{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,20]],"date-time":"2026-06-20T00:21:40Z","timestamp":1781914900636,"version":"3.54.5"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2021,9,9]],"date-time":"2021-09-09T00:00:00Z","timestamp":1631145600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100002767","name":"Hunan Provincial Science and Technology Department","doi-asserted-by":"publisher","award":["2019CB1007"],"award-info":[{"award-number":["2019CB1007"]}],"id":[{"id":"10.13039\/501100002767","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002767","name":"Hunan Provincial Science and Technology Department","doi-asserted-by":"publisher","award":["B18059"],"award-info":[{"award-number":["B18059"]}],"id":[{"id":"10.13039\/501100002767","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U19A2064"],"award-info":[{"award-number":["U19A2064"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,17]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Long non-coding RNAs (lncRNAs) are a class of RNA molecules with more than 200 nucleotides. A growing amount of evidence reveals that subcellular localization of lncRNAs can provide valuable insights into their biological functions. Existing computational methods for predicting lncRNA subcellular localization use k-mer features to encode lncRNA sequences. However, the sequence order information is lost by using only k-mer features. We proposed a deep learning framework, DeepLncLoc, to predict lncRNA subcellular localization. In DeepLncLoc, we introduced a new subsequence embedding method that keeps the order information of lncRNA sequences. The subsequence embedding method first divides a sequence into some consecutive subsequences and then extracts the patterns of each subsequence, last combines these patterns to obtain a complete representation of the lncRNA sequence. After that, a text convolutional neural network is employed to learn high-level features and perform the prediction task. Compared with traditional machine learning models, popular representation methods and existing predictors, DeepLncLoc achieved better performance, which shows that DeepLncLoc could effectively predict lncRNA subcellular localization. Our study not only presented a novel computational model for predicting lncRNA subcellular localization but also introduced a new subsequence embedding method which is expected to be applied in other sequence-based prediction tasks. The DeepLncLoc web server is freely accessible at http:\/\/bioinformatics.csu.edu.cn\/DeepLncLoc\/, and source code and datasets can be downloaded from https:\/\/github.com\/CSUBioGroup\/DeepLncLoc.<\/jats:p>","DOI":"10.1093\/bib\/bbab360","type":"journal-article","created":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T07:17:27Z","timestamp":1629184647000},"source":"Crossref","is-referenced-by-count":86,"title":["DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding"],"prefix":"10.1093","volume":"23","author":[{"given":"Min","family":"Zeng","sequence":"first","affiliation":[{"name":"Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, Hunan, 410083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Wu","sequence":"additional","affiliation":[{"name":"Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, Hunan, 410083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengqian","family":"Lu","sequence":"additional","affiliation":[{"name":"Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, Hunan, 410083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fuhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, Hunan, 410083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4593-9332","authenticated-orcid":false,"given":"Fang-Xiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Division of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0188-1394","authenticated-orcid":false,"given":"Min","family":"Li","sequence":"additional","affiliation":[{"name":"Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, Hunan, 410083, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,9,9]]},"reference":[{"key":"2022011921005801400_ref1","doi-asserted-by":"crossref","first-page":"280","DOI":"10.26599\/BDMA.2020.9020025","article-title":"CircRNA-disease associations prediction based on metapath2vec++ and matrix factorization","volume":"3","author":"Zhang","year":"2020","journal-title":"Big Data Min Anal"},{"key":"2022011921005801400_ref2","doi-asserted-by":"crossref","first-page":"261","DOI":"10.26599\/BDMA.2019.9020010","article-title":"Prediction of miRNA-circRNA associations based on k-NN multi-label with random walk restart on a heterogeneous network","volume":"2","author":"Fang","year":"2019","journal-title":"Big Data Min Anal"},{"key":"2022011921005801400_ref3","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1038\/nature05874","article-title":"Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project","volume":"447","author":"Consortium","year":"2007","journal-title":"Nature"},{"key":"2022011921005801400_ref4","doi-asserted-by":"crossref","first-page":"3357","DOI":"10.1093\/bioinformatics\/bty327","article-title":"Prediction of lncRNA\u2013disease associations based on inductive matrix completion","volume":"34","author":"Lu","year":"2018","journal-title":"Bioinformatics"},{"key":"2022011921005801400_ref5","doi-asserted-by":"crossref","first-page":"6391","DOI":"10.1093\/nar\/gks296","article-title":"Emerging functional and mechanistic paradigms of mammalian long non-coding