Evolutionary Genomics: Statistical and Computational Methods, Volume 2
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 Computat...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Totowa, NJ
Humana Press
2012
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| Schriftenreihe: | Methods in Molecular Biology, Methods and Protocols
856 |
| Schlagworte: | |
| Online-Zugang: | UBR01 TUM01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (XV, 556 p. 111 illus., 44 illus. in color) |
| ISBN: | 9781617795855 |
| DOI: | 10.1007/978-1-61779-585-5 |
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| spelling | Evolutionary Genomics Statistical and Computational Methods, Volume 2 edited by Maria Anisimova Totowa, NJ Humana Press 2012 1 Online-Ressource (XV, 556 p. 111 illus., 44 illus. in color) txt rdacontent c rdamedia cr rdacarrier Methods in Molecular Biology, Methods and Protocols 856 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 Biomedicine Human Genetics Evolutionary Biology Medicine Human genetics Evolutionary biology Evolution (DE-588)4071050-6 gnd rswk-swf Bioinformatik (DE-588)4611085-9 gnd rswk-swf Genanalyse (DE-588)4200230-8 gnd rswk-swf Genanalyse (DE-588)4200230-8 s Evolution (DE-588)4071050-6 s Bioinformatik (DE-588)4611085-9 s b DE-604 Anisimova, Maria edt Erscheint auch als Druck-Ausgabe 9781617795848 https://doi.org/10.1007/978-1-61779-585-5 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Evolutionary Genomics Statistical and Computational Methods, Volume 2 Biomedicine Human Genetics Evolutionary Biology Medicine Human genetics Evolutionary biology Evolution (DE-588)4071050-6 gnd Bioinformatik (DE-588)4611085-9 gnd Genanalyse (DE-588)4200230-8 gnd |
| subject_GND | (DE-588)4071050-6 (DE-588)4611085-9 (DE-588)4200230-8 |
| title | Evolutionary Genomics Statistical and Computational Methods, Volume 2 |
| title_auth | Evolutionary Genomics Statistical and Computational Methods, Volume 2 |
| title_exact_search | Evolutionary Genomics Statistical and Computational Methods, Volume 2 |
| title_full | Evolutionary Genomics Statistical and Computational Methods, Volume 2 edited by Maria Anisimova |
| title_fullStr | Evolutionary Genomics Statistical and Computational Methods, Volume 2 edited by Maria Anisimova |
| title_full_unstemmed | Evolutionary Genomics Statistical and Computational Methods, Volume 2 edited by Maria Anisimova |
| title_short | Evolutionary Genomics |
| title_sort | evolutionary genomics statistical and computational methods volume 2 |
| title_sub | Statistical and Computational Methods, Volume 2 |
| topic | Biomedicine Human Genetics Evolutionary Biology Medicine Human genetics Evolutionary biology Evolution (DE-588)4071050-6 gnd Bioinformatik (DE-588)4611085-9 gnd Genanalyse (DE-588)4200230-8 gnd |
| topic_facet | Biomedicine Human Genetics Evolutionary Biology Medicine Human genetics Evolutionary biology Evolution Bioinformatik Genanalyse |
| url | https://doi.org/10.1007/978-1-61779-585-5 |
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