Parallel multiple sequence alignment with decentralized cache support

Denis Trystram; Jaroslaw Zola

doi:10.1007/11549468_133

Parallel multiple sequence alignment with decentralized cache support

Denis Trystram
, Jaroslaw Zola

Department of Computer Science and Engineering

Laboratoire ID-IMAG

Research output: Contribution to journal › Conference article › peer-review

7 Scopus citations

Abstract

In this paper we present a new method for aligning large sets of biological sequences. The method performs a sequence alignment in parallel and uses a decentralized cache to store intermediate results. The method allows alignments to be recomputed efficiently when new sequences are added or when alignments of different precisions are requested. Our method can be used to solve important biological problems like the adaptive update of a complete evolution tree when new sequences are added (without recomputing the whole tree). To validate the method, some experiments were performed using up to 512 Small Subunit Ribosomal RNA sequences, which were analyzed with different levels of precision.

Original language	English
Pages (from-to)	1217-1226
Number of pages	10
Journal	Lecture Notes in Computer Science
Volume	3648
DOIs	https://doi.org/10.1007/11549468_133
State	Published - 2005
Event	11th International Euro-Par Conference, Euro-Par 2005 - Lisbon, Portugal Duration: Aug 30 2005 → Sep 2 2005

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title = "Parallel multiple sequence alignment with decentralized cache support",

abstract = "In this paper we present a new method for aligning large sets of biological sequences. The method performs a sequence alignment in parallel and uses a decentralized cache to store intermediate results. The method allows alignments to be recomputed efficiently when new sequences are added or when alignments of different precisions are requested. Our method can be used to solve important biological problems like the adaptive update of a complete evolution tree when new sequences are added (without recomputing the whole tree). To validate the method, some experiments were performed using up to 512 Small Subunit Ribosomal RNA sequences, which were analyzed with different levels of precision.",

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journal = "Lecture Notes in Computer Science",

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AU - Trystram, Denis

AU - Zola, Jaroslaw

PY - 2005

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N2 - In this paper we present a new method for aligning large sets of biological sequences. The method performs a sequence alignment in parallel and uses a decentralized cache to store intermediate results. The method allows alignments to be recomputed efficiently when new sequences are added or when alignments of different precisions are requested. Our method can be used to solve important biological problems like the adaptive update of a complete evolution tree when new sequences are added (without recomputing the whole tree). To validate the method, some experiments were performed using up to 512 Small Subunit Ribosomal RNA sequences, which were analyzed with different levels of precision.

AB - In this paper we present a new method for aligning large sets of biological sequences. The method performs a sequence alignment in parallel and uses a decentralized cache to store intermediate results. The method allows alignments to be recomputed efficiently when new sequences are added or when alignments of different precisions are requested. Our method can be used to solve important biological problems like the adaptive update of a complete evolution tree when new sequences are added (without recomputing the whole tree). To validate the method, some experiments were performed using up to 512 Small Subunit Ribosomal RNA sequences, which were analyzed with different levels of precision.

UR - https://www.scopus.com/pages/publications/27144534891

U2 - 10.1007/11549468_133

DO - 10.1007/11549468_133

M3 - Conference article

AN - SCOPUS:27144534891

SN - 0302-9743

VL - 3648

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EP - 1226

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

T2 - 11th International Euro-Par Conference, Euro-Par 2005

Y2 - 30 August 2005 through 2 September 2005

ER -

Parallel multiple sequence alignment with decentralized cache support

Abstract

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