RNAs","volume":"40","author":"Moran","year":"2012","journal-title":"Nucleic Acids Res"},{"key":"2022011921005801400_ref6","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.ymeth.2020.05.002","article-title":"SDLDA: lncRNA-disease association prediction based on singular value decomposition and deep learning","volume":"179","author":"Zeng","year":"2020","journal-title":"Methods"},{"key":"2022011921005801400_ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2020.2983958","article-title":"DMFLDA: a deep learning framework for predicting IncRNA\u2013disease associations","author":"Zeng","year":"2020","journal-title":"IEEE\/ACM Trans Comput Biol"},{"key":"2022011921005801400_ref8","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1038\/nrg3074","article-title":"Non-coding RNAs in human disease","volume":"12","author":"Esteller","year":"2011","journal-title":"Nat Rev Genet"},{"key":"2022011921005801400_ref9","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/978-1-4939-7471-9_6","article-title":"The emerging role of long noncoding RNAs in human disease","volume":"1706","author":"DiStefano","year":"2018","journal-title":"Methods Mol Biol"},{"key":"2022011921005801400_ref10","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1016\/j.molcel.2011.08.018","article-title":"Molecular mechanisms of long noncoding RNAs","volume":"43","author":"Wang","year":"2011","journal-title":"Mol Cell"},{"key":"2022011921005801400_ref11","article-title":"Predicting human lncRNA-disease associations based on geometric matrix completion","volume":"24","author":"Lu","year":"2019","journal-title":"IEEE J Biomed Health Inform"},{"key":"2022011921005801400_ref12","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1016\/j.molcel.2019.02.008","article-title":"Global positioning system: understanding long noncoding RNAs through subcellular localization","volume":"73","author":"Carlevaro-Fita","year":"2019","journal-title":"Mol Cell"},{"key":"2022011921005801400_ref13","doi-asserted-by":"crossref","first-page":"1628","DOI":"10.1093\/bib\/bbz106","article-title":"Critical evaluation of web-based prediction tools for human protein subcellular localization","volume":"21","author":"Shen","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022011921005801400_ref14","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.jtbi.2018.11.012","article-title":"Identification of protein subcellular localization via integrating evolutionary and physicochemical information into Chou\u2019s general PseAAC","volume":"462","author":"Shen","year":"2019","journal-title":"J Theor Biol"},{"key":"2022011921005801400_ref15","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1038\/nsmb.2764","article-title":"Topological organization of multichromosomal regions by the long intergenic noncoding RNA firre","volume":"21","author":"Hacisuleyman","year":"2014","journal-title":"Nat Struct Mol Biol"},{"key":"2022011921005801400_ref16","doi-asserted-by":"crossref","first-page":"648","DOI":"10.1016\/j.molcel.2012.06.027","article-title":"LincRNA-p21 suppresses target mRNA translation","volume":"47","author":"Yoon","year":"2012","journal-title":"Mol Cell"},{"key":"2022011921005801400_ref17","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1186\/s13062-016-0165-y","article-title":"ZFAS1: a long noncoding RNA associated with ribosomes in breast cancer cells","volume":"11","author":"Hansji","year":"2016","journal-title":"Biol Direct"},{"key":"2022011921005801400_ref18","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1004012","article-title":"150 years of the mass action law","volume":"11","author":"Voit","year":"2015","journal-title":"PLoS Comput Biol"},{"key":"2022011921005801400_ref19","first-page":"D135","article-title":"RNALocate: a resource for RNA subcellular localizations","volume":"45","author":"Zhang","year":"2016","journal-title":"Nucleic Acids Res"},{"key":"2022011921005801400_ref20","doi-asserted-by":"crossref","first-page":"1080","DOI":"10.1261\/rna.060814.117","article-title":"LncATLAS database for subcellular localization of long noncoding RNAs","volume":"23","author":"Mas-Ponte","year":"2017","journal-title":"RNA"},{"key":"2022011921005801400_ref21","doi-asserted-by":"publisher","DOI":"10.1093\/database\/bay085","article-title":"lncSLdb: a resource for long non-coding RNA subcellular localization","volume":"2018","author":"Wen","year":"2018","journal-title":"Database"},{"key":"2022011921005801400_ref22","doi-asserted-by":"crossref","first-page":"2185","DOI":"10.1093\/bioinformatics\/bty085","article-title":"The lncLocator: a subcellular localization predictor for long non-coding RNAs based on a stacked ensemble classifier","volume":"34","author":"Cao","year":"2018","journal-title":"Bioinformatics"},{"key":"2022011921005801400_ref23","doi-asserted-by":"crossref","first-page":"4196","DOI":"10.1093\/bioinformatics\/bty508","article-title":"iLoc-lncRNA: predict the subcellular location of lncRNAs by incorporating octamer composition into general PseKNC","volume":"34","author":"Su","year":"2018","journal-title":"Bioinformatics"},{"key":"2022011921005801400_ref24","doi-asserted-by":"crossref","first-page":"16385","DOI":"10.1038\/s41598-018-34708-w","article-title":"Prediction of lncRNA subcellular localization with deep learning from sequence features","volume":"8","author":"Gudenas","year":"2018","journal-title":"Sci Rep"},{"key":"2022011921005801400_ref25","doi-asserted-by":"crossref","first-page":"124702","DOI":"10.1109\/ACCESS.2020.3007317","article-title":"lncLocPred: