Principles of Statistical Genomics
Xu, Shizhong (Geneticist)
Principles of Statistical Genomics by Shizhong Xu - New York Springer International Publishing 2013 - 1 recurso en línea (XV, 428 p.) 46 il., 12 il. col.
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 hurdleÂthe 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 isÂomprehensive reference for researchers and graduate students studying statistical genomics.Â
9780387708072
Genomas
QH438.4.S73 / X874 2013 EB
581.35
Principles of Statistical Genomics by Shizhong Xu - New York Springer International Publishing 2013 - 1 recurso en línea (XV, 428 p.) 46 il., 12 il. col.
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 hurdleÂthe 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 isÂomprehensive reference for researchers and graduate students studying statistical genomics.Â
9780387708072
Genomas
QH438.4.S73 / X874 2013 EB
581.35