Evolutionary Genomics Statistical and Computational Methods

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. A...

Descripción completa

Detalles Bibliográficos
Otros Autores: Anisimova, Maria (Editor), Anisimova, Maria. editor (editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: New York, NY : Springer Nature 2019
2019.
Edición:2nd ed. 2019.
Colección:Methods in Molecular Biology, 1910
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009422931306719
Tabla de Contenidos:
  • 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.