000			03814nam a22003615i 4500
001			391872
003			ES-MaUEC
005			20230102122621.0
007			cr nn 008mamaa
008			120309s2012 xxu| s |||| 0|eng d
020			_a9781617795824
024	7		_a10.1007/978-1-61779-582-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC
245	1	0	_aEvolutionary Genomics _bStatistical and Computational Methods, Volume 1 _cedited by Maria Anisimova.
250			_a1st edition 2012
264		1	_aTotowa, NJ _bHumana Press _c2012
300			_a1 recurso en línea (XIV, 467 páginas) _b91 ilustraciones, 13 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029 _v855
505	0		_aIntroduction to Genome Biology: Features, Processes, and Structures -- Diversity of Genome Organization -- Probability, Statistics, and Computational Science -- The Essentials of Computational Molecular Evolution -- Next-Generation Sequencing Technologies and Fragment Assembly Algorithms -- Gene Prediction -- Alignment Methods: Strategies, Challenges, Benchmarking, and Comparative Overview -- Whole-Genome Alignment -- Inferring Orthology and Paralogy -- Detecting Laterally Transferred Genes -- Genome Evolution in Outcrossing Vs. Selfing Vs. Asexual Species -- Transposable Elements And Their Identification -- Evolution of Genome Content: Population Dynamics of Transposable Elements in Flies and Humans -- Detection and Phylogenetic Assessment of Conserved Synteny Derived from Whole Genome Duplications -- Analysis of Gene Order Evolution Beyond Single-Copy Genes -- Discovering Patterns in Gene Order.
520			_aTogether with early theoretical work in population genetics, the debate on sources of genetic makeup initiated by proponents of the neutral theory made a solid contribution to the spectacular growth in statistical methodologies for molecular evolution. Evolutionary Genomics: Statistical and Computational Methods is intended to bring together the more recent developments in the statistical methodology and the challenges that followed as a result of rapidly improving sequencing technologies.  Presented by top scientists from a variety of disciplines, the collection includes a wide spectrum of articles encompassing theoretical works and hands-on tutorials, as well as many reviews with key biological insight.  Volume 1 includes a helpful introductory section of bioinformatician primers followed by detailed chapters detailing genomic data assembly, alignment, and homology inference as well as insights into genome evolution from statistical analyses.  Written in the highly successful Methods in Molecular Biology™ series format, this work provides the kind of advice on methodology and implementation that is crucial for getting ahead in genomic data analyses.   Comprehensive and cutting-edge, Evolutionary Genomics: Statistical and Computational Methods is a treasure chest of state-of the-art methods to study genomic and omics data, certain to inspire both young and experienced readers to join the interdisciplinary field of evolutionary genomics.
700	1		_aAnisimova, Maria _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9781617795817
776	0	8	_iPrinted edition: _z9781617795831
776	0	8	_iPrinted edition: _z9781493959082
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-61779-582-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
988			_aSpringer_Protocols_2012
999			_c391872 _d391872