{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:07:58Z","timestamp":1781827678899,"version":"3.54.5"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"17","license":[{"start":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T00:00:00Z","timestamp":1657238400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,9,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Summary<\/jats:title><jats:p>Accurate prediction of the subcellular locations (SLs) of proteins is a critical topic in protein science. In this study, we present SLPred, an ensemble-based multi-view and multi-label protein subcellular localization prediction tool. For a query protein sequence, SLPred provides predictions for nine main SLs using independent machine-learning models trained for each location. We used UniProtKB\/Swiss-Prot human protein entries and their curated SL annotations as our source data. We connected all disjoint terms in the UniProt SL hierarchy based on the corresponding term relationships in the cellular component category of Gene Ontology and constructed a training dataset that is both reliable and large scale using the re-organized hierarchy. We tested SLPred on multiple benchmarking datasets including our-in house sets and compared its performance against six state-of-the-art methods. Results indicated that SLPred outperforms other tools in the majority of cases.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>SLPred is available both as an open-access and user-friendly web-server (https:\/\/slpred.kansil.org) and a stand-alone tool (https:\/\/github.com\/kansil\/SLPred). All datasets used in this study are also available at https:\/\/slpred.kansil.org.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac458","type":"journal-article","created":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T13:20:35Z","timestamp":1657286435000},"page":"4226-4229","source":"Crossref","is-referenced-by-count":6,"title":["SLPred: a multi-view subcellular localization prediction tool for multi-location human proteins"],"prefix":"10.1093","volume":"38","author":[{"given":"G\u00f6khan","family":"\u00d6zsar\u0131","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Middle East Technical University , Ankara 06800, Turkey"},{"name":"Department of Computer Engineering, Ni\u011fde \u00d6mer Halisdemir University , Ni\u011fde 51240, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmet Sureyya","family":"Rifaioglu","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, \u0130skenderun Technical University , Hatay 31200, Turkey"},{"name":"Faculty of Medicine, Institute for Computational Biomedicine, Heidelberg University and Heidelberg University Hospital , Heidelberg 69120, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmet","family":"Atakan","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Middle East Technical University , Ankara 06800, Turkey"},{"name":"Department of Computer Engineering, Erzincan Binali Y\u0131ld\u0131r\u0131m University , Erzincan 24002, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1298-9763","authenticated-orcid":false,"given":"Tunca","family":"Do\u011fan","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Hacettepe University , Ankara 06800, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5454-2815","authenticated-orcid":false,"given":"Maria Jesus","family":"Martin","sequence":"additional","affiliation":[{"name":"European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL\u2013EBI) , Cambridge, Hinxton CB10 1SD, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2408-6606","authenticated-orcid":false,"given":"Reng\u00fcl","family":"\u00c7etin Atalay","sequence":"additional","affiliation":[{"name":"Graduate School of Informatics Middle East Technical University , Ankara 06800, Turkey"},{"name":"Section of Pulmonary and Critical Care Medicine, the University of Chicago , Chicago, IL 60637, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7850-0601","authenticated-orcid":false,"given":"Volkan","family":"Atalay","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Middle East Technical University , Ankara 06800, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,7,8]]},"reference":[{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"3387","DOI":"10.1093\/bioinformatics\/btx431","article-title":"DeepLoc: prediction of protein subcellular localization using deep learning","volume":"33","author":"Almagro Armenteros","year":"2017","journal-title":"Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/75556","article-title":"Gene ontology: tool for the unification of biology","volume":"25","author":"Ashburner","year":"2000","journal-title":"Nat. Genet"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1186\/1471-2105-10-274","article-title":"MultiLoc2: integrating phylogeny and gene ontology terms improves subcellular protein localization prediction","volume":"10","author":"Blum","year":"2009","journal-title":"BMC Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"W497","DOI":"10.1093\/nar\/gkq477","article-title":"YLoc\u2014an interpretable web server for predicting subcellular localization","volume":"38","author":"Briesemeister","year":"2010","journal-title":"Nucleic Acids Res"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"2499","DOI":"10.1093\/bioinformatics\/bty140","article-title":"iFeature: a python package and web server for features extraction and selection from protein and peptide sequences","volume":"34","author":"Chen","year":"2018","journal-title":"Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1186\/s12859-018-2368-y","article-title":"ECPred: