Random generation of combinatorial structures from a uniform
Theoretical Computer Science
Transforming cabbage into turnip: polynomial algorithm for sorting signed permutations by reversals
Journal of the ACM (JACM)
Sorting Permutations by Reversals and Eulerian Cycle Decompositions
SIAM Journal on Discrete Mathematics
Introduction to Algorithms
1.375-Approximation Algorithm for Sorting by Reversals
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
A very elementary presentation of the Hannenhalli-Pevzner theory
Discrete Applied Mathematics - 12th annual symposium on combinatorial pattern matching (CPM)
Maximum likelihood of evolutionary trees is hard
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
A probabilistic model for gene content evolution with duplication, loss, and horizontal transfer
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
H-trees: a Model of Evolutionary Scenarios with Horizontal Gene Transfer
Fundamenta Informaticae - From Mathematical Beauty to the Truth of Nature: to Jerzy Tiuryn on his 60th Birthday
Simultaneous Identification of Duplications and Lateral Gene Transfers
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
RECOMB'12 Proceedings of the 16th Annual international conference on Research in Computational Molecular Biology
Inferring evolutionary scenarios in the duplication, loss and horizontal gene transfer model
Logic and Program Semantics
Phylogenetic tree reconstruction with protein linkage
ISBRA'12 Proceedings of the 8th international conference on Bioinformatics Research and Applications
Simultaneous Identification of Duplications, Losses, and Lateral Gene Transfers
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Accounting for gene tree uncertainties improves gene trees and reconciliation inference
WABI'12 Proceedings of the 12th international conference on Algorithms in Bioinformatics
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Phylogeny is both a fundamental tool in biology and a rich source of fascinating modeling and algorithmic problems. Today's wealth of sequenced genomes makes it increasingly important to understand evolutionary events such as duplications, losses, transpositions, inversions, lateral transfers, and domain shuffling. We focus on the gene duplication event, that constitutes a major force in the creation of genes with new function [Ohno 1970; Lynch and Force 2000] and, thereby also, of biodiversity. We introduce the probabilistic gene evolution model, which describes how a gene tree evolves within a given species tree with respect to speciation, gene duplication, and gene loss. The actual relation between gene tree and species tree is captured by a reconciliation, a concept which we generalize for more expressiveness. The model is a canonical generalization of the classical linear birth-death process, obtained by replacing the interval where the process takes place by a tree. For the gene evolution model, we derive efficient algorithms for some associated probability distributions: the probability of a reconciled tree, the probability of a gene tree, the maximum probability reconciliation, the posterior probability of a reconciliation, and sampling reconciliations with respect to the posterior probability. These algorithms provides the basis for several applications, including species tree construction, reconciliation analysis, orthology analysis, biogeography, and host-parasite co-evolution.