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This highlights the urgent need to develop efficient computational models that can predict circRNA\u2013disease associations, offering an alternative approach to overcome the limitations of expensive experimental studies. Although multi-view learning methods have been widely adopted, most approaches fail to fully exploit the latent information across views, while simultaneously overlooking the fact that different views contribute to varying degrees of significance.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>This study presents a method that combines multi-view shared units and multichannel attention mechanisms to predict circRNA\u2013disease associations (MSMCDA). MSMCDA first constructs similarity and meta-path networks for circRNAs and diseases by introducing shared units to facilitate interactive learning across distinct network features. Subsequently, multichannel attention mechanisms were used to optimize the weights within similarity networks. Finally, contrastive learning strengthened the similarity features. Experiments on five public datasets demonstrated that MSMCDA significantly outperformed other baseline methods. Additionally, case studies on colorectal cancer, gastric cancer, and nonsmall cell lung cancer confirmed the effectiveness of MSMCDA in uncovering new associations.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The source code and data are available at https:\/\/github.com\/zhangxue2115\/MSMCDA.git.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaf088","type":"journal-article","created":{"date-parts":[[2025,3,6]],"date-time":"2025-03-06T04:24:31Z","timestamp":1741235071000},"source":"Crossref","is-referenced-by-count":15,"title":["Predicting circRNA\u2013disease associations with shared units and multi-channel attention mechanisms"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8466-8838","authenticated-orcid":false,"given":"Xue","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Harbin Institute of Technology , Harbin, Heilongjiang 150000,","place":["China"]},{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , Chengdu, Sichuan 610000,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6406-1142","authenticated-orcid":false,"given":"Quan","family":"Zou","sequence":"additional","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , Chengdu, Sichuan 610000,","place":["China"]},{"name":"Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China , Quzhou, Zhejiang 324000,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9175-4649","authenticated-orcid":false,"given":"Mengting","family":"Niu","sequence":"additional","affiliation":[{"name":"Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China , Chengdu, Sichuan 610000,","place":["China"]},{"name":"School of Electronic and Communication Engineering, Shenzhen Polytechnic University , Shenzhen, Guangdong 518055,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2965-9920","authenticated-orcid":false,"given":"Chunyu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Harbin Institute of Technology , Harbin, Heilongjiang 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