{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T00:01:08Z","timestamp":1755216068377,"version":"3.43.0"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T00:00:00Z","timestamp":1754179200000},"content-version":"vor","delay-in-days":33,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["GYKP034","62303372"],"award-info":[{"award-number":["GYKP034","62303372"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["LQ23F020018"],"award-info":[{"award-number":["LQ23F020018"]}]},{"name":"Young Talent Fund of Xi\u2019an Association for Science and Technology","award":["959202313033"],"award-info":[{"award-number":["959202313033"]}]},{"name":"Project funded by China Postdoctoral Science Foundation","award":["2023M742794"],"award-info":[{"award-number":["2023M742794"]}]},{"name":"Postdoctoral Research Project in Shaanxi Province","award":["2023BSHEDZZ34"],"award-info":[{"award-number":["2023BSHEDZZ34"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["xzy012024091"],"award-info":[{"award-number":["xzy012024091"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,7,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), play pivotal roles in various human diseases. Predicting associations such as lncRNA\u2013disease associations (LDAs), miRNA\u2013disease associations (MDAs), and lncRNA\u2013miRNA interactions (LMIs) is crucial for understanding disease mechanisms and identifying therapeutic targets. However, existing models face significant challenges in handling extreme data imbalance and often treat multiple ncRNA\u2013disease and ncRNA\u2013ncRNA interactions collectively, lacking the ability to provide precise, differentiated predictions for specific types of ncRNAs. This limitation reduces their practical applicability. To address these issues, we propose the Dual Balanced Augmented Topological Noncoding RNA Disease triplet Association (DBATNDA) model. DBATNDA constructs an Interaction Dual Graph with LDAs, MDAs, and LMIs as nodes and introduces an efficient graph-based balanced topological augmentation mechanism to enhance node structural representation and adaptability to imbalanced data. This innovative approach enables fast and accurate predictions of ncRNA\u2013disease and ncRNA\u2013ncRNA triplet associations through node classification view. To the best of our knowledge, no existing method employs such a dual-representation strategy to provide simultaneously differentiated predictions for the associations between diverse ncRNAs and diseases while also enhancing target specificity. Experimental results demonstrate DBATNDA\u2019s superior performance compared to state-of-the-art models, while case studies confirm its practical significance in these triple association prediction. The code and datasets are publicly available at https:\/\/github.com\/AI4Bread\/DBATNDA.<\/jats:p>","DOI":"10.1093\/bib\/bbaf389","type":"journal-article","created":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T14:29:37Z","timestamp":1754231377000},"source":"Crossref","is-referenced-by-count":0,"title":["Dual balanced augmented topological noncoding RNA disease triplet association in heterogeneous graphs"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9086-3982","authenticated-orcid":false,"given":"Laiyi","family":"Fu","sequence":"first","affiliation":[{"name":"School of Automation Science and Engineering, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , Shannxi,","place":["China"]},{"name":"Research Institute of Xi\u2019an Jiaotong University , Zhejiang, Hangzhou 311200, Zhejiang ,","place":["China"]},{"name":"Sichuan Digital Economy Industry Development Research Institute , Chengdu 610036, Sichuan ,","place":["China"]}]},{"given":"Yangyi","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Automation Science and Engineering, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , Shannxi,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5061-4762","authenticated-orcid":false,"given":"Hongqiang","family":"Lyu","sequence":"additional","affiliation":[{"name":"School of Automation Science and Engineering, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , Shannxi,","place":["China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2046-2109","authenticated-orcid":false,"given":"Hequan","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Automation Science and Engineering, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , 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