{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T17:56:54Z","timestamp":1773511014718,"version":"3.50.1"},"reference-count":46,"publisher":"Oxford University Press (OUP)","issue":"24","license":[{"start":{"date-parts":[[2020,12,15]],"date-time":"2020-12-15T00:00:00Z","timestamp":1607990400000},"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\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972423"],"award-info":[{"award-number":["61972423"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1909208"],"award-info":[{"award-number":["U1909208"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013314","name":"111 Project","doi-asserted-by":"publisher","award":["B18059"],"award-info":[{"award-number":["B18059"]}],"id":[{"id":"10.13039\/501100013314","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hunan Provincial Science and Technology Program","award":["2018wk4001"],"award-info":[{"award-number":["2018wk4001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,4,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Emerging studies indicate that circular RNAs (circRNAs) are widely involved in the progression of human diseases. Due to its special structure which is stable, circRNAs are promising diagnostic and prognostic biomarkers for diseases. However, the experimental verification of circRNA\u2013disease associations is expensive and limited to small-scale. Effective computational methods for predicting potential circRNA\u2013disease associations are regarded as a matter of urgency. Although several models have been proposed, over-reliance on known associations and the absence of characteristics of biological functions make precise predictions are still challenging.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this study, we propose a method for predicting CircRNA\u2013disease associations based on sequence and ontology representations, named CDASOR, with convolutional and recurrent neural networks. For sequences of circRNAs, we encode them with continuous k-mers, get low-dimensional vectors of k-mers, extract their local feature vectors with 1D CNN and learn their long-term dependencies with bi-directional long short-term memory. For diseases, we serialize disease ontology into sentences containing the hierarchy of ontology, obtain low-dimensional vectors for disease ontology terms and get terms\u2019 dependencies. Furthermore, we get association patterns of circRNAs and diseases from known circRNA\u2013disease associations with neural networks. After the above steps, we get circRNAs\u2019 and diseases\u2019 high-level representations, which are informative to improve the prediction. The experimental results show that CDASOR provides an accurate prediction. Importing the characteristics of biological functions, CDASOR achieves impressive predictions in the de novo test. In addition, 6 of the top-10 predicted results are verified by the published literature in the case studies.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The code and data of CDASOR are freely available at https:\/\/github.com\/BioinformaticsCSU\/CDASOR.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa1077","type":"journal-article","created":{"date-parts":[[2020,12,15]],"date-time":"2020-12-15T17:54:46Z","timestamp":1608054886000},"page":"5656-5664","source":"Crossref","is-referenced-by-count":38,"title":["Improving circRNA\u2013disease association prediction by sequence and ontology representations with convolutional and recurrent neural networks"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9201-6912","authenticated-orcid":false,"given":"Chengqian","family":"Lu","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , Changsha 410083, P.R. China"},{"name":"Hunan Provincial Key Lab on Bioinformatics, Central South University , Changsha 410083, P.R. China"}]},{"given":"Min","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , Changsha 410083, P.R. China"},{"name":"Hunan Provincial Key Lab on Bioinformatics, Central South University , Changsha 410083, P.R. China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4593-9332","authenticated-orcid":false,"given":"Fang-Xiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Division of Biomedical Engineering, University of Saskatchewan , Saskatchewan S7N 5A9, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0188-1394","authenticated-orcid":false,"given":"Min","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , Changsha 410083, P.R. China"},{"name":"Hunan Provincial Key Lab on Bioinformatics, Central South University , Changsha 410083, P.R. China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1516-0480","authenticated-orcid":false,"given":"Jianxin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , Changsha 