Part I: Introduction: Bioinformatician’s Primers

Aidan Budd

Rajeev K. Azad and Jeffrey G. Lawrence

Part III: Genome Evolution: Insights from Statistical Analyses

11.

2. Diversity of Genome Organization

Aidan Budd

3. Probability, Statistics, and Computational Science

Niko Beerenwinkel and Juliane Siebourg

4. The Essentials of Computational Molecular Evolution

Stéphane Aris-Brosou and Nicolas Rodrigue

Part II: Genomic Data Assembly, Alignment, and Homology Inference

5. Next-Generation Sequencing Technologies and Fragment Assembly Algorithms

Heewook Lee and Haixu Tang

6. Gene Prediction

Rajeev K. Azad and Jeffrey G. Lawrence

Part III: Genome Evolution: Insights from Statistical Analyses

11.

Tyler Alioto

Rajeev K. Azad and Jeffrey G. Lawrence

Part III: Genome Evolution: Insights from Statistical Analyses

11.

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

Ari Löytynoja

8. Whole-Genome Alignment

Colin N. Dewey

9. Inferring Orthology and Paralogy

Adrian M. Altenho and Christophe Dessimoz

10. Detecting Laterally Transferred Genes

Rajeev K. Azad and Jeffrey G. Lawrence

Part III: Genome Evolution: Insights from Statistical Analyses

11.

Sylvain Glémin and Nicolas Galtier

12. Transposable Elements And Their Identification

Wojciech Makałowski, Amit Pande, Valer Gotea, and Izabela Makałowska

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

Josefa González and Dmitri A. Petrov

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

Shigehiro Kuraku and Axel Meyer

15. Analysis of Gene Order Evolution Beyond Single-Copy Genes

Nadia El-Mabrouk and David Sankoff

16. Discovering Patterns in Gene Order

Laxmi Parida and Niina Haiminen

1. Introduction to Genome Biology: Features, Processes, and Structures

Rajeev K. Azad and Jeffrey G. Lawrence

Part III: Genome Evolution: Insights from Statistical Analyses

11.

Aidan Budd

Rajeev K. Azad and Jeffrey G. Lawrence

Part III: Genome Evolution: Insights from Statistical Analyses

11.

2. Diversity of Genome Organization

Aidan Budd

3. Probability, Statistics, and Computational Science

Niko Beerenwinkel and Juliane Siebourg

4. The Essentials of Computational Molecular Evolution

Stéphane Aris-Brosou and Nicolas Rodrigue

Part II: Genomic Data Assembly, Alignment, and Homology Inference

5. Next-Generation Sequencing Technologies and Fragment Assembly Algorithms

Heewook Lee and Haixu Tang

6. Gene Prediction

Rajeev K. Azad and Jeffrey G. Lawrence

Part III: Genome Evolution: Insights from Statistical Analyses

11.

Tyler Alioto

Rajeev K. Azad and Jeffrey G. Lawrence

Part III: Genome Evolution: Insights from Statistical Analyses

11.

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

Ari Löytynoja

8. Whole-Genome Alignment

Colin N. Dewey

9. Inferring Orthology and Paralogy

Adrian M. Altenho and Christophe Dessimoz

10. Detecting Laterally Transferred Genes

Rajeev K. Azad and Jeffrey G. Lawrence

Part III: Genome Evolution: Insights from Statistical Analyses

11.

Sylvain Glémin and Nicolas Galtier

12. Transposable Elements And Their Identification

Wojciech Makałowski, Amit Pande, Valer Gotea, and Izabela Makałowska

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

Josefa González and Dmitri A. Petrov

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

Shigehiro Kuraku and Axel Meyer

15. Analysis of Gene Order Evolution Beyond Single-Copy Genes

Nadia El-Mabrouk and David Sankoff

16. Discovering Patterns in Gene Order

Laxmi Parida and Niina Haiminen

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(t) 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.