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Products - Books & Software - DNA Array Image Analysis Compilation Focusing on Microarray Scanning and Data Analysis
DNA Array Image Analysis Nuts & Bolts
Gerda Kamberova, Ph.D. and Shishir Shah, Ph.D.
Publisher: Xela Schenk
Cover Design and Production Layout: Alex Nartea
Microarray and Image Analysis: Introduction
Gerda Kamberova, Shishir Shah
Introduction to Image Analysis
Advantages of Laser Confocal Microarray Scanning
Mark McGovern, Reda Fayek
Considerations for a Quality Microarray Scanner
Scott J. Vacha, Jeffrey McMillan, Andreas Dorsel (Agilent Technologies, Inc.)
Key Considerations for Accurate Microarray Scanning
and Image Analysis.
Shawn Handran, Siobahn Pickett, Damian Verdnik (Axon Instruments, Inc.)
Microarray Image Processing and Quality Control
Anton Petrov, Shishir Shah, Sorin Draghici, Soheil Shams
Microarray Data Normalization
Michael F. Ochs, Ghislain Bidaut
Quantitative Comparison of Image Analysis Software
Diane Moody, Bassem Fadlia, Abhay Singh, Swapnal Shah, Lauren McIntyre
DNA Array Information Workflow and Data Management
S. Shah, J.P. Gregg, M. Mohammed, W. Yu, S. Damani, R. Locker
Chapter 1: Microarrays and Image Analysis: Introduction
The chapter provides brief introduction to microarray technology and the challenges of image analysis in this field. It outlines the objectives of the book. Chapter 1 is intended as a reading material for students and researchers with different scientific backgrounds who are just entering the exciting field of microarray research and applications.
Chapter 2: Introduction to Image Analysis
The chapter introduces basic image analysis terminology and techniques. The digital image, its various representations, and properties are presented. The process of image formation, noise, and noise sources are reviewed. The author discusses important image processing operations. Estimation of image parameters in the presence of noise is addressed. The chapter contains an appendix including mathematical definitions from Fourier analysis and probability theory.
Chapter 3: Advantages of Laser Confocal Microarray Scanning
This chapter provides a general understanding of different approaches used to design commercial microarray scanners. Particular attention is given to laser confocal microarray scanners. Important issues in the authors’ discussion are resolution, sensitivity, the use of multiple dyes, and other requirements in the design of commercial microarray scanners.
Chapter 4: Considerations for a Quality Microarray Scanner
This chapter continues the discussion on microarray scanners. Although intended as a general introduction, several features of Agilent’s SureScan Technology are introduced. The authors discuss issues of instrument noise, sensitivity and resolution.
Chapter 5: Key Considerations for Accurate Microarray Scanning and Image Analysis
This chapter reviews how to obtain the most reliable performance from the microarray scanner. The authors from Axon, Inc. discuss several image analysis methods used in microarray experiments, including numerical pre-processing methods that can be considered prior to cluster analysis of large sets of microarray data.
Chapter 6: Microarray Image Processing and Quality Control
Chapter 6 describes the issues of spot finding, microarray image segmentation, and quality control issues in microarray image analysis. The authors discuss automated batch analysis of microarray images.
Chapter 7: Microarray Data Normalization
This chapter discusses the issue of data normalization for spotted microarrays. The authors dwell on background correction, and data normalization, including a summary of each of the methods which have been widely used. A sample procedure for data normalization is then given along with a brief discussion of types of noise which normalization cannot handle.
Chapter 8: Quantitative Comparison of Image Analysis Software
In this chapter, the authors from Purdue University describe a systematic evaluation of three microarray data acquisition software packages. In order to provide a benchmark to which investigators may compare the reliability of data acquisition in their own experiments, they have evaluated these software packages using a variety of different types of arrays (macro and microarrays; glass and nylon; cDNA and bacterial). The reliability, accuracy, and throughput of data generated from each type of microarray and each software package are discussed.
Chapter 9: DNA Array Information Workflow and Data Management
This chapter outlines the flow of data in a microarray experiment. It discusses some aspects of microarray database management and data mining.
Chapter 10: BAC Microarrays
This chapter discusses an emerging application for microarray technology, which utilizes bacterial artificial chromosomes (BACs). The authors focus on the experimental design, image analysis and data normalization.
Gerda Kamberova, Ph.D. is an Assistant Professor in Computer Science at Hofstra University, New York. She teaches computer vision, computer graphics, and artificial intelligence. Her Ph.D in Computer Science is from the University of Pennsylvania, Philadelphia. Dr. Kamberova has published research papers in computer vision, robotics, and applied statistics. Her current research interests are in shape representation and recovery and 3D data compression.
Gerda L. Kamberova, Ph.D., 103 Hofstra University, Department of Computer Science, Hempstead, NY 11549 U.S.A. E-mail: Gerda.L.Kamberova@hofstra.edu
Shishir Shah, Ph.D. is an Associate Professor at Wayne State University (Detroit, MI). Dr. Shah is an author of numerous publications on image analysis and data mining. His current interests are developing new applications for BAC arrays, enhanced microarray image processing and data analysis.
Shishir Shah, Ph.D., 2302 Oak Links Avenue, Houston, TX 77059 U.S.A.
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