{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/ultra-large-alignments-using-phylogeny-aware","title":"Ultra-large alignments using Phylogeny-aware Profiles","arxiv_id":"1504.01142","date":"2015-04-05","proceeding":null,"authors":["Nam-phuong Nguyen","Siavash Mirarab","Keerthana Kumar","Tandy Warnow"],"abstract":"Many biological questions, including the estimation of deep evolutionary\nhistories and the detection of remote homology between protein sequences, rely\nupon multiple sequence alignments (MSAs) and phylogenetic trees of large\ndatasets. However, accurate large-scale multiple sequence alignment is very\ndifficult, especially when the dataset contains fragmentary sequences. We\npresent UPP, an MSA method that uses a new machine learning technique - the\nEnsemble of Hidden Markov Models - that we propose here. UPP produces highly\naccurate alignments for both nucleotide and amino acid sequences, even on\nultra-large datasets or datasets containing fragmentary sequences. UPP is\navailable at https://github.com/smirarab/sepp.","url_abs":"http://arxiv.org/abs/1504.01142v1","url_pdf":"http://arxiv.org/pdf/1504.01142v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"ultra-large-alignments-using-phylogeny-aware","repo_url":"https://github.com/smirarab/sepp","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"multiple-sequence-alignment","task_name":"Multiple Sequence Alignment"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}