{"oa_version":"Published Version","date_created":"2023-05-23T16:08:20Z","related_material":{"record":[{"id":"7181","status":"public","relation":"used_in_publication"}]},"oa":1,"ddc":["570"],"day":"07","citation":{"short":"E. Garriga, P. di Tommaso, C. Magis, I. Erb, L. Mansouri, A. Baltzis, H. Laayouni, F. Kondrashov, E. Floden, C. Notredame, (2018).","apa":"Garriga, E., di Tommaso, P., Magis, C., Erb, I., Mansouri, L., Baltzis, A., … Notredame, C. (2018). Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.2025846\">https://doi.org/10.5281/ZENODO.2025846</a>","ama":"Garriga E, di Tommaso P, Magis C, et al. Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method. 2018. doi:<a href=\"https://doi.org/10.5281/ZENODO.2025846\">10.5281/ZENODO.2025846</a>","ieee":"E. Garriga <i>et al.</i>, “Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method.” Zenodo, 2018.","chicago":"Garriga, Edgar, Paolo di Tommaso, Cedrik Magis, Ionas Erb, Leila Mansouri, Athanasios Baltzis, Hafid Laayouni, Fyodor Kondrashov, Evan Floden, and Cedric Notredame. “Fast and Accurate Large Multiple Sequence Alignments with a Root-to-Leaf Regressive Method.” Zenodo, 2018. <a href=\"https://doi.org/10.5281/ZENODO.2025846\">https://doi.org/10.5281/ZENODO.2025846</a>.","ista":"Garriga E, di Tommaso P, Magis C, Erb I, Mansouri L, Baltzis A, Laayouni H, Kondrashov F, Floden E, Notredame C. 2018. Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method, Zenodo, <a href=\"https://doi.org/10.5281/ZENODO.2025846\">10.5281/ZENODO.2025846</a>.","mla":"Garriga, Edgar, et al. <i>Fast and Accurate Large Multiple Sequence Alignments with a Root-to-Leaf Regressive Method</i>. Zenodo, 2018, doi:<a href=\"https://doi.org/10.5281/ZENODO.2025846\">10.5281/ZENODO.2025846</a>."},"title":"Fast and accurate large multiple sequence alignments with a root-to-leaf regressive method","department":[{"_id":"FyKo"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"date_updated":"2023-09-06T14:32:51Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"12","doi":"10.5281/ZENODO.2025846","author":[{"last_name":"Garriga","full_name":"Garriga, Edgar","first_name":"Edgar"},{"first_name":"Paolo","last_name":"di Tommaso","full_name":"di Tommaso, Paolo"},{"first_name":"Cedrik","full_name":"Magis, Cedrik","last_name":"Magis"},{"full_name":"Erb, Ionas","last_name":"Erb","first_name":"Ionas"},{"last_name":"Mansouri","full_name":"Mansouri, Leila","first_name":"Leila"},{"first_name":"Athanasios","last_name":"Baltzis","full_name":"Baltzis, Athanasios"},{"first_name":"Hafid","last_name":"Laayouni","full_name":"Laayouni, Hafid"},{"id":"44FDEF62-F248-11E8-B48F-1D18A9856A87","first_name":"Fyodor","full_name":"Kondrashov, Fyodor","orcid":"0000-0001-8243-4694","last_name":"Kondrashov"},{"full_name":"Floden, Evan","last_name":"Floden","first_name":"Evan"},{"full_name":"Notredame, Cedric","last_name":"Notredame","first_name":"Cedric"}],"status":"public","abstract":[{"lang":"eng","text":"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\".\r\nIt also contains the Multiple Sequence Alignments (MSAs) generated and well as the main figures and tables from the manuscript.\r\nThe repository is also available at GitHub (https://github.com/cbcrg/dpa-analysis) release `v1.2`.\r\nFor details on how to use the regressive alignment algorithm, see the T-Coffee software suite (https://github.com/cbcrg/tcoffee)."}],"article_processing_charge":"No","publisher":"Zenodo","date_published":"2018-12-07T00:00:00Z","type":"research_data_reference","main_file_link":[{"url":"https://doi.org/10.5281/zenodo.3271452","open_access":"1"}],"_id":"13059","year":"2018"}