Selasa, 27 Januari 2015

PDF Download Next-Generation Sequencing Data Analysis

PDF Download Next-Generation Sequencing Data Analysis

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Next-Generation Sequencing Data Analysis

Next-Generation Sequencing Data Analysis


Next-Generation Sequencing Data Analysis


PDF Download Next-Generation Sequencing Data Analysis

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Next-Generation Sequencing Data Analysis

About the Author

Dr. Xinkun "Sequen" Wang is the director of the NUSeq Core Facility and research associate professor in the Department of Biochemistry and Molecular Genetics at Northwestern University. He was previously an associate research professor of neurogenomics in the Higuchi Biosciences Center and Department of Pharmacology and Toxicology at the University of Kansas, where he was also the director of the Genomics Facility and Genome Sequencing Core. Dr. Wang’s research focuses on unraveling genomic changes that underlie neurodegeneration in brain aging and neurodegenerative diseases, such as Alzheimer’s disease.

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Product details

Hardcover: 258 pages

Publisher: CRC Press; 1 edition (February 24, 2016)

Language: English

ISBN-10: 1482217880

ISBN-13: 978-1482217889

Product Dimensions:

6.5 x 0.5 x 9.5 inches

Shipping Weight: 1.1 pounds (View shipping rates and policies)

Average Customer Review:

4.6 out of 5 stars

3 customer reviews

Amazon Best Sellers Rank:

#471,946 in Books (See Top 100 in Books)

I bought this book right around Christmas, it is a very good overview of today's technology in High through-put sequencing field. Although the price of the book is higher than other books, it is relatively useful for people who want to know about the sequencing. ~50 pages of introduction. No programming detail, which makes sense because there are so many ways you can analyze your data. If you have the money, not bad to own one, the book is systematic. By the way, there are also a lot of materials that you can find online.

Good quality and perfect size for travel

The first section (Chapter 1, 2, & 3) of this book provides a very good introduction to molecular biology for non-biologists (in particular Statisticians/Computer Scientists interested in high-throughput genomics analysis).

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