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Computational and Statistical Approaches to Genomics

  • Book
  • © 2006

Overview

Editors:
  1. Wei Zhang

    1. M.D. Anderson Cancer Center, University of Texas, USA

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  2. Ilya Shmulevich

    1. Institute for Systems Biology, Seattle

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  • Contains the newest research results on genomic analysis and modeling using state-of-the-art methods from engineering, statistics, and genomics
  • Involves the application of these tools and models to real biological and clinical problems
  • Provides new initiatives and directions for industry leaders in genomics

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Table of contents (18 chapters)

  1. Front Matter

    Pages i-ix
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  2. Microarray Image Analysis and Gene Expression Ratio Statistics

    • Yidong Chen, Edward R. Dougherty, Michael L. Bittner, Paul Meltzer, Jeffery Trent
    Pages 1-19

  3. Statistical Considerations in the Assessment of cDNA Microarray Data Obtained Using Amplification

    • Jing Wang, Kevin R. Coombes, Keith Baggerly, Limei Hu, Stanley R. Hamilton, Wei Zhang
    Pages 21-36

  4. Sources of Variation in Microarray Experiments

    • Kathleen F. Kerr, Edward H. Leiter, Laurent Picard, Gary A. Churchill
    Pages 37-47

  5. Studentizing Microarray Data

    • Keith A. Baggerly, Kevin R. Coombes, Kenneth R. Hess, David N. Stivers, Lynne V. Abruzzo, Wei Zhang
    Pages 49-59

  6. Exploratory Clustering of Gene Expression Profiles of Mutated Yeast Strains

    • Merja Oja, Janne Nikkilä, Petri Törönen, Garry Wong, Eero Castrén, Samuel Kaski
    Pages 61-74

  7. Selecting Informative Genes for Cancer Classification Using Gene Expression Data

    • Tatsuya Akutsu, Satoru Miyano
    Pages 75-88

  8. Finding Functional Structures in Ggioma Gene-Expressions Using Gene Shaving Clustering and MDL Principle

    • Ciprian D. Giurcaneanu, Cristian Mircean, Gregory N. Fuller, Ioan Tabus
    Pages 89-118

  9. Design Issues and Comparison of Methods for Microarray-Based Classification

    • Edward R. Dougherty, Sanju N. Attoor
    Pages 119-136

  10. Analyzing Protein Sequences Using Signal Analysis Techniques

    • Karen M. Bloch, Gonzalo R. Arce
    Pages 137-161

  11. Scale-Dependent Statistics of the Numbers of Transcripts and Protein Sequences Encoded in the Genome

    • Vladimir A. Kuznetsov
    Pages 163-208

  12. Statistical Methods in Serial Analysis of Gene Expression (Sage)

    • Ricardo Z. N. Vêncio, Helena Brentani
    Pages 209-233

  13. Normalized Maximum Likelihood Models for Boolean Regression with Application to Prediction and Classification in Genomics

    • Ioan Tabus, Jorma Rissanen, Jaakko Astola
    Pages 235-258

  14. Inference of Genetic Regulatory Networks via Best-Fit Extensions

    • Harri Lähdesmäki, Ilya Shmulevich, Olli Yli-Harja, Jaakko Astola
    Pages 259-278

  15. Regularization and Noise Injection for Improving Genetic Network Models

    • Eugene van Someren, Lodewyk Wessels, Marcel Reinders, Eric Backer
    Pages 279-295

  16. Parallel Computation and Visualization Tools for Codetermination Analysis of Multivariate Gene Expression Relations

    • Edward B. Suh, Edward R. Dougherty, Seungchan Kim, Michael L. Bittner, Yidong Chen, Daniel E. Russ et al.
    Pages 297-310

  17. Single Nucleotide Polymorphisms and Their Applications

    • Rudy Guerra, Zhaoxia Yu
    Pages 311-349

  18. The Contribution of Alternative Transcription and Alternative Splicing to the Complexity of Mammalian Transcriptomes

    • Mihaela Zavolan, Christian Schönbach
    Pages 351-380

  19. Computational Imaging, and Statistical Analysis of Tissue Microarrays: Quantitative Automated Analysis of Tissue Microarrays

    • Aaron J. Berger, Robert L. Camp, David L. Rimm
    Pages 381-403

  20. Back Matter

    Pages 405-416
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Keywords

About this book

The 2nd edition of this book adds 8 new contributors to reflect a modern cutting edge approach to genomics. The expanded scope includes coverage of statistical issues on single nucleotide polymorphism analysis array, CGH analysis, SAGE analysis, gene shaving and related methods for microarray data analysis, and cross-hybridization issues on oligo arrays. The authors of the 17 original chapters have updated the contents of their chapters, including references, on such topics as the development of novel engineering, statistical and computational principles, as well as methods, models, and tools from these disciplines applied to genomics.

Editors and Affiliations

  • M.D. Anderson Cancer Center, University of Texas, USA

    Wei Zhang

  • Institute for Systems Biology, Seattle

    Ilya Shmulevich

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