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020 _a9780387708072
040 _aES-MaUEC
050 4 _aQH438.4.S73
_bX874 2013 EB
082 0 4 _a581.35
100 1 _aXu, Shizhong
_c(Geneticist)
_0Local
_984261
245 1 0 _aPrinciples of Statistical Genomics
_cby Shizhong Xu
260 _aNew York
_bSpringer International Publishing
_c2013
300 _a1 recurso en línea (XV, 428 p.) 46 il., 12 il. col.
336 _aTexto (visual)
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
338 _aonline resource
_bcr
_2rdacarrier
520 _aStatistical 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 hurdleÂ{u4BE0}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 isÂ{u1823}omprehensive reference for researchers and graduate students studying statistical genomics.Â{u0826}
942 _2lcc
_cLE
988 _aEBOOK, EBSPRINGERrevisado
650 7 _aGenomas
_9162605
_0comprobar BNE20033155385
_2embne
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-0-387-70807-2
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901 _ai9780387708072
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_b10-10-17
_c01-10-14
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_a_vill
_b03-01-17
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