predicting LncRNA subcellular localization using multiple sequence feature information","volume":"8","author":"Fan","year":"2020","journal-title":"IEEE Access"},{"key":"2022011921005801400_ref26","first-page":"1","article-title":"Identify RNA-associated subcellular localizations based on multi-label learning using Chou\u2019s 5-steps rule","volume":"22","author":"Wang","year":"2021","journal-title":"BMC Genomics"},{"key":"2022011921005801400_ref27","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","article-title":"Spatial pyramid pooling in deep convolutional networks for visual recognition","volume":"37","author":"He","year":"2015","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2022011921005801400_ref28","volume-title":"arXiv:1301.3781","author":"Mikolov","year":"2013"},{"key":"2022011921005801400_ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2021.3050102","article-title":"DPCMNE: detecting protein complexes from protein-protein interaction networks via multi-level network embedding","author":"Meng","year":"2021","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2022011921005801400_ref30","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-020-03682-4","article-title":"NEDD: a network embedding based method for predicting drug-disease associations","volume":"21","author":"Zhou","year":"2020","journal-title":"Bmc Bioinformatics"},{"key":"2022011921005801400_ref31","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.ymeth.2020.06.015","article-title":"PrGeFNE: predicting disease-related genes by fast network embedding","volume":"192","author":"Xiang","year":"2021","journal-title":"Methods"},{"key":"2022011921005801400_ref32","volume-title":"Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks","author":"Rehurek","year":"2010"},{"key":"2022011921005801400_ref33","volume-title":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","author":"Kim","year":"2014"},{"key":"2022011921005801400_ref34","article-title":"Protein\u2013protein interaction site prediction through combining local and global features with deep neural networks","volume":"36","author":"Zeng","year":"2019","journal-title":"Bioinformatics"},{"key":"2022011921005801400_ref35","volume-title":"Automatic differentiation in pytorch","author":"Paszke","year":"2017"},{"key":"2022011921005801400_ref36","first-page":"2980","volume-title":"Focal loss for dense object detection","author":"Lin","year":"2017"},{"key":"2022011921005801400_ref37","doi-asserted-by":"crossref","first-page":"1900019","DOI":"10.1002\/pmic.201900019","article-title":"DeepFunc: a deep learning framework for accurate prediction of protein functions from protein sequences and interactions","volume":"19","author":"Zhang","year":"2019","journal-title":"Proteomics"},{"key":"2022011921005801400_ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2019.2897679","article-title":"A deep learning framework for identifying essential proteins by integrating multiple types of biological information","volume":"18","author":"Zeng","year":"2019","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2022011921005801400_ref39","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.neucom.2018.04.081","article-title":"Automatic ICD-9 coding via deep transfer learning","volume":"324","author":"Zeng","year":"2019","journal-title":"Neurocomputing"},{"key":"2022011921005801400_ref40","first-page":"1263","article-title":"Learning from imbalanced data","volume":"21","author":"He","year":"2008","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2022011921005801400_ref41","doi-asserted-by":"crossref","first-page":"i333","DOI":"10.1093\/bioinformatics\/btz337","article-title":"Prediction of mRNA subcellular localization using deep recurrent neural networks","volume":"35","author":"Yan","year":"2019","journal-title":"Bioinformatics"},{"key":"2022011921005801400_ref42","doi-asserted-by":"crossref","first-page":"1326","DOI":"10.1093\/bioinformatics\/bty824","article-title":"Exploring sequence-based features for the improved prediction of DNA N4-methylcytosine sites in multiple species","volume":"35","author":"Wei","year":"2018","journal-title":"Bioinformatics"},{"key":"2022011921005801400_ref43","doi-asserted-by":"crossref","first-page":"i354","DOI":"10.1093\/bioinformatics\/btz395","article-title":"ShaKer: RNA SHAPE prediction using graph kernel","volume":"35","author":"Mautner","year":"2019","journal-title":"Bioinformatics"},{"key":"2022011921005801400_ref44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-33321-1","article-title":"Recurrent neural network for predicting transcription factor binding sites","volume":"8","author":"Shen","year":"2018","journal-title":"Sci Rep"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/23\/1\/bbab360\/42230033\/bbab360.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/23\/1\/bbab360\/42230033\/bbab360.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,7]],"date-time":"2023-11-07T08:13:12Z","timestamp":1699344792000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbab360\/6366323"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,9]]},"references-count":44,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,1,17]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbab360","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.03.13.435245","asserted-by":"object"}]},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,1]]},"published":{"date-parts":[[2021,9,9]]},"article-number":"bbab360"}}