Read Statistical Analysis of Gene Expression Microarray Data by Terry Speed Online
Read [Terry Speed Book] ^ Statistical Analysis of Gene Expression Microarray Data Online ! PDF eBook or Kindle ePUB free. Statistical Analysis of Gene Expression Microarray Data wiredweird said Outstanding survey. Microarray studies are becoming the preferred research tools in many areas, including cancer research, development studies, and studies in organisms' responses to their environments. Because of differences between organisms or between experiments, microarray data is always statistical in nature. The problem is that the data aren't well suited to traditional statistics. Instead of studying a few characteristics in large numbers of individuals, microarray studie
| Title | : | Statistical Analysis of Gene Expression Microarray Data |
| Author | : | |
| Rating | : | 4.50 (935 Votes) |
| Asin | : | 1584883278 |
| Format Type | : | paperback |
| Number of Pages | : | 240 Pages |
| Publish Date | : | 2013-08-26 |
| Language | : | English |
wiredweird said Outstanding survey. Microarray studies are becoming the preferred research tools in many areas, including cancer research, development studies, and studies in organisms' responses to their environments. Because of differences between organisms or between experiments, microarray data is always statistical in nature. The problem is that the data aren't well suited to traditional statistics. Instead of studying a few characteristics in large numbers of individuals, microarray studies typically yield thousands of data values for a few dozen samples.That mismatch, bet. "the wave of the future" according to Michael R. Chernick. This book looks like a text on statistical methods in microarray data edited and contributed by Terry Speed a leading researcher in the field from the Berkeley California Statistics department. There are several contributors to the book include Hastie and Tibshirani from Stanford and Tseng and Wong from Harvard. These are some of the top academic biostatisticians in the world who are currently heavily involved in microarray research.Usually I write the first amazon review on books like this. But this book has been out since 200the wave of the future This book looks like a text on statistical methods in microarray data edited and contributed by Terry Speed a leading researcher in the field from the Berkeley California Statistics department. There are several contributors to the book include Hastie and Tibshirani from Stanford and Tseng and Wong from Harvard. These are some of the top academic biostatisticians in the world who are currently heavily involved in microarray research.Usually I write the first amazon review on books like this. But this book has been out since 2003 and so my frie. and so my frie. "Excellent book for data analyst" according to Xiwei Wu. Thorough converage of statistics involved in microarray data analysis. It presents important knowledge for biologists who use data analysis tools but would like to know what is behind the scene. Understanding the book needs some statistical background and hence not a easy book for biologists and genetists who do not have that knowledge.I would like to emphasize that experiment design issue is presented in a very clear way and should be read by all who plan to start project related to gene expression. Clustering and classification are two major
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. 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. These include::Model-based analysis of oligonucleotide arrays, including expression index computation, outlier d
157 (3) "Analysis for gene expression data is the latest hot new topic in statistical data analysisthis book deals with microarray experiments: design and analysis for a comparative study, classification methods for data analysis, and clustering for data analysis. "The 10 authors are among the world's authorities on the statistical analysis of this new class of biotechnology . Scientists whose work concerns this type of data will want to get a copy of the book." -Technometrics, 2003 "This book is a milestone, documenting major significant advances in the statistical methodology. I highly recommend this book for library purchase, and for individuals in the field ." - Journal of the Royal Statistical Society, Series A, Vol. The statistical ideas are introduced succinctly. The four chapters, though independent, share common foci with issues of design, robustness, and the freely available associated software. The book is especially valuable for research scientists in the field seek
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