410083, P.R. China"},{"name":"Hunan Provincial Key Lab on Bioinformatics, Central South University , Changsha 410083, P.R. China"}]}],"member":"286","published-online":{"date-parts":[[2020,12,26]]},"reference":[{"key":"2023062408131924200_btaa1077-B1","doi-asserted-by":"crossref","first-page":"D1034","DOI":"10.1093\/nar\/gky905","article-title":"LncRNADisease 2.0: an updated database of long non-coding RNA-associated diseases","volume":"47","author":"Bao","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2023062408131924200_btaa1077-B2","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1093\/nar\/gkh061","article-title":"The unified medical language system (UMLS): integrating biomedical terminology","volume":"32","author":"Bodenreider","year":"2004","journal-title":"Nucleic Acids Res"},{"key":"2023062408131924200_btaa1077-B3","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":"2023062408131924200_btaa1077-B47","article-title":"Convergence guarantees for RMSProp and ADAM in non-convex optimization and an empirical comparison to Nesterov acceleration","author":"De","year":"2018"},{"key":"2023062408131924200_btaa1077-B5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/ncomms14741","article-title":"FUS affects circular RNA expression in murine embryonic stem cell-derived motor neurons","volume":"8","author":"Errichelli","year":"2017","journal-title":"Nat. Commun"},{"key":"2023062408131924200_btaa1077-B6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/database\/bay044","article-title":"CircR2Disease: a manually curated database for experimentally supported circular RNAs associated with various diseases","volume":"2018","author":"Fan","year":"2018","journal-title":"Database"},{"key":"2023062408131924200_btaa1077-B7","doi-asserted-by":"crossref","first-page":"1950","DOI":"10.7150\/ijbs.28260","article-title":"Prediction of CircRNA-disease associations using KATZ model based on heterogeneous networks","volume":"14","author":"Fan","year":"2018","journal-title":"Int. J. Biol. Sci"},{"key":"2023062408131924200_btaa1077-B8","doi-asserted-by":"crossref","first-page":"1666","DOI":"10.1261\/rna.043687.113","article-title":"CircBase: a database for circular RNAs","volume":"20","author":"Glazar","year":"2014","journal-title":"RNA"},{"key":"2023062408131924200_btaa1077-B9","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1093\/nar\/gki033","article-title":"Online Mendelian inheritance in man (OMIM), a knowledge base of human genes and genetic disorders","volume":"33","author":"Hamosh","year":"2005","journal-title":"Nucleic Acids Res"},{"key":"2023062408131924200_btaa1077-B10","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1038\/nature11993","article-title":"Natural RNA circles function as efficient microRNA sponges","volume":"495","author":"Hansen","year":"2013","journal-title":"Nature"},{"key":"2023062408131924200_btaa1077-B48","doi-asserted-by":"crossref","DOI":"10.3115\/v1\/D14-1181","article-title":"Convolutional neural networks for sentence classification","author":"Kim","year":"2014"},{"key":"2023062408131924200_btaa1077-B12","doi-asserted-by":"crossref","first-page":"1474","DOI":"10.1038\/s41588-018-0207-8","article-title":"Functional classification of long non-coding RNAs by k-mer content","volume":"50","author":"Kirk","year":"2018","journal-title":"Nat. Genet"},{"key":"2023062408131924200_btaa1077-B13","doi-asserted-by":"crossref","first-page":"1940","DOI":"10.1038\/s41598-020-59040-0","article-title":"Integrating random walk with restart and k-Nearest Neighbor to identify novel circRNA-disease association","volume":"10","author":"Lei","year":"2020","journal-title":"Sci. Rep"},{"key":"2023062408131924200_btaa1077-B14","doi-asserted-by":"crossref","first-page":"2911","DOI":"10.7150\/ijbs.33806","article-title":"GBDTCDA: predicting circRNA-disease associations based on gradient boosting decision tree with multiple biological data fusion","volume":"15","author":"Lei","year":"2019","journal-title":"Int. J. Biol. Sci"},{"key":"2023062408131924200_btaa1077-B15","doi-asserted-by":"crossref","first-page":"3410","DOI":"10.3390\/ijms19113410","article-title":"PWCDA: path weighted method for predicting circRNA-disease associations","volume":"19","author":"Lei","year":"2018","journal-title":"Int. J. Mol. Sci"},{"key":"2023062408131924200_btaa1077-B16","first-page":"897","article-title":"Predicting circRNA-disease associations based on improved collaboration filtering recommendation system with multiple data","volume":"10","author":"Lei","year":"2019","journal-title":"Int. J. Biol. Sci"},{"key":"2023062408131924200_btaa1077-B17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12920-020-0679-0","article-title":"Prediction