Maximum bounded 3-dimensional matching is MAX SNP-complete
Information Processing Letters
Kaikoura tree theorems: computing the maximum agreement subtree
Information Processing Letters
On the agreement of many trees
Information Processing Letters
Fast comparison of evolutionary trees
Information and Computation
Sparse Dynamic Programming for Evolutionary-Tree Comparison
SIAM Journal on Computing
General techniques for comparing unrooted evolutionary trees
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Maximum Agreement Subtree in a Set of Evolutionary Trees: Metrics and Efficient Algorithms
SIAM Journal on Computing
Tree Contractions and Evolutionary Trees
SIAM Journal on Computing
An O(n log n) algorithm for the maximum agreement subtree problem for binary trees
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
An O(nlog n) Algorithm for the Maximum Agreement Subtree Problem for Binary Trees
SIAM Journal on Computing
Computing the Unrooted Maximum Agreement Subtree in Sub-quadratic Time
SWAT '96 Proceedings of the 5th Scandinavian Workshop on Algorithm Theory
On the Approximability of the Maximum Common Subgraph Problem
STACS '92 Proceedings of the 9th Annual Symposium on Theoretical Aspects of Computer Science
FSTTCS'06 Proceedings of the 26th international conference on Foundations of Software Technology and Theoretical Computer Science
Hi-index | 0.00 |
The Maximum Isomorphic Agreement Subtree (MIT) problem is one of the simplest versions of the Maximum Interval Weight Agreement Subtree method (MIWT) which is used to compare phylogenies. More precisely MIT allows to provide a subset of the species such that the exact distances between species in such subset is preserved among all evolutionary trees considered. In this paper, the approximation complexity of the MIT problem is investigated, showing that it cannot be approximated in polynomial time within factor logδ n for any δ 0 unless NP ⊆ DTIME (2polylog n) for instances containing three trees. Moreover, we show that such result can be strengthened whenever instances of the MIT problem can contain an arbitrary number of trees, since MIT shares the same approximation lower bound of MAX CLIQUE.