimensional Visualization of Microarray Data. Bioconductor Tools for Microarray Data Analysis.
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