| View Larger Image | DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments (Biostatistics) | Hardcoverby David B. Allison (Editor), Grier P. Page (Editor), T. Mark Beasley (Editor), Jode W. Edwards (Editor)
| List Price: | $93.95 | | Price: | $81.00 | | You Save: | $12.95 (14%) | | | Available: | Usually ships in 24 hours |
| | Binding: | Hardcover | | Publisher: | Chapman & Hall/CRC | | Edition: | 1st Edition | | Page Count: | 392 Pages | | Publication Date: | November 14, 2005 | | Sales Rank: | 1,222,166st |
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ACCESSORIES |
| Data Analysis Tools for DNA Microarrays
by Sorin Draghici (Author)
Technology today allows the collection of biological information at an unprecedented level of detail and in increasingly vast quantities. To reap real knowledge from the mountains of data produced, however, requires interdisciplinary skills-a background not only in biology but also in computer science and the tools and techniques of data analysis.To help meet the challenges of DNA research, Data Analysis Tools for DNA Microarrays builds the foundation in the statistics and data analysis tools...
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| Statistical Analysis of Gene Expression Microarray Data
by Terry Speed (Editor)
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. And there is arguably no group better qualified to do so than the authors of this book.Statistical Analysis of Gene Expression Microarray Data...
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| Knowledge Discovery in Proteomics (Chapman & Hall/ Crc Mathematical Biology and Medicine)
by Igor Jurisica (Author), Dennis Wigle (Author)
Knowledge Discovery in High-Throughput Biological Domains describes the challenges in high-throughput biology areas and emerging computational approaches for representation, integration and organization, analysis, and interpretation of this data with the overall goal of producing and managing new knowledge. The authors provide systematic management tools for high-dimensional data in high-throughput biology, discuss systems biology and integrative computation biology, and describe...
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EDITORIAL REVIEWS |
Product Description
Considered highly exotic tools as recently as the late 1990s, microarrays are now ubiquitous in biological research. Traditional statistical approaches to design and analysis were not developed to handle the high-dimensional, small sample problems posed by microarrays. In just a few short years the number of statistical papers providing approaches to analyzing microarray data has gone from almost none to hundreds if not thousands. This overwhelming deluge is quite daunting to either the applied investigator looking for methodologies or the methodologist trying to keep up with the field. DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments consolidates discussions of methodological advances into a single volume. The book’s structure parallels the steps an investigator or an analyst takes when conducting and analyzing a microarray experiment from conception to interpretation. It begins with foundational issues such as ensuring the quality and integrity of the data and assessing the validity of the statistical models employed, then moves on to cover critical aspects of designing a microarray experiment. The book includes discussions of power and sample size, where only very recently have developments allowed such calculations in a high dimensional context, followed by several chapters covering the analysis of microarray data. The amount of space devoted to this topic reflects both the variety of topics and the effort investigators have devoted to developing new methodologies. In closing, the book explores the intellectual frontier – interpretation of microarray data. It discusses new methods for facilitating and affecting formalization of the interpretation process and the movement to make large high dimensional datasets public for further analysis, and methods for doing so. There is no question that this field will continue to advance rapidly and some of the specific methodologies discussed in this book will be replaced by new advances. Nevertheless, the field is now at a point where a foundation of key categories of methods has been laid out and begun to settle. Although the details may change, the majority of the principles described in this book and the foundational categories it contains will stand the test of time, making the book a touchstone for researchers in this field. |
CUSTOMER REVIEWS (Average Customer Rating: 5.0 based on 1 review)
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Exquisite coverage of existing & developing methodologies by Elliot Kleiman (San Diego, CA United States)  5 Stars
December 06, 2006
An expansive tour of existing statistical methodologies used in microarray data analysis from contributed experts. What it does is deeply explore what people are using nowadays, cites references in each chapter beautifully, and gives the reader a solid footing as to the pros and cons of each technique presented. Each chapter delves deep enough, and by citing references extensively, one can go seek further detail from the source.
IMHO, this is probably one of the most professionally done books out there. By that I mean there is no fluff, just high quality content across the board. The intended audience is those having some computational background, particularly in statistics. However, each chapter begins with an introductory paragraph serving as a review so that anyone could pretty much gather what is going to be discussed.
A really nice feature of this compilation is that not only does it provide insight into the current methods, it outlines where further developments are needed and how they may help in filling in the gaps. With so many developments having been made in microarray data analysis recently, its nice to know that this book exists to help one gain a solid foundation on how to proceed with some sort of clarity. A five star rating for this one hands down. :)
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SIMILAR PRODUCTS |
| Microarray Gene Expression Data Analysis: A Beginner's Guide
by Helen Causton (Author), John Quackenbush (Author), Alvis Brazma (Author)
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...
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| Lattice: Multivariate Data Visualization with R (Use R)
by Deepayan Sarkar (Author)
R is rapidly growing in popularity as the environment of choice for data analysis and graphics both in academia and industry. Lattice brings the proven design of Trellis graphics (originally developed for S by William S. Cleveland and colleagues at Bell Labs) to R, considerably expanding its capabilities in the process. Lattice is a powerful and elegant high level data visualization system that is sufficient for most everyday graphics needs, yet flexible enough to be easily extended to handle...
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| Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health)
by Robert Gentleman (Editor), Vincent Carey (Editor), Wolfgang Huber (Editor), Rafael Irizarry (Editor), Sandrine Dudoit (Editor)
Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R. This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including importation and preprocessing of high-throughput data from microarray, proteomic, and...
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| Bioconductor Case Studies (Use R)
by Florian Hahne (Author), Wolfgang Huber (Author), Robert Gentleman (Author), Seth Falcon (Author)
Bioconductor software has become a standard tool for the analysis and comprehension of data from high-throughput genomics experiments. Its application spans a broad field of technologies used in contemporary molecular biology. In this volume, the authors present a collection of cases to apply Bioconductor tools in the analysis of microarray gene expression data. Topics covered include * import and preprocessing of data from various sources * statistical modeling of...
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| Introductory Statistics with R (Statistics and Computing)
by Peter Dalgaard (Author)
R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development. This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and...
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