TY - GEN
T1 - Solving Large Scale Phylogenetic Problems using DCM2
AU - Huson, Daniel H.
AU - Vawter, Lisa
AU - Warnow, Tandy J.
N1 - Publisher Copyright:
Copyright © 1999 American Association for Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 1999
Y1 - 1999
N2 - In an earlier paper, we described a new method for phylogenetic tree reconstruction called the Disk Covering Method, or DCM. This is a general method which can be used with any existing phylogenetic method in order to improve its performance. We showed analytically and experimentally that when DCM is used in conjunction with polynomial time distance-based methods, it improves the accuracy of the trees reconstructed. In this paper, we discuss a variant on DCM, that we call DCM2. DCM2 is designed to be used with phylogenetic methods whose objective is the solution of NP-hard optimization problems. We show that DCM2 can be used to accelerate searches for Maximum Parsimony trees. We also motivate the need for solutions to NP-hard optimization problems by showing that on some very large and important datasets, the most popular (and presumably best performing) polynomial time distance methods have poor accuracy.
AB - In an earlier paper, we described a new method for phylogenetic tree reconstruction called the Disk Covering Method, or DCM. This is a general method which can be used with any existing phylogenetic method in order to improve its performance. We showed analytically and experimentally that when DCM is used in conjunction with polynomial time distance-based methods, it improves the accuracy of the trees reconstructed. In this paper, we discuss a variant on DCM, that we call DCM2. DCM2 is designed to be used with phylogenetic methods whose objective is the solution of NP-hard optimization problems. We show that DCM2 can be used to accelerate searches for Maximum Parsimony trees. We also motivate the need for solutions to NP-hard optimization problems by showing that on some very large and important datasets, the most popular (and presumably best performing) polynomial time distance methods have poor accuracy.
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M3 - Conference contribution
C2 - 10786294
AN - SCOPUS:0033289315
T3 - Proceedings of the 7th International Conference on Intelligent Systems for Molecular Biology, ISMB 1999
SP - 118
EP - 129
BT - Proceedings of the 7th International Conference on Intelligent Systems for Molecular Biology, ISMB 1999
PB - American Association for Artificial Intelligence (AAAI) Press
T2 - 7th International Conference on Intelligent Systems for Molecular Biology, ISMB 1999
Y2 - 6 August 1999 through 10 August 1999
ER -