{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:04:18Z","timestamp":1755219858377,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>We have built PLASMIDITY, an automated pipeline to assemble short reads and characterize contigs searching for biologically relevant features for plasmid sequences detection applying machine learning methods, including contig length, multiplicity, circularity, insertion sequence composition, chromosome markers (rRNA, tRNA), plasmid markers (OriV, Rep, Mob\/Rlx), G+C% variation, similarity with plasmid references, and k-mer profile. Using simulated WGS reads from 200 taxonomically diverse samples, we trained two Gradient Boosting classifiers, achieving a maximum F1 score of 0.901 in the test dataset. The comparison of the models against other plasmid prediction tools shows an improvement in the outcomes.<\/jats:p>","DOI":"10.3233\/shti251083","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:40:27Z","timestamp":1754566827000},"source":"Crossref","is-referenced-by-count":0,"title":["Plasmidity: A Novel Pipeline for Plasmid Sequence Prediction"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6423-4821","authenticated-orcid":false,"given":"Rosalia","family":"Palomino-Cabrera","sequence":"first","affiliation":[{"name":"Servicio de Microbiolog\u00eda H. U. Marqu\u00e9s de Valdecilla \u2013 IDIVAL, Santander, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8939-3271","authenticated-orcid":false,"given":"Inmaculada","family":"Garcia Romero","sequence":"additional","affiliation":[{"name":"Centro Andaluz de Biolog\u00eda del Desarrollo, CSIC-Universidad Pablo de Olavide, Sevilla, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8229-3641","authenticated-orcid":false,"given":"Miguel A.","family":"Valvano","sequence":"additional","affiliation":[{"name":"Wellcome-Wolfson Institute for Experimental Medicine, Queen\u2019s University Belfast, Belfast, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3011-0940","authenticated-orcid":false,"given":"Guillermo H.","family":"Lopez-Campos","sequence":"additional","affiliation":[{"name":"Wellcome-Wolfson Institute for Experimental Medicine, Queen\u2019s University Belfast, Belfast, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI251083","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:40:27Z","timestamp":1754566827000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251083"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251083","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}