Exploration and Analysis of DNA Microarray and Other High-Dimensional Data
β Scribed by Dhammika Amaratunga, Javier Cabrera, Ziv Shkedy
- Publisher
- Wiley
- Year
- 2014
- Tongue
- English
- Leaves
- 346
- Series
- Wiley Series in Probability and Statistics
- Edition
- 2
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Praise for the First Edition
ββ¦extremely well writtenβ¦a comprehensive and up-to-date overview of this important field.β β Journal of Environmental Quality
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Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent advancements in microarray data analysis. A cutting-edge guide, the Second Edition demonstrates various methodologies for analyzing data in biomedical research and offers an overview of the modern techniques used in microarray technology to study patterns of gene activity.
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The new edition answers the need for an efficient outline of all phases of this revolutionary analytical technique, from preprocessing to the analysis stage. Utilizing research and experience from highly-qualified authors in fields of data analysis, Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition features:
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- A new chapter on the interpretation of findings that includes a discussion of signatures and material on gene set analysis, including network analysis
- New topics of coverage including ABC clustering, biclustering, partial least squares, penalized methods, ensemble methods, and enriched ensemble methods
- Updated exercises to deepen knowledge of the presented material and provide readers with resources for further study
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The book is an ideal reference for scientists in biomedical and genomics research fields who analyze DNA microarrays and protein array data, as well as statisticians and bioinformatics practitioners. Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition is also a useful text for graduate-level courses on statistics, computational biology, and bioinformatics.
π SIMILAR VOLUMES
This book provides an excellent overview of various methods in DNA microarray analysis. It explains most of the theories behind the algorithms, so that you know why the analyses are done in certain way. In fact, I find I get more insights from the book as compare to the research papers which tend
<p>This book shows how to decompose high-dimensional microarrays into small subspaces (Small Matryoshkas, SMs), statistically analyze them, and perform cancer gene diagnosis. The information is useful for genetic experts, anyone who analyzes genetic data, and students to use as practical textbooks.<
A cutting-edge guide to the analysis of DNA microarray dataGenomics is one of the major scientific revolutions of this century, and the use of microarrays to rapidly analyze numerous DNA samples has enabled scientists to make sense of mountains of genomic data through statistical analysis. Today, mi
Big data poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. Th