E-Book, Englisch, 240 Seiten
Speed Statistical Analysis of Gene Expression Microarray Data
Erscheinungsjahr 2003
ISBN: 978-1-135-44137-1
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
E-Book, Englisch, 240 Seiten
Reihe: Chapman & Hall/CRC Interdisciplinary Statistics
            ISBN: 978-1-135-44137-1 
            Verlag: Taylor & Francis
            
 Format: PDF
    Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies. And there is arguably no group better qualified to do so than the authors of this book.
Statistical Analysis of Gene Expression Microarray Data promises to become the definitive basic reference in the field. Under the editorship of Terry Speed, some of the world's most pre-eminent authorities have joined forces to present the tools, features, and problems associated with the analysis of genetic microarray data. These include:
- Model-based analysis of oligonucleotide arrays, including expression index computation, outlier detection, and standard error applications
- Design and analysis of comparative experiments involving microarrays, with focus on \ two-color cDNA or long oligonucleotide arrays on glass slides 
- Classification issues, including the statistical foundations of classification and an overview of different classifiers
- Clustering, partitioning, and hierarchical methods of analysis, including techniques related to principal components and singular value decomposition
Although the technologies used in large-scale, high throughput assays will continue to evolve, statistical analysis will remain a cornerstone of their success and future development. Statistical Analysis of Gene Expression Microarray Data will help you meet the challenges of large, complex datasets and contribute to new methodological and computational advances.
Zielgruppe
Biologists and researchers in genomics/biotechnology companies; statisticians in bioinformatics and statistical genetics; graduate students in computational genomics, computational biology, and bioinformatics; computer scientists working in computational biology; biomathematicians
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
MODEL-BASED ANALYSIS OF OLIGONUCLEOTIDE ARRAYS AND ISSUES IN cDNA MICROARRAY ANALYSIS, Cheng Li, George C. Tseng, and Wing Hung Wong
Model-Based Analysis of Oligonucleotide Arrays
Issues in cDNA Microarray Analysis 
Acknowledgments 
DESIGN AND ANALYSIS OF COMPARATIVE MICROARRAY EXPERIMENTS, Yee Hwa Yang and Terry Speed
Introduction 
Experimental Design 
Two-Sample Comparisons 
Single-Factor Experiments with more than Two Levels 
Factorial Experiments 
Some Topics for Further Research 
CLASSIFICATION IN MICROARRAY EXPERIMENTS, \ Sandrine Dudoit and Jane Fridlyand
Introduction 
Overview of Different Classifiers 
General Issues in Classification
Performance Assessment 
Aggregating Predictors 
Datasets 
Results 
Discussion 
Software and Datasets 
Acknowledgments 
CLUSTERING MICROARRAY DATA, Hugh Chipman, Trevor J. Hastie, and Robert Tibshirani
An Example 
Dissimilarity 
Clustering Methods 
Partitioning Methods 
Hierarchical Methods 
Two-Way Clustering 
Principal Components, the SVD, and Gene Shaving 
Other Approaches 
Software 
REFERENCES
INDEX





