Microarray data analysis : methods and applications / edited by Michael J. Korenberg. — Totowa, N.J. : Humana Press, c2007.—(58.17/M592/v.377)

Contents

    Contents
    
    Preface vi
    Contributors x
    1 Microarray Data Analysis: An Overview of Design， Methodology， and Analysis
    2 Genomic Signal Processing: From Matrix Algebra to Genetic Networks
    3 Online Analysis of Microarray Data Using Artificial Neural Networks
    4 Signal Processing and the Design of Microarray Time-Series Experiments
    5 Predictive Models of Gene Regulation: Application of Regression Methods to Microarray Data
    6 Statistical Framework for Gene Expression Data Analysis
    7 Gene Expression Profiles and Prognostic Markers for Primary Breast Cancer
    8 Comparing Microarray Studies
    9 A Pitfall in Series of Microarrays: The Position of Probes Affects the Cross-Correlation of Gene Expression Profiles
    10 In-Depth Query of Large Genomes Using Tiling Arrays
    11 Analysis of Comparative Genomic Hybridization Data on cDNA Microarrays
    12 Integrated High-Resolution Genome-Wide Analysis of Gene Dosage and Gene Expression in Human Brain Tumors
    13 Progression-Associated Genes in Astrocytoma Identified by Novel Microarray Gene Expression Data Reanalysis
    14 Interpreting Microarray Results With Gene Ontology and MeSH
    15 Incorporation of Gene Ontology Annotations to Enhance Microarray Data Analysis
    16 Predicting Survival in Follicular Lymphoma Using Tissue Microarrays