TY - JOUR
T1 - A few logs suffice to build (almost) all trees
T2 - Part II
AU - Erdos, Péter L.
AU - Steel, Michael A.
AU - Székely, László A.
AU - Warnow, Tandy J.
N1 - Funding Information:
We thank Scott Nettles for fruitful discussions of efficient implementations, and David Bryant and l~va Czabarka for proof reading the manuscript. We also thank A. Ambainis and another (anonymous) referee, for their careful reading of the manuscript and helpful suggestions for improving the exposition. P&er L. Erdfs was supported in part by the Hungarian National Science Fund contract T 016 358. L~iszl6 A. Szrkely was supported by the National Science Foundation grant DMS 970121 l, the Hungarian National Science Fund contracts T 016 358 and T 019 367, and European Communities (Cooperation in Science and Technology with Central and Eastern European Countries) contract ERBCIPACT 930 113. Michael A. Steel was supported by the New Zealand Marsden Fund and the New Zealand Ministry of Research, Science and Technology. Tandy J. Warnow was supported by an NSF Young Investigator Award CCR-9457800, a David and Lucille Packard Foundation fellowship, and generous research support from the Penn Research Foundation and Paul Angello. This research started in 1995 when the authors enjoyed the hospitality of DIMACS during the Special Year for Mathematical Support to Molecular Biology, and was completed in 1997 while enjoying the hospitality of Andreas Dress, at Universitiit Bielefeld, in Germany.
PY - 1999/6/28
Y1 - 1999/6/28
N2 - Inferring evolutionary trees is an interesting and important problem in biology, but one that is computationally difficult as most associated optimization problems are NP-hard. Although many methods are provably statistically consistent (i.e. the probability of recovering the correct tree converges to 1 as the sequence length increases), the actual rate of convergence for different methods has not been well understood. In a recent paper we introduced a new method for reconstructing evolutionary trees called the dyadic closure method (DCM), and we showed that DCM has a very fast convergence rate. DCM runs in O(n5log n) time, where n is the number of sequences, and so, although polynomial, the computational requirements are potentially too large to be of use in practice. In this paper we present another tree reconstruction method, the witness-antiwitness method (WAM). WAM is faster than DCM, especially on random trees, and converges to the true tree topology at the same rate as DCM. We also compare WAM to other methods used to reconstruct trees, including Neighbor Joining (possibly the most popular method among molecular biologists), and new methods introduced in the computer science literature.
AB - Inferring evolutionary trees is an interesting and important problem in biology, but one that is computationally difficult as most associated optimization problems are NP-hard. Although many methods are provably statistically consistent (i.e. the probability of recovering the correct tree converges to 1 as the sequence length increases), the actual rate of convergence for different methods has not been well understood. In a recent paper we introduced a new method for reconstructing evolutionary trees called the dyadic closure method (DCM), and we showed that DCM has a very fast convergence rate. DCM runs in O(n5log n) time, where n is the number of sequences, and so, although polynomial, the computational requirements are potentially too large to be of use in practice. In this paper we present another tree reconstruction method, the witness-antiwitness method (WAM). WAM is faster than DCM, especially on random trees, and converges to the true tree topology at the same rate as DCM. We also compare WAM to other methods used to reconstruct trees, including Neighbor Joining (possibly the most popular method among molecular biologists), and new methods introduced in the computer science literature.
KW - Distance-based methods
KW - Dyadic closure method
KW - Evolutionary tree reconstruction
KW - Phylogeny
KW - Quartet methods
KW - Short quartet methods
KW - Witness-antiwitness method
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U2 - 10.1016/S0304-3975(99)00028-6
DO - 10.1016/S0304-3975(99)00028-6
M3 - Article
AN - SCOPUS:0001860411
SN - 0304-3975
VL - 221
SP - 77
EP - 118
JO - Theoretical Computer Science
JF - Theoretical Computer Science
IS - 1-2
ER -