The Analysis of Gene Expression Data

Description

This book presents practical approaches for the analysis of data from gene expression microarrays. Each chapter describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. Methods cover all aspects of statistical analysis of microarrays, from annotation and filtering to clustering and classification. Chapters are written by the developers of the software. All software packages described are free to academic users. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences. Some chapters describe simple menu-driven software in a user-friendly fashion, and are designed to be accessible to microarray data analysts without formal quantitative training. Most chapters are directed at microarray data analysts with master-level training in computer science, biostatistics or bioinformatics. A minority of more advanced chapters are intended for doctoral students and researchers. The team of editors is from the Johns Hopkins Schools of Medicine and Public Health and has been involved with developing methods and software for microarray data analysis since the inception of this technology. Giovanni Parmigiani is Associate Professor of Oncology, Pathology and Biostatistics. He is the author of the book on "Modeling in Medical decision Making," a fellow of the ASA, and a recipient of the Savage Awards for Bayesian statistics. Elizabeth S. Garrett is Assistant Professor of Oncology and Biostatistics, and recipient of the Abbey Award for statistical education. Rafael A Irizarry is Assistant Professor of Biostatistics, and recipient of the Noether Award for non-parametric statistics. Scott L. Zeger is Professor and chair of Biostatistics. He is co-author of the book "Longitudinal Data Analysis," a fellow of the ASA and recipient of the Spiegelman Award for public health statistics.

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1. Ebooks list page : 1581
2. Microarray Gene Expression Data Analysis
3. Advanced Analysis of Gene Expression Microarray Data (2006)
4. Analysis of Microarray Gene Expression Data (Trends in Logic S.)
5. Bayesian Analysis of Gene Expression Data (Statistics in Practice)
6. DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling
7. Statistical Analysis of Gene Expression Microarray Data by Terry Speed
8. Statistical Analysis of Gene Expression Microarray Data by Terry Speed
9. Advanced Analysis of Gene Expression Microarray Data (Science, Engineering, and Biology Informatics)
10. Analyzing Microarray Gene Expression Data
11. Analyzing Microarray Gene Expression Data (2004)
12. Gene Expression Systems: Using Nature for the Art of Expression (1999)
13. Serial Analysis of Gene Expression (SAGE): Methods and Protocols (Methods in Molecular Biology Volume 387)
14. Analysing Gene Expression
15. Gene Expression and Regulation
16. Gene Expression Technology