Read Bioconductor Case Studies (Use R!) by Florian Hahne, Wolfgang Huber, Robert Gentleman, Seth Falcon Online
^ Bioconductor Case Studies (Use R!) ✓ PDF Read by ^ Florian Hahne, Wolfgang Huber, Robert Gentleman, Seth Falcon eBook or Kindle ePUB Online free. Bioconductor Case Studies (Use R!) Awful book, period! Quanticus I am loathe to write this review, but I feel compelled to. This is really an awful, awful book. There is no plan for the book in terms of trying to teach the reader the methods of analysis of Bioconductor in a structured way. All the chapters of the book seem like a patchwork which begin somewhere and end abruptly without any consistency. It is highly puzzling for me since the Bioconductor package seems to relatively well thought out overall. When it comes to writin
| Title | : | Bioconductor Case Studies (Use R!) |
| Author | : | |
| Rating | : | 4.24 (923 Votes) |
| Asin | : | 0387772391 |
| Format Type | : | paperback |
| Number of Pages | : | 284 Pages |
| Publish Date | : | 2014-09-27 |
| Language | : | English |
Awful book, period! Quanticus I am loathe to write this review, but I feel compelled to. This is really an awful, awful book. There is no plan for the book in terms of trying to teach the reader the methods of analysis of Bioconductor in a structured way. All the chapters of the book seem like a patchwork which begin somewhere and end abruptly without any consistency. It is highly puzzling for me since the Bioconductor package seems to relatively well thought out overall. When it comes to writing books, all the authors associated with the Bioconductor seem to abrupt
Topics covered include: (1) import and preprocessing of data from various sources; (2) statistical modeling of differential gene expression; (3) biological metadata; (4) application of graphs and graph rendering; (5) machine learning for clustering and classification problems; (6) gene set enrichment analysis.Each chapter of this book describes an analysis of real data using hands-on example driven approaches. The book is a dynamic document. Its application spans a broad field of technologies used in contemporary molecular biology. Short exercises help in the learning process and invite more advanced considerations of key topics. In this volume, the authors present a collection of cases to apply Bioconductor tools in the analysis of microarray gene expression data. Bioconductor software has become a standard tool for the analysis and comprehension of data from high-throughput genomics experiments. All the code shown can be executed on a local computer, and readers are able to reproduce every computation, figure, and table.
…All in all, this text is an excellent, well-written reference for many of the common tasks that arise during the analysis of microarray gene expression datasets, as implemented by Bioconductor. … All the code, including solutions to the exercises, is available for downloading on the Web and-this is well worth mentioning-it runs straight out of the box…. In particular the interpretation of the results of clustering is more sensible then you often see…. The discussion of analysis is generally sound and practical. This book is strongly recommended for learning more about Bioconductor." (Antony Unwin, Journal of Statistical Software, January 2009,
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