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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).
FOS: Computer and information sciences, Regressive MSA, Bioinformatics, Genomics, Multiple Sequence Alignment
FOS: Computer and information sciences, Regressive MSA, Bioinformatics, Genomics, Multiple Sequence Alignment
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 18 | |
| downloads | 7 |

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