Fast algorithms for finding nearest common ancestors
SIAM Journal on Computing
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
On reconstructing species trees from gene trees in term of duplications and losses
RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
New algorithms for the duplication-loss model
RECOMB '00 Proceedings of the fourth annual international conference on Computational molecular biology
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
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
On the structure of reconciliations
RCG'04 Proceedings of the 2004 RECOMB international conference on Comparative Genomics
The Gene-Duplication Problem: Near-Linear Time Algorithms for NNI-Based Local Searches
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Linear-Time Algorithms for the Multiple Gene Duplication Problems
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
GTP supertrees from unrooted gene trees: linear time algorithms for NNI based local searches
ISBRA'12 Proceedings of the 8th international conference on Bioinformatics Research and Applications
Efficient Algorithms for Knowledge-Enhanced Supertree and Supermatrix Phylogenetic Problems
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
| Hi-index | 0.00 |
The gene-duplication problem is to infer a species supertree from gene trees that are confounded by complex histories of gene duplications. This problem is NP-hard and thus requires efficient and effective heuristics. Existing heuristics perform a stepwise search of the tree space, where each step is guided by an exact solution to an instance of a local search problem. We improve on the time complexity of the local search problem by a factor of n2= log n, where n is the size of the resulting species supertree. Typically, several thousand instances of the local search problem are solved throughout a stepwise heuristic search. Hence, our improvement makes the gene-duplication problem much more tractable for large-scale phylogenetic analyses.