Microarrays for an Integrative Genomics (Paperback)

Isaac S. Kohane, Alvin Kho, Atul J. Butte

  • 出版商: A Bradford Book
  • 出版日期: 2005-08-12
  • 定價: $775
  • 售價: 3.9$299
  • 語言: 英文
  • 頁數: 326
  • 裝訂: Paperback
  • ISBN: 0262612100
  • ISBN-13: 9780262612104

立即出貨 (庫存 < 4)

買這商品的人也買了...

商品描述

Description:

Functional genomics--the deconstruction of the genome to determine the biological function of genes and gene interactions--is one of the most fruitful new areas of biology. The growing use of DNA microarrays allows researchers to assess the expression of tens of thousands of genes at a time. This quantitative change has led to qualitative progress in our ability to understand regulatory processes at the cellular level.

This book provides a systematic introduction to the use of DNA microarrays as an investigative tool for functional genomics. The presentation is appropriate for readers from biology or bioinformatics. After presenting a framework for the design of microarray-driven functional genomics experiments, the book discusses the foundations for analyzing microarray data sets, genomic data-mining, the creation of standardized nomenclature and data models, clinical applications of functional genomics research, and the future of functional genomics.

Isaac S. Kohane is Director of the Children’s Hospital Informatics Program, Associate Professor of Pediatrics at Harvard Medical School, and an Attending Physician in Endocrinology at Children's Hospital, Boston.

Alvin Kho is Research Fellow in Medicine at Children's Hospital, Boston.

Atul J. Butte is a Staff Informatician in the Children's Hospital Informatics Program, an Instructor in Pediatrics at Harvard Medical School, and an Attending Physician in Endocrinology at Children's Hospital, Boston.

 

Table of Contents:

Foreword xi
Preface xiii
Acknowledgments xvii
1 Introduction 1
1.1 The Future Is So Bright... 1
1.2 Functional Genomics 4
1.3 Missing the Forest for the Dendrograms 13
1.4 Functional Genomics, Not Genetics 19
1.5 Basic Biology 25
2 Experimental Design 37
2.1 The Safe Conception of a Functional Genomic Experiment 37
2.2 Gene-Clustering Dogma 60
3 Microarray Measurements to Analyses 69
3.1 Generic Features of Microarray Technologies 69
3.2 Replicate Experiments, Reproducibility, and Noise 88
3.3 Prototypical Objectives and Questions 116
3.4 Preprocessing: Filters and Normalization 121
3.5 Background on Fold 127
3.6 Dissimilarity and Similarity Measures 137
4 Genomic Data-Mining Techniques 149
4.1 Introduction 149
4.2 What Can Be Clustered in Functional Genomics? 149
4.3 What Does it Mean to Cluster? 150
4.4 Hierarchy of Bioinformatics Algorithms 151
4.5 Data Reduction and Filtering 155
4.6 Self-Organizing Maps 161
4.7 Finding Genes That Split Sets 169
4.8 Phylogenetic-Type Trees 172
4.9 Relevance Networks 181
4.10 Other Methods 189
4.11 Which Technique Should I Use? 191
4.12 Determining the Significance of Findings 195
4.13 Genetic Networks 203
5 Bio-Ontologies, Data Models, Nomenclature 215
5.1 Ontologies 216
5.2 Expressivity versus Computability 224
5.3 Ontology versus Data Model versus Nomenclature 226
5.4 Data Model Introduction 231
5.5 Nomenclature 239
5.6 Postanalysis Challenges 247
6 From Functional Genomics to Clinical Relevance 249
6.1 Electronic Medical Records 249
6.2 Standardized Vocabularies for Clinical Phenotypes 251
6.3 Privacy of Clinical Data 252
6.4 Costs of Clinical Data Acquisition 256
7 The Near Future 257
7.1 New Methods for Gene Expression Profiling 257
7.2 Respecting the Older Generation 266
7.3 Selecting Software 271
7.4 Investing in the Future of the Genomic Enterprise 273
Glossary 277
References 283
Index 296