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Algorithms 2013, 6(3), 396-406; doi:10.3390/a6030396

New Heuristics for Rooted Triplet Consistency

Tazehkand 1,2,* , 1
 and 3
Received: 14 April 2013; in revised form: 26 June 2013 / Accepted: 26 June 2013 / Published: 11 July 2013
(This article belongs to the Special Issue Graph Algorithms)
Download PDF [222 KB, uploaded 11 July 2013]
Abstract: Rooted triplets are becoming one of the most important types of input for reconstructing rooted phylogenies. A rooted triplet is a phylogenetic tree on three leaves and shows the evolutionary relationship of the corresponding three species. In this paper, we investigate the problem of inferring the maximum consensus evolutionary tree from a set of rooted triplets. This problem is known to be APX-hard. We present two new heuristic algorithms. For a given set of m triplets on n species, the FastTree algorithm runs in O(m + α(n)n2) time, where α(n) is the functional inverse of Ackermann’s function. This is faster than any other previously known algorithms, although the outcome is less satisfactory. The Best Pair Merge with Total Reconstruction (BPMTR) algorithm runs in O(mn3) time and, on average, performs better than any other previously known algorithms for this problem.
Keywords: phylogenetic tree; rooted triplet; consensus tree; approximation algorithm phylogenetic tree; rooted triplet; consensus tree; approximation algorithm
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Jahangiri, S., Tazehkand; Hashemi, S.N.; Poormohammadi, H. New Heuristics for Rooted Triplet Consistency. Algorithms 2013, 6, 396-406.

AMA Style

Jahangiri S, Tazehkand, Hashemi SN, Poormohammadi H. New Heuristics for Rooted Triplet Consistency. Algorithms. 2013; 6(3):396-406.

Chicago/Turabian Style

Jahangiri, Soheil, Tazehkand; Hashemi, Seyed N.; Poormohammadi, Hadi. 2013. "New Heuristics for Rooted Triplet Consistency." Algorithms 6, no. 3: 396-406.

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