Abstract
We consider the problem of fitting an n x n distance matrix D by a tree metric T. This problem is NP-hard for most reasonable distance functions between D and T. Recently, an approximation algorithm was presented (Agarwala et al., 1996) which achieves a factor of 3 approximation to the L∞ best fitting tree. We call this method the Single Pivot (SP) heuristic. Within the biology community, the so-called Neighbor-Joining (NJ) heuristic (Saitou and Nei, 1987) has wide acceptance. In this paper, we introduced a new Double Pivot (DP) heuristic, which is an extension of the SP heuristic, and show that DP outperforms NJ on biological and random data.
Original language | English (US) |
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Pages (from-to) | 547-558 |
Number of pages | 12 |
Journal | Journal of Computational Biology |
Volume | 4 |
Issue number | 4 |
DOIs | |
State | Published - 1997 |
Keywords
- Clustering analysis
- Numerical taxonomy
- Phylogenetic trees
ASJC Scopus subject areas
- Modeling and Simulation
- Molecular Biology
- Genetics
- Computational Mathematics
- Computational Theory and Mathematics