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Evolutionary Genomics : Statistical and Computational Methods / edited by Maria Anisimova.

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Holman Biotech Commons QH506 .M45 v.1 (1984)-v.20 (1993),v.22 (1994),v.24 (1994)-v.53 (1996), v.42 (1995) and v.51 (1995) reported missing 3-13-2000 v.55 (1995),v.58 (1996)-v.63 (1997), v.65 (1996)-v.154 (2001), v.156 (2001)-190 (2002), v.192 (2002)-v.407 (2007) v.409 (2007)-v.416 (2008),v.418 (2008)-v.466 v.468-v.490,v.492,v.494,v.496-499 501-506,508,510-512,514,516-517,519-536 538,540-569,571 573-589,591-608,610-615,617,620-627,630-633,636,638,642
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Format:
Book
Contributor:
Anisimova, Maria, editor.
SpringerLink (Online service)
Series:
Springer Protocols (Springer-12345)
Methods in molecular biology 1064-3745 ; 1910.
Methods in Molecular Biology, 1064-3745 ; 1910
Language:
English
Subjects (All):
Bioinformatics.
Genetics.
Evolution (Biology).
Genetics and Genomics.
Evolutionary Biology.
Local Subjects:
Bioinformatics.
Genetics and Genomics.
Evolutionary Biology.
Physical Description:
1 online resource (XVII, 780 pages) : 189 illustrations, 110 illustrations in color.
Edition:
Second edition 2019.
Contained In:
Springer eBooks
Place of Publication:
New York, NY : Springer New York : Imprint: Humana, 2019.
System Details:
text file PDF
Summary:
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.
Contents:
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.
Other Format:
Printed edition:
ISBN:
978-1-4939-9074-0
9781493990740
Access Restriction:
Restricted for use by site license.

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