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• Title:Microarrays for an integrative genomics / Isaac S. Kohane, Alvin T. Kho, and Atul J. Butte.
  
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• Author/Creator:Kohane, Isaac S.
  
• Other Contributors/Collections:Kho, Alvin T.
  Butte, Atul J.
  
• Published/Created:Cambridge, Mass. : MIT Press, ©2003.
  

• Holdings

  Holdings Record Display

  • Location:BMB LIBRARY (VGH) stacksWhere is this?
    
  • Call Number: QU58.5 .K63 2003
    
  • Number of Items:1
    
  • Status:Available
    

  • Location:WOODWARD LIBRARY stacksWhere is this?
    
  • Call Number: QU58.5 .K63 2003
    
  • Number of Items:1
    
  • Status:Available
    

   
• Library of Congress Subjects:DNA microarrays.
  Genomics--Automation.
  Bioinformatics.
  
• Description:xviii, 306 p. : ill. ; 24 cm.
  
• Series:Computational molecular biology series.
  
• Notes:"A Bradford book."
  Includes bibliographical references (pages [283]-295) and index.
  
• ISBN:026211271X (hc : alk. paper)
  
• Contents:1. Introduction
  1.1. Future Is So Bright ...
  1.2. Functional Genomics
  1.3. Missing the Forest for the Dendrograms
  1.4. Functional Genomics, Not Genetics
  1.5. Basic Biology
  2. Experimental Design
  2.1. Safe Conception of a Functional Genomic Experiment
  2.2. Gene-Clustering Dogma
  3. Microarray Measurements to Analyses
  3.1. Generic Features of Microarray Technologies
  3.2. Replicate Experiments, Reproducibility, and Noise
  3.3. Prototypical Objectives and Questions
  3.4. Preprocessing: Filters and Normalization
  3.5. Background on Fold
  3.6. Dissimilarity and Similarity Measures
  4. Genomic Data-Mining Techniques
  4.1. Introduction
  4.2. What Can Be Clustered in Functional Genomics?
  4.3. What Does it Mean to Cluster?
  4.4. Hierarchy of Bioinformatics Algorithms
  4.5. Data Reduction and Filtering
  4.6. Self-Organizing Maps
  4.7. Finding Genes That Split Sets
  4.8. Phylogenetic-Type Trees
  4.9. Relevance Networks
  4.10. Other Methods
  4.11. Which Technique Should I Use?
  4.12. Determining the Significance of Findings
  4.13. Genetic Networks
  5. Bio-Ontologies, Data Models, Nomenclature
  5.1. Ontologies
  5.2. Expressivity versus Computability
  5.3. Ontology versus Data Model versus Nomenclature
  5.4. Data Model Introduction
  5.5. Nomenclature
  5.6. Postanalysis Challenges
  6. From Functional Genomics to Clinical Relevance
  6.1. Electronic Medical Records
  6.2. Standardized Vocabularies for Clinical Phenotypes
  6.3. Privacy of Clinical Data
  6.4. Costs of Clinical Data Acquisition
  7. Near Future
  7.1. New Methods for Gene Expression Profiling
  7.2. Respecting the Older Generation
  7.3. Selecting Software
  7.4. Investing in the Future of the Genomic Enterprise.