Evolutionary Genomics

Statistical and Computational Methods, Volume 2

Maria Anisimova (Herausgeber)

Buch | Hardcover
556 Seiten
2012
Humana Press Inc. (Verlag)
978-1-61779-584-8 (ISBN)

Lese- und Medienproben

Evolutionary Genomics -
235,39 inkl. MwSt
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.
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.

Tangled Trees: The Challenge of Inferring Species Trees from Coalescent and Non-Coalescent Genes.- Modeling Gene Family Evolution and Reconciling Phylogenetic Discord.- Genome-Wide Comparative Analysis of Phylogenetic Trees: The Prokaryotic Forest of Life.- Philosophy and Evolution: Minding the Gap Between Evolutionary Patterns and Tree-Like Patterns.- Selection on the Protein Coding Genome.- Methods to Detect Selection on Non-Coding DNA.- The Origin and Evolution of New Genes.- Evolution of Protein Domain Architectures.- Estimating Recombination Rates from Genetic Variation in Humans.- Evolution of Viral Genomes: Interplay Between Selection, Recombination, and Other Forces.- Association Mapping and Disease: Evolutionary Perspectives.- Ancestral Population Genomics.- Non-Redundant Representation of Ancestral Recombinations Graphs.- Using Genomic Tools to Study Regulatory Evolution.- Characterization and Evolutionary Analysis of Protein-Protein Interaction Networks.- Statistical Methods in Metabolomics.- Introduction to the Analysis of Environmental Sequences: Metagenomics with MEGAN.- Analyzing Epigenome Data in Context of Genome Evolution and Human Diseases.- Genetical Genomics for Evolutionary Studies.- Genomics Data Resources: Frameworks and Standards.- Sharing Programming Resources Between Bio* Projects through Remote Procedure Call and Native Call Stack Strategies.- Scalable Computing for Evolutionary Genomics.

Reihe/Serie Methods in Molecular Biology ; 856
Zusatzinfo XV, 556 p.
Verlagsort Totowa, NJ
Sprache englisch
Maße 178 x 254 mm
Themenwelt Medizin / Pharmazie Medizinische Fachgebiete
Studium 2. Studienabschnitt (Klinik) Humangenetik
Naturwissenschaften Biologie Evolution
Naturwissenschaften Biologie Genetik / Molekularbiologie
Schlagworte Bioinformatics • Computational Techniques • Gen-Analyse / Genom-Analyse • Genome Evolution • Genomic data • Genomic sequences • Molecular Evolution • Phylogenomics • Statistical methodologies
ISBN-10 1-61779-584-4 / 1617795844
ISBN-13 978-1-61779-584-8 / 9781617795848
Zustand Neuware
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