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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