of circRNA-disease associations based on inductive matrix completion","volume":"13","author":"Li","year":"2020","journal-title":"BMC Med. Genomics"},{"key":"2023062408131924200_btaa1077-B18","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1186\/s13046-018-1006-x","article-title":"RNA sequencing reveals the expression profiles of circRNA and indicates that circDDX17 acts as a tumor suppressor in colorectal cancer","volume":"37","author":"Li","year":"2018","journal-title":"J. Exp. Clin. Cancer Res"},{"key":"2023062408131924200_btaa1077-B19","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1038\/cr.2015.82","article-title":"Circular RNA is enriched and stable in exosomes: a promising biomarker for cancer diagnosis","volume":"25","author":"Li","year":"2015","journal-title":"Cell Res"},{"key":"2023062408131924200_btaa1077-B20","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1038\/nsmb.2959","article-title":"Exon-intron circular RNAs regulate transcription in the nucleus","volume":"22","author":"Li","year":"2015","journal-title":"Nat. Struct. Mol. Biol"},{"key":"2023062408131924200_btaa1077-B21","first-page":"1","article-title":"Circular RNA FAM114A2 suppresses progression of bladder cancer via regulating \u0394NP63 by sponging miR-762","volume":"11","author":"Liu","year":"2020","journal-title":"Cell Death Dis"},{"key":"2023062408131924200_btaa1077-B22","first-page":"doi: 10.1109\/JBHI.2020.2999638","article-title":"Deep matrix factorization improves prediction of human circRNA-disease associations","author":"Lu","year":"2020","journal-title":"IEEE J. Biomed. Health Inform"},{"key":"2023062408131924200_btaa1077-B23","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res"},{"key":"2023062408131924200_btaa1077-B24","article-title":"MNDR v3.0: mammal ncRNA-disease repository with increased coverage and annotation","author":"Ning","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"2023062408131924200_btaa1077-B25","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.neucom.2018.04.036","article-title":"Learning distributed representations of RNA sequences and its application for predicting RNA-protein binding sites with a convolutional neural network","volume":"305","author":"Pan","year":"2018","journal-title":"Neurocomputing"},{"key":"2023062408131924200_btaa1077-B26","first-page":"1532","author":"Pennington","year":"2014"},{"key":"2023062408131924200_btaa1077-B27","doi-asserted-by":"crossref","first-page":"3852","DOI":"10.1073\/pnas.73.11.3852","article-title":"Viroids are single-stranded covalently closed circular RNA molecules existing as highly base-paired rod-like structures","volume":"73","author":"Sanger","year":"1976","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023062408131924200_btaa1077-B28","doi-asserted-by":"crossref","first-page":"D955","DOI":"10.1093\/nar\/gky1032","article-title":"Human Disease Ontology 2018 update: classification, content and workflow expansion","volume":"47","author":"Schriml","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2023062408131924200_btaa1077-B29","doi-asserted-by":"crossref","first-page":"2673","DOI":"10.1109\/78.650093","article-title":"Bidirectional recurrent neural networks","volume":"45","author":"Schuster","year":"1997","journal-title":"IEEE Trans. Signal Process"},{"key":"2023062408131924200_btaa1077-B30","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1186\/s12872-019-1191-3","article-title":"Association of circular RNAs and environmental risk factors with coronary heart disease","volume":"19","author":"Sun","year":"2019","journal-title":"BMC Cardiovasc. Disord"},{"key":"2023062408131924200_btaa1077-B31","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1038\/s41422-018-0033-7","article-title":"Circular RNA F-circEA produced from EML4-ALK fusion gene as a novel liquid biopsy biomarker for non-small cell lung cancer","volume":"28","author":"Tan","year":"2018","journal-title":"Cell Res"},{"key":"2023062408131924200_btaa1077-B32","doi-asserted-by":"crossref","first-page":"4038","DOI":"10.1093\/bioinformatics\/btz825","article-title":"An efficient approach based on multi-sources information to predict circRNA-disease associations using deep convolutional neural network","volume":"36","author":"Wang","year":"2019","journal-title":"Bioinformatics"},{"key":"2023062408131924200_btaa1077-B33","first-page":"145","author":"Wang","year":"2019"},{"key":"2023062408131924200_btaa1077-B34","doi-asserted-by":"crossref","first-page":"e1007568","DOI":"10.1371\/journal.pcbi.1007568","article-title":"GCNCDA: a new method for predicting circRNA-disease associations based on Graph Convolutional Network