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Evolutionary Genomics [[electronic resource] ] : Statistical and Computational Methods / / edited by Maria Anisimova



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Autore: Anisimova Maria Visualizza persona
Titolo: Evolutionary Genomics [[electronic resource] ] : Statistical and Computational Methods / / edited by Maria Anisimova Visualizza cluster
Pubblicazione: Springer Nature, 2019
New York, NY : , : Springer New York : , : Imprint : Humana, , 2019
Edizione: 2nd ed. 2019.
Descrizione fisica: 1 online resource (XVII, 780 p. 189 illus., 110 illus. in color.)
Disciplina: 570.285
Soggetto topico: Bioinformatics
Genetics
Evolution (Biology)
Genetics and Genomics
Evolutionary Biology
Genètica evolutiva
Genòmica
Models matemàtics
Bioinformàtica
Soggetto genere / forma: Llibres electrònics
Soggetto non controllato: Life sciences
Bioinformatics
Genetics
Evolutionary biology
Persona (resp. second.): AnisimovaMaria
Nota di contenuto: Introduction to Genome Biology and Diversity -- Probability, Statistics, and Computational Science -- A Not-So-Long Introduction to Computational Molecular Evolution -- Whole-Genome Alignment -- Inferring Orthology and Paralogy -- Transposable Elements and Their Identification -- Modern Phylogenomics: Building Phylogenetic Trees Using the Multispecies Coalescent Model -- Genome-Wide Comparative Analysis of Phylogenetic Trees: The Prokaryotic Forest of Life -- The Methodology Behind Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution -- Bayesian Molecular Clock Dating Using Genome-Scale Datasets -- Genome Evolution in Outcrossing vs. Selfing vs. Asexual Species -- Selection Acting on Genomes -- Looking for Darwin in Genomic Sequences: Validity and Success Depends on the Relationship between Model and Data -- Evolution of Viral Genomes: Interplay between Selection, Recombination, and Other Forces -- Evolution of Protein Domain Architectures -- New Insights on the Evolution of Genome Content: Population Dynamics of Transposable Elements in Flies and Humans -- Association Mapping and Disease: Evolutionary Perspectives -- Ancestral Population Genomics -- Introduction to the Analysis of Environmental Sequences: Metagenomics with MEGAN -- Multiple Data Analyses and Statistical Approaches for Analyzing Data from Metagenomic Studies and Clinical Trials -- Systems Genetics for Evolutionary Studies -- Analyzing Epigenome Data in Context of Genome Evolution and Human Diseases -- Semantic Integration and Enrichment of Heterogeneous Biological Databases -- High-Performance Computing in Bayesian Phylogenetics and Phylodynamics Using BEAGLE -- Scalable Workflows and Reproducible Data Analysis for Genomics -- Sharing Programming Resources between Bio* Projects.
Sommario/riassunto: This open access book addresses the challenge of analyzing and understanding the evolutionary dynamics of complex biological systems at the genomic level, and elaborates on some promising strategies that would bring us closer to uncovering of the vital relationships between genotype and phenotype. After a few educational primers, the book continues with sections on sequence homology and alignment, phylogenetic methods to study genome evolution, methodologies for evaluating selective pressures on genomic sequences as well as genomic evolution in light of protein domain architecture and transposable elements, population genomics and other omics, and discussions of current bottlenecks in handling and analyzing genomic data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and expert implementation advice that lead to the best results. Authoritative and comprehensive, Evolutionary Genomics: Statistical and Computational Methods, Second Edition aims to serve both novices in biology with strong statistics and computational skills, and molecular biologists with a good grasp of standard mathematical concepts, in moving this important field of study forward.
Titolo autorizzato: Evolutionary Genomics  Visualizza cluster
ISBN: 1-4939-9074-8
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910372751703321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: Methods in Molecular Biology, . 1064-3745 ; ; 1910