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Toni Espinosa

dblp:99/8322 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › multiple sequence alignment
consistency-based alignment		 0.112010
Cloud-Coffee: implementation of a parallel consistency-based multiple alignment algorithm in the T-Coffee package and its benchmarking on the Amazon Elastic-Cloud · Bioinform. 2010
Bioinformatics and computational biology
multiple sequence alignment		 0.112010
Cloud-Coffee: implementation of a parallel consistency-based multiple alignment algorithm in the T-Coffee package and its benchmarking on the Amazon Elastic-Cloud · Bioinform. 2010
Bioinformatics and computational biology
sequence alignment		 0.112010
Cloud-Coffee: implementation of a parallel consistency-based multiple alignment algorithm in the T-Coffee package and its benchmarking on the Amazon Elastic-Cloud · Bioinform. 2010
Cloud and datacenter computing › cloud applications
cloud-based scientific computing		 0.012010
Cloud-Coffee: implementation of a parallel consistency-based multiple alignment algorithm in the T-Coffee package and its benchmarking on the Amazon Elastic-Cloud · Bioinform. 2010

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

t-coffee · 0.2parallel consistency-based alignment · 0.2
YearPublicationVenuePosition
2010 Cloud-Coffee: implementation of a parallel consistency-based multiple alignment algorithm in the T-Coffee package and its benchmarking on the Amazon Elastic-Cloud
abstract
SUMMARY: We present the first parallel implementation of the T-Coffee consistency-based multiple aligner. We benchmark it on the Amazon Elastic Cloud (EC2) and show that the parallelization procedure is reasonably effective. We also conclude that for a web server with moderate usage (10K hits/month) the cloud provides a cost-effective alternative to in-house deployment. AVAILABILITY: T-Coffee is a freeware open source package available from http://www.tcoffee.org/homepage.html
Paolo Di Tommaso, Miquel Orobitg, Fernando Guirado, Fernando Cores, Toni Espinosa, Cédric Notredame
 Bioinform.5