Microarray Image and Data Analysis : Theory and Practice book cover
1st Edition

Microarray Image and Data Analysis
Theory and Practice

Edited By

Luis Rueda

ISBN 9781466586826
Published March 6, 2014 by CRC Press
520 Pages 137 B/W Illustrations

USD $140.00

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Book Description

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.

Table of Contents




Introduction to Microarrays

Luis Rueda and Adnan Ali

Biological Aspects: Types and Applications of Microarrays

Adnan Ali

Gridding Methods for DNA Microarray Images

Iman Rezaeian and Luis Rueda

Machine Learning-Based DNA Microarray Image Gridding

Dimitris Bariamis, Michalis Savelonas, and Dimitris Maroulis

Non-Statistical Segmentation Methods for DNA Microarray Images

Shahram Shirani

Statistical Segmentation Methods for DNA Microarray Images

Meng-Yuan Tsai, Tai-Been Chen, and Henry Horng-Shing Lu

Microarray Image Restoration and Noise Filtering

Rastislav Lukac

Compression of DNA Microarray Images

Miguel Hern´andez-Cabronero, Michael W. Marcellin, and Joan Serra-Sagrist`a

Image Processing of Affymetrix Microarrays

Jose Manuel Arteaga-Salas

Treatment of Noise and Artifacts in Affymetrix Arrays

Caroline C. Friedel

Quality Control and Analysis Algorithms for Tissue Microarrays as Biomarker Validation Tools

Todd H. Stokes, Sonal Kothari, Chih-wen Cheng, and May D. Wang

CNV-Interactome-Transcriptome Integration to Detect Driver Genes in Cancerology

Maxime Garcia, Rapha¨ele Millat-Carus, Franc¸ois Bertucci, Pascal Finetti, Arnaud Guille, Jos´e Ad´ela¨ıde, Ismahane Bekhouche, Renaud Sabatier, Max Chaffanet, Daniel Birnbaum, and Ghislain Bidaut

Mining Gene-Sample-Time Microarray Data

Yifeng Li and Alioune Ngom

Systematic and Stochastic Biclustering Algorithms for Microarray Data Analysis

Wassim Ayadi, Mourad Elloumi, and Jin-Kao Hao

Reconstruction of Regulatory Networks from Microarray Data

Yiqian Zhou, Rehman Qureshi, Francis Bell, and Ahmet Sacan

Multidimensional Visualization of Microarray Data

Urˇska Cvek and Marjan Trutschl

Bioconductor Tools for Microarray Data Analysis

Simon Cockell, Matthew Bashton, and Colin S. Gillespie


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Luis Rueda is professor for the School of Computer Science, University of Windsor, Ontario, Canada. Before joining the University of Windsor, he earned a Ph.D from Carleton University, Ottawa, Ontario, Canada and spent two years at the University of Concepción, Chile. A member of IEEE, the Association for Computing Machinery, and the International Society for Computational Biology, he holds three patents on data encryption, secrecy, and stealth; has published over 100 journal and conference papers; and has participated in numerous editorial and technical committees. His research is primarily focused on machine learning and pattern recognition in transcriptomics, interactomics, and genomics.