Algorithm","volume":"16","author":"Wang","year":"2020","journal-title":"PLoS Comput. Biol"},{"key":"2023062408131924200_btaa1077-B35","doi-asserted-by":"crossref","first-page":"832","DOI":"10.3389\/fgene.2019.00832","article-title":"Predicting circRNA-disease associations based on circRNA expression similarity and functional similarity","volume":"10","author":"Wang","year":"2019","journal-title":"Front. Genet"},{"key":"2023062408131924200_btaa1077-B36","doi-asserted-by":"crossref","first-page":"1356","DOI":"10.1093\/bib\/bbz057","article-title":"iCircDA-MF: identification of circRNA-disease associations based on matrix factorization","volume":"21","author":"Wei","year":"2019","journal-title":"Brief. Bioinform"},{"key":"2023062408131924200_btaa1077-B37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-020-02018-y","article-title":"CircAtlas: an integrated resource of one million highly accurate circular RNAs from 1070 vertebrate transcriptomes","volume":"21","author":"Wu","year":"2020","journal-title":"Genome Biol"},{"key":"2023062408131924200_btaa1077-B38","doi-asserted-by":"crossref","first-page":"2661","DOI":"10.1109\/JBHI.2019.2891779","article-title":"Computational prediction of human disease-associated circRNAs based on manifold regularization Learning framework","volume":"23","author":"Xiao","year":"2019","journal-title":"IEEE J. Biomed. Health Inform"},{"key":"2023062408131924200_btaa1077-B39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41419-019-1382-y","article-title":"circTADA2As suppress breast cancer progression and metastasis via targeting miR-203a-3p\/SOCS3 axis","volume":"10","author":"Xu","year":"2019","journal-title":"Cell Death Dis"},{"key":"2023062408131924200_btaa1077-B40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13046-020-01556-4","article-title":"Circular RNA hsa_circ_0000326 acts as a miR-338-3p sponge to facilitate lung adenocarcinoma progression","volume":"39","author":"Xu","year":"2020","journal-title":"J. Exp. Clin. Cancer Res"},{"key":"2023062408131924200_btaa1077-B41","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1186\/s12859-018-2522-6","article-title":"DWNN-RLS: regularized least squares method for predicting circRNA-disease associations","volume":"19","author":"Yan","year":"2018","journal-title":"BMC Bioinformatics"},{"key":"2023062408131924200_btaa1077-B42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-29360-3","article-title":"Circ2Disease: a manually curated database of experimentally validated circRNAs in human disease","volume":"8","author":"Yao","year":"2018","journal-title":"Sci. Rep"},{"key":"2023062408131924200_btaa1077-B43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41419-020-2532-y","article-title":"The circular RNA circMAST1 promotes hepatocellular carcinoma cell proliferation and migration by sponging miR-1299 and regulating CTNND1 expression","volume":"11","author":"Yu","year":"2020","journal-title":"Cell Death Dis"},{"key":"2023062408131924200_btaa1077-B44","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1093\/bib\/bbz080","article-title":"Predicting disease-associated circular RNAs using deep forests combined with positive-unlabeled learning methods","volume":"21","author":"Zeng","year":"2019","journal-title":"Brief. Bioinform"},{"key":"2023062408131924200_btaa1077-B45","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1109\/TNB.2019.2922214","article-title":"Integrating bipartite network projection and KATZ measure to identify novel CircRNA-disease associations","volume":"18","author":"Zhao","year":"2019","journal-title":"IEEE Trans. Nanobiosci"},{"key":"2023062408131924200_btaa1077-B46","doi-asserted-by":"crossref","first-page":"e1007872","DOI":"10.1371\/journal.pcbi.1007872","article-title":"iCDA-CGR: identification of circRNA-disease associations based on Chaos Game Representation","volume":"16","author":"Zheng","year":"2020","journal-title":"PLoS Comput. Biol"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaa1077\/36197385\/btaa1077.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/24\/5656\/50692867\/btaa1077.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/24\/5656\/50692867\/btaa1077.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,24]],"date-time":"2023-06-24T23:37:48Z","timestamp":1687649868000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/36\/24\/5656\/6050707"}},"subtitle":[],"editor":[{"given":"Jan","family":"Gorodkin","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2020,12,15]]},"references-count":46,"journal-issue":{"issue":"24","published-print":{"date-parts":[[2021,4,5]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaa1077","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,12,15]]},"published":{"date-parts":[[2020,12,15]]}}}