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	Cancer Epigenetics by Trygve Tollefsbol (Editor) During the past few decades, it has become increasingly apparent that heredity is not the sole determining factor in disease development, such as cancer. This landmark work covers a wide array of aspects in the relatively new area of epigenetics, ranging from its role in the basic mechanisms of tumorigenesis, to the newest epigenetic drugs being developed and used for cancer therapy. Cancer Epigenetics presents in-depth discussions of DNA methylation alterations, histone and RNA...
	DNA Methylation: Approaches and Applications by Manel Esteller (Editor) Understanding the complex roles of DNA methylation is currently an active field of research. DNA Methylation: Approaches and Applications presents the most current research on the impact of DNA methylation in human disease, particularly cancer. Written by leaders in the field, this state-of-art reference delineates the best techniques to use when addressing questions concerning the cytocine methylation status of genomic DNA. It includes concepts, experimental models, and clinical uses of...

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Product Description
Providing an interface between dry-bench bioinformaticians and wet-lab biologists, DNA Methylation Microarrays: Experimental Design and Statistical Analysis presents the statistical methods and tools to analyze high-throughput epigenomic data, in particular, DNA methylation microarray data. Since these microarrays share the same underlying principles as gene expression microarrays, many of the analyses in the text also apply to microarray-based gene expression and histone modification (ChIP-on-chip) studies. After introducing basic statistics, the book describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting from measurement imperfections. It then explores differential methylation and genomic tiling arrays. Focusing on exploratory data analysis, the next several chapters show how cluster and network analyses can link the functions and roles of unannotated DNA elements with known ones. The book concludes by surveying the open source software (R and Bioconductor), public databases, and other online resources available for microarray research. Requiring only limited knowledge of statistics and programming, this book helps readers gain a solid understanding of the methodological foundations of DNA microarray analysis.

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