Computing Refined Buneman Trees in Cubic Time
DOI:
https://doi.org/10.7146/brics.v9i51.21766Resumé
Reconstructing the evolutionary tree for a set of n species based on pairwise distances between the species is a fundamental problem in bioinformatics. Neighbour joining is a popular distance based tree reconstruction method. It always proposes fully resolved binary trees despite missing evidence in the underlying distance data. Distance based methods based on the theory of Buneman trees and refined Buneman trees avoid this problem by only proposing evolutionary trees whose edges satisfy a number of constraints. These trees might not be fully resolved but there is strong combinatorial evidence for each proposed edge. The currently best algorithm for computing the refined Buneman tree from a given distance measure has a running time of O(n^5) and a space consumption of O(n^4). In this paper, we present an algorithm with running time O(n^3) and space consumption O(n^2).Downloads
Publiceret
2002-12-05
Citation/Eksport
Brodal, G. S., Fagerberg, R., Östlin, A., Pedersen, C. N. S., & Rao, S. S. (2002). Computing Refined Buneman Trees in Cubic Time. BRICS Report Series, 9(51). https://doi.org/10.7146/brics.v9i51.21766
Nummer
Sektion
Artikler
Licens
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).