Principles of Statistical Genomics
Shizhong Xu
Venduto da BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Venditore AbeBooks dal 11 gennaio 2012
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Aggiungere al carrelloVenduto da BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Venditore AbeBooks dal 11 gennaio 2012
Condizione: Nuovo
Quantità: 2 disponibili
Aggiungere al carrelloThis 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.
Codice articolo 9780387708065
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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