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E-raamat: Microarray Image and Data Analysis: Theory and Practice

Edited by (School of Computer Science, University of Windsor, Ontario, Canada)
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Computer scientists and electrical engineers present an advanced graduate textbook on the main methods, tools, and techniques for microarray image and data analysis. The topics include gridding methods for DNA microarray images, non-statistical segmentation methods for DNA microarray images, microarray image restoration and noise filtering, quality control and analysis algorithms for tissue microarrays as biomarker validation tools, systematic and stochastic biclustering algorithms for microarray data-analysis, and the multidimensional visualization of microarray data. Annotation ©2014 Ringgold, Inc., Portland, OR (protoview.com)

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.

Preface ix
Editor xiii
Contributors xv
Chapter 1 Introduction to Microarrays
1(40)
Luis Rueda
Adnan Ali
Chapter 2 Biological Aspects: Types and Applications of Microarrays
41(36)
Adnan Ali
Chapter 3 Gridding Methods for DNA Microarray Images
77(32)
Iman Rezaeian
Luis Rueda
Chapter 4 Machine Learning-Based DNA Microarray Image Gridding
109(20)
Dimitris Bariamis
Michalis Savelonas
Dimitris Maroulis
Chapter 5 Non-Statistical Segmentation Methods for DNA Microarray Images
129(20)
Shahram Shirani
Chapter 6 Statistical Segmentation Methods for DNA Microarray Images
149(22)
Meng-Yuan Tsai
Tai-Been Chen
Henry Horng-Shing Lu
Chapter 7 Microarray Image Restoration and Noise Filtering
171(24)
Rastislav Lukac
Chapter 8 Compression of DNA Microarray Images
195(32)
Miguel Hernandez-Cabronero
Michael W. Marcellin
Joan Serra-Sagrista
Chapter 9 Image Processing of Affymetrix Microarrays
227(28)
Jose Manuel Arteaga-Salas
Chapter 10 Treatment of Noise and Artifacts in Affymetrix Arrays
255(28)
Caroline C. Friedel
Chapter 11 Quality Control and Analysis Algorithms for Tissue Microarrays as Biomarker Validation Tools
283(30)
Todd H. Stokes
Sonal Kothari
Chih-wen Cheng
May D. Wang
Chapter 12 CNV-Interactome-Transcriptome Integration to Detect Driver Genes in Cancerology
313(26)
Maxime Garcia
Raphaele Millat-Carus
Francois Bertucci
Pascal Finetti
Arnaud Guille
Jose Adelaide
Ismahane Bekhouche
Renaud Sabatier
Max Chaffanet
Daniel Birnbaum
Ghislain Bidaut
Chapter 13 Mining Gene-Sample-Time Microarray Data
339(30)
Yifeng Li
Alioune Ngom
Chapter 14 Systematic and Stochastic Biclustering Algorithms for Microarray Data Analysis
369(32)
Wassim Ayadi
Mourad Elloumi
Jin-Kao Hao
Chapter 15 Reconstruction of Regulatory Networks from Microarray Data
401(30)
Yiqian Zhou
Rehman Qureshi
Francis Bell
Ahmet Sacan
Chapter 16 Multidimensional Visualization of Microarray Data
431(28)
Urska Cvek
Marjan Trutschl
Chapter 17 Bioconductor Tools for Microarray Data Analysis
459(22)
Simon Cockell
Matthew Bashton
Colin S. Gillespie
Index 481
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.
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