{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T15:26:20Z","timestamp":1787066780310,"version":"build-2736575974"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T00:00:00Z","timestamp":1724716800000},"content-version":"vor","delay-in-days":56,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Associating one or more Gene Ontology (GO) terms to a protein means making a statement about a particular functional characteristic of the protein. This association provides scientists with a snapshot of the biological context of the protein activity. This paper introduces PRONTO-TK, a Python-based software toolkit designed to democratize access to Neural-Network based complex protein function prediction workflows. PRONTO-TK is a user-friendly graphical interface (GUI) for empowering researchers, even those with minimal programming experience, to leverage state-of-the-art Deep Learning architectures for protein function annotation using GO terms. We demonstrate PRONTO-TK\u2019s effectiveness on a running example, by showing how its intuitive configuration allows it to easily generate complex analyses while avoiding the complexities of building such a pipeline from scratch.<\/jats:p>","DOI":"10.1093\/nargab\/lqae112","type":"journal-article","created":{"date-parts":[[2024,8,15]],"date-time":"2024-08-15T11:08:54Z","timestamp":1723720134000},"source":"Crossref","is-referenced-by-count":3,"title":["PRONTO-TK: a user-friendly PROtein Neural neTwOrk tool-kit for accessible protein function prediction"],"prefix":"10.1093","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5268-9899","authenticated-orcid":false,"given":"Gianfranco","family":"Politano","sequence":"first","affiliation":[{"name":"Department of Control and Computer Engineering, Politecnico di Torino ,\u00a0Torino, 10129, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3433-7739","authenticated-orcid":false,"given":"Alfredo","family":"Benso","sequence":"additional","affiliation":[{"name":"Department of Control and Computer Engineering, Politecnico di Torino ,\u00a0Torino, 10129, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3274-6347","authenticated-orcid":false,"given":"Hafeez Ur","family":"Rehman","sequence":"additional","affiliation":[{"name":"School of Computing and Data Sciences, Oryx Universal College with Liverpool John Moores University , Qatar"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3179-6967","authenticated-orcid":false,"given":"Angela","family":"Re","sequence":"additional","affiliation":[{"name":"Department of Applied Science and Technology, Politecnico di Torino ,Torino, 10129, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,8,27]]},"reference":[{"key":"2024082710441847100_B1","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1093\/nar\/28.1.304","article-title":"The ENZYME database in 2000","volume":"28","author":"Bairoch","year":"2000","journal-title":"Nucleic Acids Res."},{"key":"2024082710441847100_B2","doi-asserted-by":"crossref","first-page":"D353","DOI":"10.1093\/nar\/gkw1092","article-title":"KEGG: new perspectives on genomes, pathways, diseases and drugs","volume":"45","author":"Kanehisa","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"2024082710441847100_B3","doi-asserted-by":"crossref","first-page":"iyad031","DOI":"10.1093\/genetics\/iyad031","article-title":"The gene ontology knowledgebase in 2023","volume":"224","author":"Gene Ontology Consortium","year":"2023","journal-title":"Genetics"},{"key":"2024082710441847100_B4","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.tim.2019.10.010","article-title":"An Ecosystems perspective on virus evolution and emergence","volume":"28","author":"Rebecca K French and Edward C Holmes","year":"2020","journal-title":"Trends Microbiol."},{"key":"2024082710441847100_B5","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1016\/j.cell.2016.10.027","article-title":"The central nervous system and the gut microbiome","volume":"167","author":"Sharon","year":"2016","journal-title":"Cell"},{"key":"2024082710441847100_B6","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1038\/s41587-024-02127-0","article-title":"Machine learning for functional protein design","volume":"42","author":"Notin","year":"2024","journal-title":"Nat. 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