000			03008nam a22003374a 4500
001			BD-DhSAU 1519
001			16400966
003			BD-DhSAU
005			20161107140007.0
008			150115s2011 enka ob 001 0 eng
020			_a9780199213269 (hardback)
020			_a0199213267 (hardback)
040			_aBD-DhSAU
082			_a- _b- _222
100	1		_aGu, Xun, _cDr.
245	1	0	_aStatistical theory and methods for evolutionary genomics _h[online resource] / _cXun Gu.
260			_aOxford ; _aNew York : _bOxford University Press, _c2011.
300			_axi, 259 p. : _bill. ; _c26 cm.
490	1		_aOxford biology
500			_aOxford scholarship online biology
504			_aIncludes bibliographical references (p. [223]-250) and index.
505	0		_a1. Basics in molecular evolution -- 2. Basics in bioinformatics and statistics -- 3. Functional divergence after gene duplication: statistical modeling -- 4. Functional divergence after gene duplication: applications and others -- 5. Phylogenomic expression analysis between duplicate genes -- 6. Expression between duplicate genes: genome-wide analysis -- 7. Tissue-driven hypothesis of genomic evolution -- 8. Gene pleiotropy and evolution of protein sequence -- 9. Modeling the genomic evolution of gene contents -- 10. Advanced topics in systems biology and network evolution.
520			_a"Evolutionary genomics is a relatively new research field with the ultimate goal of understanding the underlying evolutionary and genetic mechanisms for the emergence of genome complexity under changing environments. It stems from an integration of high throughput data from functional genomics, statistical modelling and bioinformatics, and the procedure of phylogeny-based analysis. Statistical Theory and Methods for Evolutionary Genomics summarises the statistical framework of evolutionary genomics, and illustrates how statistical modelling and testing can enhance our understanding of functional genomic evolution. The book reviews the recent developments in methodology from an evolutionary perspective of genome function, and incorporates substantial examples from high throughput data in model organisms. In addition to phylogeny-based functional analysis of DNA sequences, the author includes extensive discussion on how new types of functional genomic data (e.g. microarray) can provide exciting new insights into the evolution of genome function, which can lead in turn to an understanding of the emergence of genome complexity during evolution"-- _cProvided by publisher.
590			_aAnwar
650		0	_aGenomics _xStatistical methods.
650		0	_aEvolutionary genetics _xStatistical methods.
830		0	_aOxford biology.
856			_uhttp://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780199213269.001.0001/acprof-9780199213269?rskey=9v7IoD&result=72
856			_uhttp://doi.org/10.1093/acprof:oso/9780199213269.001.0001
942			_2ddc _cOnline book
999			_c1519 _d1519