Faster scaling algorithms for network problems
SIAM Journal on Computing
Kaikoura tree theorems: computing the maximum agreement subtree
Information Processing Letters
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
Fast comparison of evolutionary trees
SODA '94 Proceedings of the fifth annual ACM-SIAM symposium on Discrete algorithms
The Complexity of Some Problems on Subsequences and Supersequences
Journal of the ACM (JACM)
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
On Nakhleh's Metric for Reduced Phylogenetic Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Metrics on Multilabeled Trees: Interrelationships and Diameter Bounds
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Computing a Smallest Multilabeled Phylogenetic Tree from Rooted Triplets
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Algorithms for building consensus MUL-trees
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
Generating functions for multi-labeled trees
Discrete Applied Mathematics
Extracting conflict-free information from multi-labeled trees
WABI'12 Proceedings of the 12th international conference on Algorithms in Bioinformatics
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Identifying common patterns among area cladograms that arise in historical biogeography is an important tool for biogeographical inference. We develop the first rigorous formalization of these pattern-identification problems. We develop metrics to compare area cladograms. We define the maximum agreement area cladogram (MAAC) and we develop efficient algorithms for finding the MAAC of two area cladograms, while showing that it is NP-hard to find the MAAC of several binary area cladograms. We also describe a linear-time algorithm to identify if two area cladograms are identical.