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Justin Ebedes

dblp:57/4901 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2004
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 67% High-performance computing · 33%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
multiple sequence alignment
0.012004
Multiple sequence alignment in parallel on a workstation cluster · Bioinform. 2004
Bioinformatics and computational biology
sequence analysis
0.012004
Multiple sequence alignment in parallel on a workstation cluster · Bioinform. 2004
Parallel and multicore computing › parallel programming models
message passing
0.012004
Multiple sequence alignment in parallel on a workstation cluster · Bioinform. 2004
High-performance computing › cluster computing
network of workstations
0.012004
Multiple sequence alignment in parallel on a workstation cluster · Bioinform. 2004
Parallel and multicore computing
parallel computing
0.012004
Multiple sequence alignment in parallel on a workstation cluster · Bioinform. 2004

Methods — techniques the papers use, named apart from their topics

message passing interface · 0.1guide tree · 0.1distance matrix · 0.1
YearPublicationVenuePosition
2004 Multiple sequence alignment in parallel on a workstation cluster
abstract
SUMMARY: Multiple sequence alignment is the NP-hard problem of aligning three or more DNA or amino acid sequences in an optimal way so as to match as many characters as possible from the set of sequences. The popular sequence alignment program ClustalW uses the classical method of approximating a sequence alignment, by first computing a distance matrix and then constructing a guide tree to show the evolutionary relationship of the sequences. We show that parallelizing the ClustalW algorithm can result in significant speedup. We used a cluster of workstations using C and message passing interface for our implementation. Experimental results show that speedup of over 5.5 on six processors is obtainable for most inputs. AVAILABILITY: The software is available upon request from the second author.
Justin Ebedes, Amitava Datta
Bioinform.1