1st Edition

Microarray Image Analysis An Algorithmic Approach

By Karl Fraser, Zidong Wang, Xiaohui Liu Copyright 2010
    336 Pages 134 B/W Illustrations
    by Chapman & Hall

    336 Pages 134 B/W Illustrations
    by Chapman & Hall

    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.

    Introduction
    Overview
    Current state of art
    Experimental approach
    Key issues
    Contribution to knowledge
    Structure of the book

    Background
    Introduction
    Molecular biology
    Microarray technology
    Microarray analysis
    Copasetic microarray analysis framework overview
    Summary

    Data Services
    Introduction
    Image transformation engine
    Evaluation
    Summary

    Structure Extrapolation I
    Introduction
    Pyramidic contextual clustering
    Evaluation
    Summary

    Structure Extrapolation II
    Introduction
    Image layout—master blocks
    Image structure—meta-blocks
    Summary

    Feature Identification I
    Introduction
    Spatial binding
    Evaluation of feature identification
    Evaluation of copasetic microarray analysis framework
    Summary

    Feature Identification II
    Background
    Proposed approach—subgrid detection
    Experimental results
    Conclusions

    Chained Fourier Background Reconstruction
    Introduction
    Existing techniques
    A new technique
    Experiments and results
    Conclusions

    Graph-Cutting for Improving Microarray Gene Expression
    Reconstructions
    Introduction
    Existing techniques
    Proposed technique
    Experiments and results
    Conclusions

    Stochastic Dynamic Modeling of Short Gene Expression Time Series Data
    Introduction
    Stochastic dynamic model for gene expression data
    An EM algorithm for parameter identification
    Simulation results
    Discussions
    Conclusions and future work

    Conclusions
    Introduction
    Achievements
    Contributions to microarray biology domain
    Contributions to computer science domain
    Future research topics

    Appendix A: Microarray Variants
    Appendix B: Basic Transformations
    Appendix C: Clustering
    Appendix D: A Glance on Mining Gene Expression Data
    Appendix E: Autocorrelation and GHT

    References

    Biography

    Karl Fraser is a research fellow in the Centre for Intelligent Data Analysis at Brunel University.

    Zidong Wang is a professor of dynamical systems and computing in the Department of Information Systems and Computing at Brunel University.

    Xiaohu Liu is a professor of computing and head of the Centre for Intelligent Data Analysis at Brunel University.

    Overall, this is a well-written book, and it should be useful for researchers and practitioners who work on microarray image analysis.
    —Peihua Qiu, Technometrics, May 2012