{"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/a-clustering-tool-for-nucleotide-sequences","title":"A clustering tool for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Models","arxiv_id":"1610.08227","date":"2016-10-26","proceeding":null,"authors":[],"abstract":"We propose a new procedure for clustering nucleotide sequences based on the\n\"Laplacian Eigenmaps\" and Gaussian Mixture modelling. This proposal is then\napplied to a set of 100 DNA sequences from the mitochondrially encoded NADH\ndehydrogenase 3 (ND3) gene of a collection of Platyhelminthes and Nematoda\nspecies. The resulting clusters are then shown to be consistent with the gene\nphylogenetic tree computed using a maximum likelihood approach. This comparison\nshows in particular that the clustering produced by the methodology combining\nLaplacian Eigenmaps with Gaussian Mixture models is coherent with the phylogeny\nas well as with the NCBI taxonomy. We also developed a Python package for this\nprocedure which is available online.","url_abs":"http://arxiv.org/abs/1610.08227v1","url_pdf":"http://arxiv.org/pdf/1610.08227v1.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":"a-clustering-tool-for-nucleotide-sequences","repo_url":"https://github.com/SergeMOULIN/clustering-tool-for-nucleotide-sequences-using-Laplacian-Eigenmaps-and-Gaussian-Mixture-Models","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}