Evolutionary Genomics : Statistical and Computational Methods, Volume 1 / edited by Maria Anisimova.

Format:

Book

Contributor:

Anisimova, Maria, editor.

SpringerLink (Online service)

Series:

Methods in Molecular Biology, Methods and Protocols, 1064-3745 ; 855.

Springer Protocols (Springer-12345)

Methods in Molecular Biology, Methods and Protocols, 1064-3745 ; 855

Language:

English

Subjects (All):

Medicine.

Human genetics.

Evolution (Biology).

Biomedicine.

Human Genetics.

Evolutionary Biology.

Local Subjects:

Biomedicine.

Human Genetics.

Evolutionary Biology.

Physical Description:

1 online resource (XIV, 467 pages) : 91 illustrations, 13 illustrations in color.

Contained In:

Springer eBooks

Place of Publication:

Totowa, NJ : Humana Press : Imprint: Humana Press, 2012.

System Details:

text file PDF

Summary:

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 1 includes a helpful introductory section of bioinformatician primers followed by detailed chapters detailing genomic data assembly, alignment, and homology inference as well as insights into genome evolution from statistical analyses. 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.

Contents:

Introduction to Genome Biology: Features, Processes, and Structures

Diversity of Genome Organization

Probability, Statistics, and Computational Science

The Essentials of Computational Molecular Evolution

Next-Generation Sequencing Technologies and Fragment Assembly Algorithms

Gene Prediction

Alignment Methods: Strategies, Challenges, Benchmarking, and Comparative Overview

Whole-Genome Alignment

Inferring Orthology and Paralogy

Detecting Laterally Transferred Genes

Genome Evolution in Outcrossing Vs. Selfing Vs. Asexual Species

Transposable Elements And Their Identification

Evolution of Genome Content: Population Dynamics of Transposable Elements in Flies and Humans

Detection and Phylogenetic Assessment of Conserved Synteny Derived from Whole Genome Duplications

Analysis of Gene Order Evolution Beyond Single-Copy Genes

Discovering Patterns in Gene Order.

Other Format:

Printed edition:

ISBN:

9781617795824

Access Restriction:

Restricted for use by site license.