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Automated Author Profile

Di Tommaso, Paolo

Centre for Genomic Regulation (CRG)
0000-0003-3220-0253

Current S-Index

4.3

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.1

Average Dataset Index per dataset

Total Datasets

4

Total datasets for this author

Average FAIR Score

45.2%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method (Version: v1.2)

This dataset contains a GitHub repository containing all the data, analysis, Nextflow workflows and Jupyter notebooks to replicate the manuscript titled "Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method". It also contains the Multiple Sequence Alignments (MSAs) generated and well as the main figures and tables from the manuscript. The repository is also available at GitHub (https://github.com/cbcrg/dpa-analysis) release v1.2. For details on how to use the regressive alignment algorithm, see the T-Coffee software suite (https://github.com/cbcrg/tcoffee).

Authors

  • Garriga Nogales, Edgar ;
  • Di Tommaso, Paolo ;
  • Magis, Cedrik ;
  • Erb, Ionas ;
  • Mansouri, Leila ;
  • Baltzis, Athanasios ;
  • Laayouni, Hafid ;
  • Kondrashov, Fyodor ;
  • Floden, Evan ;
  • Notredame, Cedric
0 Citations0 Mentions13% FAIR0.3 Dataset Index
10.5281/zenodo.2025846December 2018

Fast and accurate large multiple sequence alignments using root-to-leave regressive computation

This dataset contains a GitHub repository containing all the data, analysis, Nextflow workflows and Jupyter notebooks to replicate the manuscript titled "Fast and accurate large multiple sequence alignments using root-to-leave regressive computation".It also contains the Multiple Sequence Alignments (MSAs) generated and well as the main figures and tables from the manuscript.The repository is also available at GitHub (https://github.com/cbcrg/dpa-analysis) release v1.0.For details on how to use the regressive alignment algorithm, see the T-Coffee software suite (https://github.com/cbcrg/tcoffee).

Authors

  • Garriga Nogales, Edgar ;
  • Di Tommaso, Paolo ;
  • Magis, Cedrik ;
  • Erb, Ionas ;
  • Laayouni, Hafid ;
  • Kondrashov, Fyodor ;
  • Floden, Evan ;
  • Notredame, Cedric
0 Citations0 Mentions13% FAIR0.1 Dataset Index
10.5281/zenodo.2025847December 2018

Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method (Version: v1.1)

This dataset contains a GitHub repository containing all the data, analysis, Nextflow workflows and Jupyter notebooks to replicate the manuscript titled "Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method".It also contains the Multiple Sequence Alignments (MSAs) generated and well as the main figures and tables from the manuscript.The repository is also available at GitHub (https://github.com/cbcrg/dpa-analysis) release v1.1.For details on how to use the regressive alignment algorithm, see the T-Coffee software suite (https://github.com/cbcrg/tcoffee).

Authors

  • Garriga Nogales, Edgar ;
  • Di Tommaso, Paolo ;
  • Magis, Cedrik ;
  • Erb, Ionas ;
  • Laayouni, Hafid ;
  • Kondrashov, Fyodor ;
  • Floden, Evan ;
  • Notredame, Cedric
0 Citations0 Mentions77% FAIR1.9 Dataset Index
10.5281/zenodo.2555124December 2018

Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method (Version: v1.2)

This dataset contains a GitHub repository containing all the data, analysis, Nextflow workflows and Jupyter notebooks to replicate the manuscript titled "Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method". It also contains the Multiple Sequence Alignments (MSAs) generated and well as the main figures and tables from the manuscript. The repository is also available at GitHub (https://github.com/cbcrg/dpa-analysis) release v1.2. For details on how to use the regressive alignment algorithm, see the T-Coffee software suite (https://github.com/cbcrg/tcoffee).

Authors

  • Garriga Nogales, Edgar ;
  • Di Tommaso, Paolo ;
  • Magis, Cedrik ;
  • Erb, Ionas ;
  • Mansouri, Leila ;
  • Baltzis, Athanasios ;
  • Laayouni, Hafid ;
  • Kondrashov, Fyodor ;
  • Floden, Evan ;
  • Notredame, Cedric
0 Citations0 Mentions77% FAIR1.9 Dataset Index
10.5281/zenodo.3271452December 2018