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Sinopsis
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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Acerca del autor
Shizhong Xu, PhD
University of California, Department of Botany and Plant Sciences, Riverside, CA, USA
De la contraportada
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 to 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.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialSpringer
- Año de publicación2012
- ISBN 10 0387708065
- ISBN 13 9780387708065
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de páginas444
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Principles of Statistical Genomics
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Principles of Statistical Genomics
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Springer New York Sep 2012, 2012
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ISBN 13: 9780387708065
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Buch. Condición: 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. Nº de ref. del artículo: 9780387708065
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. covers microarray data analysis, which is absent in both competing books in addition to QTL mapping introduces Bayesian method, which was not available in both competing books uses more rigorous mathematical approaches to derive the statis. Nº de ref. del artículo: 5910553
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ISBN 10: 0387708065
ISBN 13: 9780387708065
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Buch. Condición: 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. Nº de ref. del artículo: 9780387708065
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ISBN 10: 0387708065
ISBN 13: 9780387708065
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Principles of Statistical Genomics
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ISBN 10: 0387708065
ISBN 13: 9780387708065
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