Principles of Statistical Genomics

Xu, Shizhong

ISBN 10: 1489994041 ISBN 13: 9781489994042
Published by Springer, 2014
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This book synthesizes current statistical methodologies applied to genome study, exploring statistical models and methods behind major bioinformatics software. Helps researchers choose the optimal algorithm to analyze data and to better interpret results. Num Pages: 444 pages, 29 black & white tables, biography. BIC Classification: PSAK1. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 23. Weight in Grams: 676. . 2014. 2013th Edition. paperback. . . . . Seller Inventory # V9781489994042

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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.

About the Author: Shizhong Xu, PhD
University of California, Department of Botany and Plant Sciences, Riverside, CA, USA

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Bibliographic Details

Title: Principles of Statistical Genomics
Publisher: Springer
Publication Date: 2014
Binding: Soft cover
Condition: New

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Taschenbuch. Condition: Neu. Principles of Statistical Genomics | Shizhong Xu | Taschenbuch | xvi | Englisch | 2014 | Springer New York | EAN 9781489994042 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 105057933

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 444 pp. Englisch. Seller Inventory # 9781489994042

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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 isa comprehensive reference for researchers and graduate students studying statistical genomics.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 444 pp. Englisch. Seller Inventory # 9781489994042

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9781489994042

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