On the agreement of many trees
Information Processing Letters
Maximum Agreement Subtree in a Set of Evolutionary Trees: Metrics and Efficient Algorithms
SIAM Journal on Computing
Efficient Data Mining for Maximal Frequent Subtrees
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Efficiently Mining Frequent Trees in a Forest: Algorithms and Applications
IEEE Transactions on Knowledge and Data Engineering
Frequent Subtree Mining - An Overview
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Discovering Frequent Agreement Subtrees from Phylogenetic Data
IEEE Transactions on Knowledge and Data Engineering
Mixed Integer Linear Programming for Maximum-Parsimony Phylogeny Inference
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
An improved algorithm for the maximum agreement subtree problem
Information Processing Letters
Uncovering Hidden Phylogenetic Consensus in Large Data Sets
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
The kernel of maximum agreement subtrees
ISBRA'11 Proceedings of the 7th international conference on Bioinformatics research and applications
Constructing large conservative supertrees
WABI'11 Proceedings of the 11th international conference on Algorithms in bioinformatics
COCOON'07 Proceedings of the 13th annual international conference on Computing and Combinatorics
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A rogue taxon in a collection of phylogenetic trees is one whose position varies drastically from tree to tree. The presence of such taxa can greatly reduce the resolution of the consensus tree (e.g., the majority-rule or strict consensus) for a collection. The reduced consensus approach aims to identify and eliminate rogue taxa to produce more informative consensus trees. Given a collection of phylogenetic trees over the same leaf set, the goal is to find a set of taxa whose removal maximizes the number of internal edges in the consensus tree of the collection. We show that this problem is NP-hard for strict and majority-rule consensus. We give a polynomial-time algorithm for reduced strict consensus when the maximum degree of the strict consensus of the original trees is bounded. We describe exact integer linear programming formulations for computing reduced strict, majority and loose consensus trees. In experimental tests, our exact solutions improved over heuristic methods on several problem instances.