Statistical analysis of gene expression microarray data
β Scribed by Terry Speed
- Publisher
- Chapman & Hall/CRC
- Year
- 2003
- Tongue
- English
- Leaves
- 218
- Series
- Interdisciplinary statistics
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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
β¦ Subjects
ΠΠΈΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄ΠΈΡΡΠΈΠΏΠ»ΠΈΠ½Ρ;ΠΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½Π°Ρ Π±ΠΈΠΎΠ»ΠΎΠ³ΠΈΡ;Methods in Molecular Biology;
π SIMILAR VOLUMES
This guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathemati
This book is very well written, in great detail and clarity. The title "Advanced" sounds daunting to some intermediate or entry level statisticians, but the math details in the book is very understandable, presented as necessary support in order to understand the explained statistical methods. I wo
mphasizing underlying concepts and principles, this concise guide describes the design of microarray experiments and the analysis of the data they produce. Intended for graduate students and bioinformatics researchers, the book stresses the conceptual aspects of analysis and keeps mathematical compl
McLachlan is a very well-known statistician who specializes in classification, pattern recognition and mixture distribution models. I was surprised to see him write a book on microarray data. But I shouldn't have been. It turns out that in addition to data processing and statistical design, clust
A multi-discipline, hands-on guide to microarray analysis of biological processesAnalyzing Microarray Gene Expression Data provides a comprehensive review of available methodologies for the analysis of data derived from the latest DNA microarray technologies. Designed for biostatisticians entering t