{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,3]],"date-time":"2026-05-03T09:17:40Z","timestamp":1777799860382,"version":"3.51.4"},"reference-count":44,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,4,22]],"date-time":"2024-04-22T00:00:00Z","timestamp":1713744000000},"content-version":"vor","delay-in-days":26,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U23A20321"],"award-info":[{"award-number":["U23A20321"]}],"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":["62272490"],"award-info":[{"award-number":["62272490"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Accurately delineating the connection between short nucleolar RNA (snoRNA) and disease is crucial for advancing disease detection and treatment. While traditional biological experimental methods are effective, they are labor-intensive, costly and lack scalability. With the ongoing progress in computer technology, an increasing number of deep learning techniques are being employed to predict snoRNA\u2013disease associations. Nevertheless, the majority of these methods are black-box models, lacking interpretability and the capability to elucidate the snoRNA\u2013disease association mechanism. In this study, we introduce IGCNSDA, an innovative and interpretable graph convolutional network (GCN) approach tailored for the efficient inference of snoRNA\u2013disease associations. IGCNSDA leverages the GCN framework to extract node feature representations of snoRNAs and diseases from the bipartite snoRNA-disease graph. SnoRNAs with high similarity are more likely to be linked to analogous diseases, and vice versa. To facilitate this process, we introduce a subgraph generation algorithm that effectively groups similar snoRNAs and their associated diseases into cohesive subgraphs. Subsequently, we aggregate information from neighboring nodes within these subgraphs, iteratively updating the embeddings of snoRNAs and diseases. The experimental results demonstrate that IGCNSDA outperforms the most recent, highly relevant methods. Additionally, our interpretability analysis provides compelling evidence that IGCNSDA adeptly captures the underlying similarity between snoRNAs and diseases, thus affording researchers enhanced insights into the snoRNA\u2013disease association mechanism. Furthermore, we present illustrative case studies that demonstrate the utility of IGCNSDA as a valuable tool for efficiently predicting potential snoRNA\u2013disease associations. The dataset and source code for IGCNSDA are openly accessible at: https:\/\/github.com\/altriavin\/IGCNSDA.<\/jats:p>","DOI":"10.1093\/bib\/bbae179","type":"journal-article","created":{"date-parts":[[2024,4,22]],"date-time":"2024-04-22T09:54:37Z","timestamp":1713779677000},"source":"Crossref","is-referenced-by-count":11,"title":["IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network"],"prefix":"10.1093","volume":"25","author":[{"given":"Xiaowen","family":"Hu","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , 410075, Changsha , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hunan Provincial Key Laboratory of Clinical Epidemiology , Xiangya School of Public Health, , 410078, Changsha China"},{"name":"Central South University , Xiangya School of Public Health, , 410078, Changsha China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dayun","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , 410075, Changsha , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaxuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of California, San Diego , 92093, CA , United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanpeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Software, Xinjiang University , 830046, Urumqi , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yihan","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , 410075, Changsha , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanhao","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , 410075, Changsha , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University , 410075, Changsha , China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,4,21]]},"reference":[{"issue":"7","key":"2024042209542859500_ref1","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1016\/S0092-8674(00)81308-2","article-title":"Site-specific ribose methylation of preribosomal rna: a novel function for small nucleolar rnas","volume":"85","author":"Kiss-L\u00e1szl\u00f3","year":"1996","journal-title":"Cell"},{"issue":"14","key":"2024042209542859500_ref2","doi-asserted-by":"crossref","first-page":"3617","DOI":"10.1093\/emboj\/20.14.3617","article-title":"Small nucleolar rna-guided post-transcriptional modification of cellular rnas","volume":"20","author":"Kiss","year":"2001","journal-title":"EMBO J"},{"issue":"22","key":"2024042209542859500_ref3","doi-asserted-by":"crossref","first-page":"4518","DOI":"10.1093\/nar\/29.22.4518","article-title":"Box C\/D RNA guides for the ribose methylation of archaeal tRNAs. 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