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Evolutionary Genomics: Statistical and Computational Methods, Volume 2 Softcover reprint of the original 1st ed. 2012 [Pehme köide]

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  • Formaat: Paperback / softback, 556 pages, kõrgus x laius: 254x178 mm, kaal: 1454 g, XV, 556 p., 1 Paperback / softback
  • Sari: Methods in Molecular Biology 856
  • Ilmumisaeg: 23-Aug-2016
  • Kirjastus: Humana Press Inc.
  • ISBN-10: 1493960423
  • ISBN-13: 9781493960422
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Evolutionary Genomics: Statistical and Computational Methods, Volume 2 Softcover reprint of the original 1st ed. 2012Suurem pilt
  • Formaat: Paperback / softback, 556 pages, kõrgus x laius: 254x178 mm, kaal: 1454 g, XV, 556 p., 1 Paperback / softback
  • Sari: Methods in Molecular Biology 856
  • Ilmumisaeg: 23-Aug-2016
  • Kirjastus: Humana Press Inc.
  • ISBN-10: 1493960423
  • ISBN-13: 9781493960422
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781493960422.html
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.

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.