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Ajouter au panier2nd Ed. XVII, 780 p. Hardcover. 2nd Ed. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stamped. Methods in Molecular Biology, Volume 1910. Sprache: Englisch.
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Ajouter au panierHardcover. Etat : New. 540 pp. 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. 0.0.
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Ajouter au panierEtat : Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
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Ajouter au panierTaschenbuch. Etat : Neu. Evolutionary Genomics | Statistical and Computational Methods, Volume 2 | Maria Anisimova | Taschenbuch | xv | Englisch | 2016 | Humana | EAN 9781493960422 | Verantwortliche Person für die EU: Humana Press in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Ajouter au panierEtat : New. pp. 571.
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Ajouter au panierHardcover. Etat : Brand New. 1st edition. 467 pages. 10.50x7.50x1.00 inches. In Stock.
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Ajouter au panierPaperback. Etat : Brand New. reprint edition. 556 pages. 10.00x7.01x1.16 inches. In Stock.
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Ajouter au panierEtat : Sehr gut. Zustand: Sehr gut | Seiten: 572 | Sprache: Englisch | Produktart: Bücher | 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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