From Gene Trees to Species Trees
SIAM Journal on Computing
On the Multiple Gene Duplication Problem
ISAAC '98 Proceedings of the 9th International Symposium on Algorithms and Computation
LATIN '00 Proceedings of the 4th Latin American Symposium on Theoretical Informatics
Reconciling a gene tree to a species tree under the duplication cost model
Theoretical Computer Science
Inferring phylogeny from whole genomes
Bioinformatics
URec: a system for unrooted reconciliation
Bioinformatics
The multiple gene duplication problem revisited
Bioinformatics
Bioinformatics
Heuristics for the gene-duplication problem: a Θ(n) speed-up for the local search
RECOMB'07 Proceedings of the 11th annual international conference on Research in computational molecular biology
Reconstructing domain compositions of ancestral multi-domain proteins
RCG'06 Proceedings of the RECOMB 2006 international conference on Comparative Genomics
Inferring evolutionary scenarios in the duplication, loss and horizontal gene transfer model
Logic and Program Semantics
Minimum leaf removal for reconciliation: complexity and algorithms
CPM'12 Proceedings of the 23rd Annual conference on Combinatorial Pattern Matching
Unrooted Tree Reconciliation: A Unified Approach
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Gene tree correction for reconciliation and species tree inference: Complexity and algorithms
Journal of Discrete Algorithms
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Evolutionary methods are increasingly challenged by the fast growing resources of genomic sequence information. Fundamental evolutionary events, like gene duplication, loss, and deep coalescence, account more then ever for incongruence between gene trees and the actual species tree. Gene tree reconciliation is addressing this fundamental problem by invoking the minimum number of gene-duplication and losses that reconcile a gene tree with a species tree. Despite its promise, gene tree reconciliation assumes the gene trees to be correctly rooted and free of error, which severely limits its application in practice. Here we present a novel linear time algorithm for error-corrected gene tree reconciliation of unrooted gene trees. Furthermore, in an empirical study on yeast genomes we successfully demonstrate the ability of our algorithm to (i) reconcile (cure) errorprone gene trees, and (ii) to improve on more advanced evolutionary applications that are based on gene tree reconciliation.