We study the agreement supertree approach for combining rooted phylogenetic trees when the input trees do not fully agree on the relative positions of the taxa. We consider two ways to deal with such conflict. The first is to contract a set of edges in the input trees so that the resulting trees have an agreement supertree. We show that this problem is NP-complete and give a fixed-parameter tractable (FPT) algorithm for the problem parameterized by the number of input trees and the number of edges contracted. The second approach is to remove a set of taxa from the input trees so that the resulting trees have an agreement supertree. Guillemot and Berry (2010) gave an FPT algorithm for this problem when the input trees are all binary. We give an FPT algorithm for the more general case where the input trees are allowed to have arbitrary degree.

Given two permutations σ and π, the Permutation Pattern problem asks if σ is a subpattern of π. We show that the problem can be solved in time 2O(ℓ2 log ℓ). n, where ℓ = |σ| and n = |π|. In other words, the problem is fixed-parameter tractable parameterized by the size of the subpattern to be found.

We investigate the computational complexity of inferring a smallest possible multilabeled phylogenetic tree (MUL tree) which is consistent with each of the rooted triplets in a given set. This problem has not been studied previously in the literature. We prove that even the very restricted case of determining if there exists a MUL tree consistent with the input and having just one leaf duplication is an NP-hard problem. Furthermore, we show that the general minimization problem is difficult to approximate, although a simple polynomial-time approximation algorithm achieves an approximation ratio close to our derived inapproximability bound. Finally, we provide an exact algorithm for the problem running in exponential time and space. As a by-product, we also obtain new, strong inapproximability results for two partitioning problems on directed graphs called ACYCLIC PARTITION and ACYCLIC TREE-PARTITION.

Given a set L of labels and a collection of rooted trees whose leaves are bijectively labeled by some elements of L, the Maximum Agreement Supertree (SMAST) problem is given as follows: find a tree T on a largest label set L(') is included in L that homeomorphically contains every input tree restricted to L('). The problem has phylogenetic applications to infer supertrees and perform tree congruence analyses. In this paper, we focus on the parameterized complexity of this NP-hard problem, considering different combinations of parameters as well as particular cases. We show that SMAST on k rooted binary trees on a label set of size n can be solved in O((8n)k) time, which is an improvement with respect to the previously known O(n3k2) time algorithm. In this case, we also give an O((2k)pkn2) time algorithm, where p is an upper bound on the number of leaves of L missing in a SMAST solution. This shows that SMAST can be solved efficiently when the input trees are mostly congruent. Then, for the particular case where any triple of leaves is contained in at least one input tree, we give O(4pn3) and O(3:12p + n4) time algorithms, obtaining the first fixed-parameter tractable algorithms on a single parameter for this problem. We also obtain intractability results for several combinations of parameters, thus indicating that it is unlikely that fixed-parameter tractable algorithms can be found in these particular cases.

Given a set of leaf-labeled trees with identical leaf sets, the well-known Maximum Agreement SubTree (MAST) problem consists in finding a subtree homeomorphically included in all input trees and with the largest number of leaves. MAST and its variant called Maximum Compatible Tree (MCT) are of particular interest in computational biology. This article presents a linear-time approximation algorithm to solve the complement version of MAST, namely identifying the smallest set of leaves to remove from input trees to obtain isomorphic trees. We also present an O ( n 2 + kn ) algorithm to solve the complement version of MCT. For both problems, we thus achieve significantly lower running times than previously known algorithms. Fast running times are especially important in phylogenetics where large collections of trees are routinely produced by resampling procedures, such as the nonparametric bootstrap or Bayesian MCMC methods.