Take a look at the new version of this page: [ beta version ]. Tell us what you think.

ABSTRACT

Heuristics for calculating phylogenetic trees for a large sets of aligned rRNA sequences based on the maximum likelihood method are computationally expensive. The core of most parallel algorithms, which accounts for the greatest part of computation time, is the tree evaluation function, that calculates the likelihood value for each tree topology. This paper describes and uses Subtree Equality Vectors (SEVs) to reduce the number of required floating point operations during topology evaluation.We integrated our optimizations into various sequential programs and into parallel fastDNAml, one of the most common and efficient parallel programs for calculating large phylogenetic trees.Experimental results for our parallel program, which renders exactly the same output as parallel fastDNAml show global run time improvements of 26% to 65%. The optimization scales best on clusters of PCs, which also implies a substantial cost saving factor for the determination of large trees.

REFERENCES

• 1: Hans L. Bodlaender , Michael R. Fellows , Michael T. Hallett , H. Todd Wareham , Tandy J. Warnow, The hardness of perfect phylogeny, feasible register assignment and other problems on thin colored graphs, Theoretical Computer Science, v.244 n.1-2, p.167-188, Aug. 6, 2000 [doi>10.1016/S0304-3975(98)00342-9]
• 2: C. Ceron , J. Dopazo , E. L. Zapata , J. M. Carazo , O. Trelles, Parallel implementation of DNAm1 program on message-passing architectures, Parallel Computing, v.24 n.5-6, p.701-716, June 1998 [doi>10.1016/S0167-8191(98)00002-7]
• 3: fastDNAml Distribution: http://geta.life.uiuc.edu/~gary/programs/fastDNAml.html
• 4: Felsenstein, J. 1981. Evolutionary trees from DNA sequences: A maximum likelihood approach. J. Mol. Evol. 17: 368--376.
• 5: HEidelberg LInux Cluster System: http://helics.uni-hd.de
• 6: Höchstleistungsrechner in Bayern (HLRB): The Hitachi SR8000-F1: http://www.lrz-muenchen.de/services/compute/hlrb
• 7: Jermiin, L.S., Olsen, G.J., Mengersen, K.L. and Easteal, S. 1997. Majority-rule consensus of phylogenetic trees obtained by maximum-likelihood analysis. Mol. Biol. Evol. 14: 1297--1302.
• 8: Sampath Kannan , Tandy Warnow, A Fast Algorithm for the Computation and Enumeration of Perfect Phylogenies, SIAM Journal on Computing, v.26 n.6, p.1749-1763, Dec. 1997 [doi>10.1137/S0097539794279067]
• 9: Korber, B., Muldoon, M., Theiler, J., Gao, F., Gupta, R., Lapedes, A., Hahn, B.H., Wolinsky, S., and Bhattacharya, T. June 2000. Timing the ancestor of the HIV-1 pandemic strains. Science 288: 1789--1796.
• 10: Olsen, G.J., Matsuda, H., Hagstrom, R., and Overbeek, R. 1994. fastDNAml: A tool for construction of phylogenetic trees of DNA sequences using maximum likelihood. Comput. Appl. Biosci. 10: 41--48.
• 11: Alexandros P. Stamatakis , Thomas Ludwig , Harald Meier , Marty J. Wolf, AxML: A Fast Program for Sequential and Parallel Phylogenetic Tree Calculations Based on the Maximum Likelihood Method, Proceedings of the IEEE Computer Society Conference on Bioinformatics, p.21, August 14-16, 2002
• 12: Craig A. Stewart , David Hart , Donald K. Berry , Gary J. Olsen , Eric A. Wernert , William Fischer, Parallel implementation and performance of fastDNAml: a program for maximum likelihood phylogenetic inference, Proceedings of the 2001 ACM/IEEE conference on Supercomputing (CDROM), p.20-20, November 10-16, 2001, Denver, Colorado [doi>10.1145/582034.582054]
• 13: Stewart, C.A., Tan, T.W., Buchhorn, M., Hart, D., Berry, D., Zhang L., Wernert, E., Sakharkar, M., Fisher, W., and McMullen, D. 1999. Evolutionary biology and computational grids. IBM CASCON 1999 Computational Biology Workshop: Software Tools for Computational Biology.
• 14: The ARB project: http://www.arb-home.de
• 15: The PHYLogeny Inference Package: http://evolution.genetics.washington.edu/phylip.html
• 16: Top 500 supercomputer sites: http://www.top500.org/list/2002/06
• 17: Wolf, M.J., Easteal, S., Kahn, M. McKay, B.D., and Jermiin, L.S. 2000. TrExML: A maximum likelihood program for extensive tree-space exploration. Bioinformatics 16:383--394.

INDEX TERMS

Primary Classification:
  E. Data
  E.1 DATA STRUCTURES
      Subjects: Trees

Additional Classification:
  G. Mathematics of Computing
  G.1 NUMERICAL ANALYSIS
      G.1.0 General
          Subjects: Parallel algorithms
  G.2 DISCRETE MATHEMATICS
      G.2.2 Graph Theory
          Subjects: Trees

  I. Computing Methodologies
  I.1 SYMBOLIC AND ALGEBRAIC MANIPULATION
      I.1.2 Algorithms
          Subjects: Analysis of algorithms
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Graph and tree search strategies

General Terms:
Algorithms, Design, Measurement