Implementation of a parallel processing system for inference of phylogenetic trees

Hideo Matsuda; Gary J. Olsen; Ray Hagstrom; Ross Overbeek; Yukio Kaneda

Implementation of a parallel processing system for inference of phylogenetic trees

Hideo Matsuda, Gary J. Olsen, Ray Hagstrom, Ross Overbeek, Yukio Kaneda

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper reports a parallel processing system for inference of phylogenetic trees. The trees are inferred from DNA sequence data by using a maximum likelihood method based on a stochastic model of the evolutional process. This method gives a good representation of the trees, but the computational cost has hindered the use of this method for inferring trees with more than about 20 species. By a parallel processing method based on a function partitioning approach, we achieved to reduce the cost significantly and obtained the phylogenetic tree of several hundreds of species on a massively parallel machine.

Original language	English (US)
Title of host publication	IEEE Pac Rim Conf Commun Comput Signal Process
Publisher	Publ by IEEE
Pages	280-283
Number of pages	4
ISBN (Print)	0780312198
State	Published - 1993
Externally published	Yes
Event	Proceedings of the IEEE 1993 Pacific Rim Conference on Communications, Computers and Signal Processing - Victoria, BC, Can Duration: May 19 1993 → May 21 1993

Publication series

Name	IEEE Pac Rim Conf Commun Comput Signal Process

Other

Other	Proceedings of the IEEE 1993 Pacific Rim Conference on Communications, Computers and Signal Processing
City	Victoria, BC, Can
Period	5/19/93 → 5/21/93

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

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Matsuda, H, Olsen, GJ, Hagstrom, R, Overbeek, R & Kaneda, Y 1993, Implementation of a parallel processing system for inference of phylogenetic trees. in IEEE Pac Rim Conf Commun Comput Signal Process. IEEE Pac Rim Conf Commun Comput Signal Process, Publ by IEEE, pp. 280-283, Proceedings of the IEEE 1993 Pacific Rim Conference on Communications, Computers and Signal Processing, Victoria, BC, Can, 5/19/93.

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AB - This paper reports a parallel processing system for inference of phylogenetic trees. The trees are inferred from DNA sequence data by using a maximum likelihood method based on a stochastic model of the evolutional process. This method gives a good representation of the trees, but the computational cost has hindered the use of this method for inferring trees with more than about 20 species. By a parallel processing method based on a function partitioning approach, we achieved to reduce the cost significantly and obtained the phylogenetic tree of several hundreds of species on a massively parallel machine.

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ER -

Implementation of a parallel processing system for inference of phylogenetic trees

Abstract

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