Data analysis tools for DNA microarrays
著者
書誌事項
Data analysis tools for DNA microarrays
(Chapman & Hall/CRC mathematical biology & medicine series)
Chapman & Hall/CRC, c2003
大学図書館所蔵 全5件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
2 computer disk in pocket
Includes bibliographical references and index
内容説明・目次
内容説明
Technology today allows the collection of biological information at an unprecedented level of detail and in increasingly vast quantities. To reap real knowledge from the mountains of data produced, however, requires interdisciplinary skills-a background not only in biology but also in computer science and the tools and techniques of data analysis.
To help meet the challenges of DNA research, Data Analysis Tools for DNA Microarrays builds the foundation in the statistics and data analysis tools needed by biologists and provides the overview of microarrays needed by computer scientists. It first presents the basics of microarray technology and more importantly, the specific problems the technology poses from the data analysis perspective. It then introduces the fundamentals of statistics and the details of the techniques most commonly used to analyze microarray data. The final chapter focuses on commercial applications with sections exploring various software packages from BioDiscovery, Insightful, SAS, and Spotfire. The book is richly illustrated with more than 230 figures in full color and comes with a CD-ROM containing full-feature trial versions of software for image analysis (ImaGene, BioDiscovery Inc.) and data analysis (GeneSight, BioDiscovery Inc. and S-Plus Array Analyzer, Insightful Inc.).
Written in simple language and illustrated in full color, Data Analysis Tools for DNA Microarrays lowers the communication barrier between life scientists and analytical scientists. It prepares those charged with analyzing microarray data to make informed choices about the techniques to use in a given situation and contribute to further advances in the field.
目次
PREFACE
INTRODUCTION
Bioinformatics - An Emerging Discipline
The Building Blocks of Genomic Information
Expression of Genetic Information
The Need for Microarrays
MICROARRAYS
Microarrays - Tools for Gene Expression Analysis
Fabrication of Microarrays
Applications of Microarrays
Challenges in Using Microarrays in Gene Expression Studies
Sources of Variability
IMAGE PROCESSING
Introduction
Basic Elements of Digital Imaging
Microarray Image Processing
Image Processing of cDNA Microarrays
Image Processing of Affymetrix Microarrrays
ELEMENTS OF STATISTICS
Introduction
Some Basic Terms
Elementary Statistics
Probabilities
Bayes' Theorem
Probability Distributions
Central Limit Theorem
Are Replicates Useful?
Summary
Solved Problems
Exercises
STATISTICAL HYPOTHESIS TESTING
Introduction
The framework
Hypothesis Testing and Significance
"I Do Not Believe God Does Not Exist"
An Algorithm for Hypothesis Testing
Errors in Hypothesis Testing
Solved Problems
CLASSICAL APPROACHES TO DATA ANALYSIS
Introduction
Tests Involving a Single Sample
Tests Involving Two Samples
Exercises
ANALYSIS OF VARIANCE - ANOVA
Introduction
One-Way ANOVA
Two-Way ANOVA
Quality Control
Exercises
EXPERIMENT DESIGN
The Concept of Experiment Design
Comparing Varieties
Improving the Production Process
Principles of Experimental Design
Guidelines for Experimental Design
A Short Synthesis of Statistical Experiment Designs
Some Microarray Specific Experiment Designs
MULTIPLE COMPARISONS
Introduction
The Problem of Multiple Comparisons
A More Precise Argument
Corrections for Multiple Comparisons
ANALYSIS AND VISUALIZATION TOOLS
Introduction
Box Plots
Gene Pies
Scatter Plots
Histograms
Time Series
Principal Component Analysis (PCA)
Independent Component Analysis (ICA)
CLUSTER ANALYSIS
Introduction
Metric Distances
Hierarchical Clustering
k-Means Clustering
Kohonen Maps (SOFM)
DATA PRE-PROCESSING AND NORMALIZATION
Introduction
General Pre-Processing Techniques
Normalization Issues Specific to cDNA Data
Normalization Issues Specific to Affymetrix Data
Other Approaches to the Normalization of Affymetrix Data
Useful Pre-Processing and Normalization Sequences
Appendix
METHODS FOR SELECTING DIFFERENTIALLY REGULATED GENES
Introduction
Criteria
Fold Change
Unusual Ratio
Hypothesis Testing, Corrections for Multiple Comparisons and Resampling
ANOVA
Noise Sampling
Model Based Maximum Likelihood Estimation Methods
Affymetrix Comparison Calls
Other Methods
Appendix
FUNCTIONAL ANALYSIS AND BIOLOGICAL INTERPRETATION OF MICROARRAY DATA
Introduction
The Gene Ontology
Other Related Resources
Translating Lists of Differentially Regulated Genes into Biological Knowledge
Onto-Express
Summary
FOCUSED MICROARRAYS - COMPARISON AND SELECTION
Introduction
Criteria for Array Selection
Onto-Compare
Some Comparisons
COMMERCIAL APPLICATIONS
Introduction
Significance Testing Among Groups Using GeneSight
Statistical Analysis of Microarray Data Using S-PLUS and Insightful ArrayAnalyzer
SAS Software for Genomics
Spofire's Decision Site
THE ROAD AHEAD
What Next?
Molecular Diagnosis
Gene Regulatory Networks
Conclusions
REFERENCES
「Nielsen BookData」 より