Eric Tannier

The complexity of genome evolution has given birth to exciting challenges for computational biologists. A various range of algorithmic, statistical, mathem- ical techniques to elucidate the histories of molecules are developed each year and many are presented at the RECOMB satellite workshop on Comparative Genomics. It is a place where scientists working on all aspects of comparative genomics can share ideas on the development of tools and their application to relevant questions. This volume contains the papers presented at RECOMB-CG 2010, held on October 9–11 in Ottawa. The ?eld is still ?ourishing as seen from the papers presented this year: many developments enrich the combinatorics of genome rearrangements, while gene order phylogenies are becoming more and more - curate, thanks to a mixing of combinatorial and statistical principles, associated with rapid and thoughtful heuristics. Several papers tend to re?ne the models of genome evolution, and more and more genomic events can be modeled, from single nucleotide substitutions in whole genome alignments to large structural mutations or horizontal gene transfers.

International Workshop, RECOMB-CG 2010, Ottawa, Canada, October 9-11, 2010, Proceedings

Comparative Genomics

Guillaume Fertin

Anthony Labarre

Irena Rusu

Stéphane Vialette

A comprehensive survey of a rapidly expanding field of combinatorial optimization, mathematically oriented but offering biological explanations when required. From one cell to another, from one individual to another, and from one species to another, the content of DNA molecules is often similar. The organization of these molecules, however, differs dramatically, and the mutations that affect this organization are known as genome rearrangements. Combinatorial methods are used to reconstruct putative rearrangement scenarios in order to explain the evolutionary history of a set of species, often formalizing the evolutionary events that can explain the multiple combinations of observed genomes as combinatorial optimization problems. This book offers the first comprehensive survey of this rapidly expanding application of combinatorial optimization. It can be used as a reference for experienced researchers or as an introductory text for a broader audience. Genome rearrangement problems have proved so interesting from a combinatorial point of view that the field now belongs as much to mathematics as to biology. This book takes a mathematically oriented approach, but provides biological background when necessary. It presents a series of models, beginning with the simplest (which is progressively extended by dropping restrictions), each constructing a genome rearrangement problem. The book also discusses an important generalization of the basic problem known as the median problem, surveys attempts to reconstruct the relationships between genomes with phylogenetic trees, and offers a collection of summaries and appendixes with useful additional information.

Eric Tannier

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