Microarray Image Analysis: An Algorithmic Approach

Karl Fraser, Zidong Wang, Xiaohui Liu

June 14, 2017 by Chapman and Hall/CRC
Reference - 335 Pages - 134 B/W Illustrations
ISBN 9781138115156 - CAT# K35416
Series: Chapman & Hall/CRC Computer Science & Data Analysis

USD$79.95

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Features

  • Takes readers through the stages of image analysis
  • Encompasses many new approaches for processing microarray images, including novel subgrid detection, feature identification, and graph-cutting techniques
  • Presents the details of the algorithmic processes along with an analysis of the processes performance over real-world microarray image data
  • Covers the strengths and weaknesses of each technique
  • Includes background material on microarray variants, basic transformations, clustering, gene expression data mining, and more

Summary

To harness the high-throughput potential of DNA microarray technology, it is crucial that the analysis stages of the process are decoupled from the requirements of operator assistance. Microarray Image Analysis: An Algorithmic Approach presents an automatic system for microarray image processing to make this decoupling a reality. The proposed system integrates and extends traditional analytical-based methods and custom-designed novel algorithms.

The book first explores a new technique that takes advantage of a multiview approach to image analysis and addresses the challenges of applying powerful traditional techniques, such as clustering, to full-scale microarray experiments. It then presents an effective feature identification approach, an innovative technique that renders highly detailed surface models, a new approach to subgrid detection, a novel technique for the background removal process, and a useful technique for removing "noise." The authors also develop an expectation–maximization (EM) algorithm for modeling gene regulatory networks from gene expression time series data. The final chapter describes the overall benefits of these techniques in the biological and computer sciences and reviews future research topics.

This book systematically brings together the fields of image processing, data analysis, and molecular biology to advance the state of the art in this important area. Although the text focuses on improving the processes involved in the analysis of microarray image data, the methods discussed can be applied to a broad range of medical and computer vision analysis areas.

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