a tool for the prediction of the enzymatic functions of protein sequences based on the EC nomenclature","volume":"19","author":"Dalkiran","year":"2018","journal-title":"BMC Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"e5298","DOI":"10.7717\/peerj.5298","article-title":"HPO2GO: prediction of human phenotype ontology term associations for proteins using cross ontology annotation co-occurrences","volume":"6","author":"Do\u011fan","year":"2018","journal-title":"PeerJ"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"e1009171","DOI":"10.1371\/journal.pcbi.1009171","article-title":"Protein domain-based prediction of drug\/compound\u2013target interactions and experimental validation on LIM kinases","volume":"17","author":"Do\u011fan","year":"2021","journal-title":"PLoS Comput. Biol"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"e96","DOI":"10.1093\/nar\/gkab543","article-title":"CROssBAR: comprehensive resource of biomedical relations with knowledge graph representations","volume":"49","author":"Do\u011fan","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"i458","DOI":"10.1093\/bioinformatics\/bts390","article-title":"LocTree2 predicts localization for all domains of life","volume":"28","author":"Goldberg","year":"2012","journal-title":"Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"259","DOI":"10.12688\/f1000research.6670.1","article-title":"PHENOstruct: prediction of human phenotype ontology terms using heterogeneous data sources","volume":"4","author":"Kahanda","year":"2015","journal-title":"F1000Research"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1093\/bioinformatics\/btx624","article-title":"DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier","volume":"34","author":"Kulmanov","year":"2018","journal-title":"Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1093\/bioinformatics\/btx680","article-title":"DEEPre: sequence-based enzyme EC number prediction by deep learning","volume":"34","author":"Li","year":"2018","journal-title":"Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"D170","DOI":"10.1093\/nar\/gkw1081","article-title":"Uniclust databases of clustered and deeply annotated protein sequences and alignments","volume":"45","author":"Mirdita","year":"2017","journal-title":"Nucleic Acids Res"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1093\/bioinformatics\/btaa858","article-title":"MDeePred: novel multi-channel protein featurization for deep learning-based binding affinity prediction in drug discovery","volume":"37","author":"Rifaioglu","year":"2021","journal-title":"Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"2531","DOI":"10.1039\/C9SC03414E","article-title":"DEEPScreen: high performance drug\u2013target interaction prediction with convolutional neural networks using 2-D structural compound representations","volume":"11","author":"Rifaioglu","year":"2020","journal-title":"Chem. Sci"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"7344","DOI":"10.1038\/s41598-019-43708-3","article-title":"DEEPred: automated protein function prediction with multi-task feed-forward","volume":"9","author":"Rifaioglu","year":"2019","journal-title":"Sci. Rep"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"2464","DOI":"10.1093\/bioinformatics\/btx219","article-title":"SubCons: a new ensemble method for improved human subcellular localization predictions","volume":"33","author":"Salvatore","year":"2017","journal-title":"Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.compbiolchem.2007.11.004","article-title":"Subsequence-based feature map for protein function classification","volume":"32","author":"Sarac","year":"2008","journal-title":"Comput. Biol. Chem"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"D325","DOI":"10.1093\/nar\/gkaa1113","article-title":"The gene ontology resource: enriching a GOld mine","volume":"49","author":"The Gene Ontology Consortium;","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"D480","DOI":"10.1093\/nar\/gkaa1100","article-title":"UniProt: the universal protein knowledgebase in 2021","volume":"49","author":"The UniProt Consortium","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"2756","DOI":"10.1093\/bioinformatics\/btx302","article-title":"POSSUM: a bioinformatics toolkit for generating numerical sequence feature descriptors based on PSSM profiles","volume":"33","author":"Wang","year":"2017","journal-title":"Bioinformatics"},{"key":"2023041408370078000_","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1002\/prot.21018","article-title":"Prediction of protein subcellular localization","volume":"64","author":"Yu","year":"2006","journal-title":"Proteins"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btac458\/44834435\/btac458.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/17\/4226\/49889675\/btac458.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/17\/4226\/49889675\/btac458.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,24]],"date-time":"2023-11-24T10:50:33Z","timestamp":1700823033000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/38\/17\/4226\/6633921"}},"subtitle":[],"editor":[{"given":"Zhiyong","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2022,7,8]]},"references-count":23,"journal-issue":{"issue":"17","published-print":{"date-parts":[[2022,9,2]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btac458","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,9,1]]},"published":{"date-parts":[[2022,7,8]]}}}