Evolutionary Genomics

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176,54 

Statistical and Computational Methods, Volume 2, Methods in Molecular Biology 856

ISBN: 1493960423
ISBN 13: 9781493960422
Herausgeber: Maria Anisimova
Verlag: Humana Press
Umfang: xv, 556 S.
Erscheinungsdatum: 23.08.2016
Auflage: 1/2012
Produktform: Kartoniert
Einband: Kartoniert

This highly practical volume, with its step-by-step techniques, brings together recent developments in the statistical methodology of evolutionary genomics and the challenges that followed as a result of rapidly improving sequencing technologies. 

Artikelnummer: 2876572 Kategorie:

Beschreibung

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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E-Mail: juergen.hartmann@springer.com

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