Evolutionary Genomics Statistical and Computational Methods, Volume 2
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- Hardcover ausgewählt
- Taschenbuch
- eBook
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Sprache:Englisch
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Verlag:Humana Press
- Humana Press Fr. 242.00 ausgewählt
- Springer Us Fr. 73.90
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Auflage:2012
- 2012 Fr. 192.00
- 2012 Fr. 242.00 ausgewählt
Fr. 242.00
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Gebundene Ausgabe
Erscheinungsdatum
08.03.2012
Herausgeber
Maria AnisimovaVerlag
Humana PressSeitenzahl
556
Maße (L/B/H)
26/18.3/3.6 cm
Gewicht
1304 g
Auflage
2012
Sprache
Englisch
ISBN
978-1-61779-584-8
Together 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 2 begins with phylogenomics and continues with in-depth coverage of natural selection, recombination, and genomic innovation. The remaining chapters treat topics of more recent interest, including population genomics, -omics studies, and computational issues related to the handling of large-scale genomic data. 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.
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