Analyzing Microarray Gene Expression Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Analyzing Microarray Gene Expression Data write by Geoffrey J. McLachlan. This book was released on 2005-02-18. Analyzing Microarray Gene Expression Data available in PDF, EPUB and Kindle. A multi-discipline, hands-on guide to microarray analysis of biological processes Analyzing 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 the field of microarray analysis as well as biologists seeking to more effectively analyze their own experimental data, the text features a unique interdisciplinary approach and a combined academic and practical perspective that offers readers the most complete and applied coverage of the subject matter to date. Following a basic overview of the biological and technical principles behind microarray experimentation, the text provides a look at some of the most effective tools and procedures for achieving optimum reliability and reproducibility of research results, including: An in-depth account of the detection of genes that are differentially expressed across a number of classes of tissues Extensive coverage of both cluster analysis and discriminant analysis of microarray data and the growing applications of both methodologies A model-based approach to cluster analysis, with emphasis on the use of the EMMIX-GENE procedure for the clustering of tissue samples The latest data cleaning and normalization procedures The uses of microarray expression data for providing important prognostic information on the outcome of disease
Analysis of Microarray Gene Expression Data
Analysis of Microarray Gene Expression Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Analysis of Microarray Gene Expression Data write by Mei-Ling Ting Lee. This book was released on 2007-05-08. Analysis of Microarray Gene Expression Data available in PDF, EPUB and Kindle. After genomic sequencing, microarray technology has emerged as a widely used platform for genomic studies in the life sciences. Microarray technology provides a systematic way to survey DNA and RNA variation. With the abundance of data produced from microarray studies, however, the ultimate impact of the studies on biology will depend heavily on data mining and statistical analysis. The contribution of this book is to provide readers with an integrated presentation of various topics on analyzing microarray data.
Microarray Gene Expression Data Analysis
Microarray Gene Expression Data Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Microarray Gene Expression Data Analysis write by Helen Causton. This book was released on 2009-04-01. Microarray Gene Expression Data Analysis available in PDF, EPUB and Kindle. 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 mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays
Statistical Analysis of Gene Expression Microarray Data
Statistical Analysis of Gene Expression Microarray Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Analysis of Gene Expression Microarray Data write by Terry Speed. This book was released on 2003-03-26. Statistical Analysis of Gene Expression Microarray Data available in PDF, EPUB and Kindle. 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
Methods of Microarray Data Analysis
Methods of Microarray Data Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Methods of Microarray Data Analysis write by Simon M. Lin. This book was released on 2012-12-06. Methods of Microarray Data Analysis available in PDF, EPUB and Kindle. Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis is one of the first books dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods ranging from data normalization, feature selection and discriminative analysis to machine learning techniques. Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis focuses on two well-known data sets, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformatics/genomics courses in undergraduate and graduate programs.
