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Other titles in the Chapman & Hall/CRC Computer Science & Data Analysis series:
Chapman & Hall/CRC Computer Science & Data Analysis #16: Microarray Image Analysis: An Algorithmic Approachby Karl Fraser
Synopses & Reviews
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.
Book News Annotation:
This resource for microarray researchers and computer scientists brings together the fields of image processing, data analysis, and molecular biology. Rather than focusing on image creation, the book walks through stages of microarray image analysis. An automatic system for microarray image processing is proposed, integrating and extending traditional analytical-based methods and custom-designed novel algorithms. Techniques covered can be applied to other medical and computer vision analysis areas as well. After a chapter of background on molecular biology, microarray technologies, and microarray analysis, the book covers data services structure extrapolation, feature identification, chained Fourier reconstruction, graph-cutting, and stochastic dynamic modeling of short gene expression time series data. About 20 pages of technical appendices are provided. Fraser is affiliated with Brunel University, UK Annotation ©2010 Book News, Inc., Portland, OR (booknews.com)
As no experiment can be successful without good data produced at the first stage, microarray image analysis is a key for high-throughput bioinformatics technologies. However, it has received relatively little attention. This book, the first to focus on this topic, provides an in-depth technical guide to the creation of algorithms for an automated approach to DNA microarray image analysis. The initial chapters provide biological and image analysis background, while the later chapters focus on specific areas of the image analysis process: image transformations, structure extrapolation, and feature identification. Concepts are illustrated throughout by examples relying on real bioinformatics data.
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Science and Mathematics » Biology » General