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Paolo Di Tommaso

dblp:35/3822 · DBLP profile ↗
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5ranked-venue papers
1as first author
2since 2021 · last 2026
0000-0003-3220-0253ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 4 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

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
3 papers
Bioinformatics and computational biology · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

Topics — the 9 heaviest of 10, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
phylogenetics
0.512021
Incorporating alignment uncertainty into Felsenstein's phylogenetic bootstrap to improve its reliability · Bioinform. 2021
Bioinformatics and computational biology › phylogenetics › statistical phylogenetics
phylogenetic bootstrap
0.512021
Incorporating alignment uncertainty into Felsenstein's phylogenetic bootstrap to improve its reliability · Bioinform. 2021
Bioinformatics and computational biology › protein function prediction
antimicrobial peptide prediction
0.112012
AMPA: an automated web server for prediction of protein antimicrobial regions · Bioinform. 2012
Bioinformatics and computational biology
protein function prediction
0.112012
AMPA: an automated web server for prediction of protein antimicrobial regions · Bioinform. 2012
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
Bioinformatics and computational biology
protein sequence analysis
0.012012
AMPA: an automated web server for prediction of protein antimicrobial regions · Bioinform. 2012
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

multiple sequence alignment · 0.5bootstrap sampling · 0.5t-coffee · 0.2parallel consistency-based alignment · 0.2machine learning · 0.1
YearPublicationVenuePosition
2026 A terminology for scientific workflow systems
Frédéric Suter, Tainã Coleman, Ilkay Altintas, Rosa M. Badia, Bartosz Balis, Kyle Chard, Iacopo Colonnelli, Ewa Deelman, Paolo Di Tommaso, Thomas Fahringer, Carole A. Goble, Shantenu Jha, Daniel S. Katz, Johannes Köster, Ulf Leser, Kshitij Mehta, Hilary Oliver, Jayson Luc Peterson, Giovanni Pizzi, Loïc Pottier, Raül Sirvent, Eric Suchyta, Douglas Thain, Sean R. Wilkinson, Justin M. Wozniak, Rafael Ferreira da Silva
Future Gener. Comput. Syst.9
2021 Incorporating alignment uncertainty into Felsenstein's phylogenetic bootstrap to improve its reliability
abstract
MOTIVATION: Most evolutionary analyses are based on pre-estimated multiple sequence alignment. Wong et al. established the existence of an uncertainty induced by multiple sequence alignment when reconstructing phylogenies. They were able to show that in many cases different aligners produce different phylogenies, with no simple objective criterion sufficient to distinguish among these alternatives. RESULTS: We demonstrate that incorporating MSA induced uncertainty into bootstrap sampling can significantly increase correlation between clade correctness and its corresponding bootstrap value. Our procedure involves concatenating several alternative multiple sequence alignments of the same sequences, produced using different commonly used aligners. We then draw bootstrap replicates while favoring columns of the more unique aligner among the concatenated aligners. We named this concatenation and bootstrapping method, Weighted Partial Super Bootstrap (wpSBOOT). We show on three simulated datasets of 16, 32 and 64 tips that our method improves the predictive power of bootstrap values. We also used as a benchmark an empirical collection of 853 one to one orthologous genes from seven yeast species and found wpSBOOT to significantly improve discrimination capacity between topologically correct and incorrect trees. Bootstrap values of wpSBOOT are comparable to similar readouts estimated using a single method. However, for reduced trees by 50 and 95% bootstrap thresholds, wpSBOOT comes out the lowest Type I error (less FP). AVAILABILITY AND IMPLEMENTATION: The automated generation of replicates has been implemented in the T-Coffee package, which is available as open source freeware available from www.tcoffee.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Jia-Ming Chang, Evan W. Floden, Javier Herrero, Olivier Gascuel, Paolo Di Tommaso, Cédric Notredame
Bioinform.5
2012 AMPA: an automated web server for prediction of protein antimicrobial regions
abstract
SUMMARY: AMPA is a web application for assessing the antimicrobial domains of proteins, with a focus on the design on new antimicrobial drugs. The application provides fast discovery of antimicrobial patterns in proteins that can be used to develop new peptide-based drugs against pathogens. Results are shown in a user-friendly graphical interface and can be downloaded as raw data for later examination. AVAILABILITY: AMPA is freely available on the web at http://tcoffee.crg.cat/apps/ampa. The source code is also available in the web. CONTACT: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Marc Torrent Burgas, Paolo Di Tommaso, David Pulido, Victòria M. Nogués, Cédric Notredame, Ester Boix, David Andreu 0002
Bioinform.2
2012 Accurate multiple sequence alignment of transmembrane proteins with PSI-Coffee
abstract
BACKGROUND: Transmembrane proteins (TMPs) constitute about 20~30% of all protein coding genes. The relative lack of experimental structure has so far made it hard to develop specific alignment methods and the current state of the art (PRALINE™) only manages to recapitulate 50% of the positions in the reference alignments available from the BAliBASE2-ref7. METHODS: We show how homology extension can be adapted and combined with a consistency based approach in order to significantly improve the multiple sequence alignment of alpha-helical TMPs. TM-Coffee is a special mode of PSI-Coffee able to efficiently align TMPs, while using a reduced reference database for homology extension. RESULTS: Our benchmarking on BAliBASE2-ref7 alpha-helical TMPs shows a significant improvement over the most accurate methods such as MSAProbs, Kalign, PROMALS, MAFFT, ProbCons and PRALINE™. We also estimated the influence of the database used for homology extension and show that highly non-redundant UniRef databases can be used to obtain similar results at a significantly reduced computational cost over full protein databases. TM-Coffee is part of the T-Coffee package, a web server is also available from http://tcoffee.crg.cat/tmcoffee and a freeware open source code can be downloaded from http://www.tcoffee.org/Packages/Stable/Latest.
Jia-Ming Chang, Paolo Di Tommaso, Jean-François Taly, Cédric Notredame
BMC Bioinform.2
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.1