{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T08:31:02Z","timestamp":1775809862902,"version":"3.50.1"},"reference-count":54,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T00:00:00Z","timestamp":1656201600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2021R1A2C1014338"],"award-info":[{"award-number":["2021R1A2C1014338"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2021R1C1C1007833"],"award-info":[{"award-number":["2021R1C1C1007833"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,18]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Long noncoding RNAs (lncRNAs) are primarily regulated by their cellular localization, which is responsible for their molecular functions, including cell cycle regulation and genome rearrangements. Accurately identifying the subcellular location of lncRNAs from sequence information is crucial for a better understanding of their biological functions and mechanisms. In contrast to traditional experimental methods, bioinformatics or computational methods can be applied for the annotation of lncRNA subcellular locations in humans more effectively. In the past, several machine learning-based methods have been developed to identify lncRNA subcellular localization, but relevant work for identifying cell-specific localization of human lncRNA remains limited. In this study, we present the first application of the tree-based stacking approach, TACOS, which allows users to identify the subcellular localization of human lncRNA in 10 different cell types. Specifically, we conducted comprehensive evaluations of six tree-based classifiers with 10 different feature descriptors, using a newly constructed balanced training dataset for each cell type. Subsequently, the strengths of the AdaBoost baseline models were integrated via a stacking approach, with an appropriate tree-based classifier for the final prediction. TACOS displayed consistent performance in both the cross-validation and independent assessments compared with the other two approaches employed in this study. The user-friendly online TACOS web server can be accessed at https:\/\/balalab-skku.org\/TACOS.<\/jats:p>","DOI":"10.1093\/bib\/bbac243","type":"journal-article","created":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T23:43:55Z","timestamp":1656287035000},"source":"Crossref","is-referenced-by-count":45,"title":["TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization"],"prefix":"10.1093","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5998-9605","authenticated-orcid":false,"given":"Young-Jun","family":"Jeon","sequence":"first","affiliation":[{"name":"Department of Integrative Biotechnology , College of Bioengineering and Biotechnology, , Suwon 16419, Korea"},{"name":"Sungkyunkwan University , College of Bioengineering and Biotechnology, , Suwon 16419, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4952-0739","authenticated-orcid":false,"given":"Md Mehedi","family":"Hasan","sequence":"additional","affiliation":[{"name":"Tulane Center for Biomedical Informatics and Genomics , Division of Biomedical Informatics and Genomics, John W. Deming Department of Medicine, School of Medicine, , New Orleans, LA 70112, USA"},{"name":"Tulane University , Division of Biomedical Informatics and Genomics, John W. Deming Department of Medicine, School of Medicine, , New Orleans, LA 70112, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hyun Woo","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Integrative Biotechnology , College of Bioengineering and Biotechnology, , Suwon 16419, Korea"},{"name":"Sungkyunkwan University , College of Bioengineering and Biotechnology, , Suwon 16419, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ki Wook","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Integrative Biotechnology , College of Bioengineering and Biotechnology, , Suwon 16419, Korea"},{"name":"Sungkyunkwan University , College of Bioengineering and Biotechnology, , Suwon 16419, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0697-9419","authenticated-orcid":false,"given":"Balachandran","family":"Manavalan","sequence":"additional","affiliation":[{"name":"Computational Biology and Bioinformatics laboratory , Department of Integrative Biotechnology, College of Bioengineering and Biotechnology, , Suwon 16419, Korea"},{"name":"Sungkyunkwan University , Department of Integrative Biotechnology, College of Bioengineering and Biotechnology, , Suwon 16419, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,6,27]]},"reference":[{"key":"2022071906184234900_ref1","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1186\/s13045-020-00945-8","article-title":"Principles and innovative technologies for decrypting noncoding RNAs: from discovery and functional prediction to clinical 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