Principles of Statistical Genomics

Nonfiction, Science & Nature, Science, Biological Sciences, Botany, Zoology
Cover of the book Principles of Statistical Genomics by Shizhong Xu, Springer New York
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Author: Shizhong Xu ISBN: 9780387708072
Publisher: Springer New York Publication: September 13, 2012
Imprint: Springer Language: English
Author: Shizhong Xu
ISBN: 9780387708072
Publisher: Springer New York
Publication: September 13, 2012
Imprint: Springer
Language: English

Statistical genomics is a rapidly developing field, with more and more people involved in this area. However, a lack of synthetic reference books and textbooks in statistical genomics has become a major hurdle on the development of the field. Although many books have been published recently in bioinformatics, most of them emphasize DNA sequence analysis under a deterministic approach.

Principles of Statistical Genomics synthesizes the state-of-the-art statistical methodologies (stochastic approaches) applied to genome study. It facilitates understanding of the statistical models and methods behind the major bioinformatics software packages, which will help researchers choose the optimal algorithm to analyze their data and better interpret the results of their analyses. Understanding existing statistical models and algorithms assists researchers to develop improved statistical methods to extract maximum information from their data.

Resourceful and easy to use, Principles of Statistical Genomics is a comprehensive reference for researchers and graduate students studying statistical genomics. 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Statistical genomics is a rapidly developing field, with more and more people involved in this area. However, a lack of synthetic reference books and textbooks in statistical genomics has become a major hurdle on the development of the field. Although many books have been published recently in bioinformatics, most of them emphasize DNA sequence analysis under a deterministic approach.

Principles of Statistical Genomics synthesizes the state-of-the-art statistical methodologies (stochastic approaches) applied to genome study. It facilitates understanding of the statistical models and methods behind the major bioinformatics software packages, which will help researchers choose the optimal algorithm to analyze their data and better interpret the results of their analyses. Understanding existing statistical models and algorithms assists researchers to develop improved statistical methods to extract maximum information from their data.

Resourceful and easy to use, Principles of Statistical Genomics is a comprehensive reference for researchers and graduate students studying statistical genomics. 

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