{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T10:03:50Z","timestamp":1769508230444,"version":"3.49.0"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T00:00:00Z","timestamp":1736726400000},"content-version":"vor","delay-in-days":18,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"China National Natural Science Foundation","doi-asserted-by":"crossref","award":["62472195"],"award-info":[{"award-number":["62472195"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"China National Natural Science Foundation","doi-asserted-by":"crossref","award":["62076109"],"award-info":[{"award-number":["62076109"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"China National Natural Science Foundation","doi-asserted-by":"crossref","award":["62401131"],"award-info":[{"award-number":["62401131"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Predicting RNA-binding proteins (RBPs) is central to understanding post-transcriptional regulatory mechanisms. Here, we introduce EnrichRBP, an automated and interpretable computational platform specifically designed for the comprehensive analysis of RBP interactions with RNA.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>EnrichRBP is a web service that enables researchers to develop original deep learning and machine learning architectures to explore the complex dynamics of RBPs. The platform supports 70 deep learning algorithms, covering feature representation, selection, model training, comparison, optimization, and evaluation, all integrated within an automated pipeline. EnrichRBP is adept at providing comprehensive visualizations, enhancing model interpretability, and facilitating the discovery of functionally significant sequence regions crucial for RBP interactions. In addition, EnrichRBP supports base-level functional annotation tasks, offering explanations and graphical visualizations that confirm the reliability of the predicted RNA-binding sites. Leveraging high-performance computing, EnrichRBP provides ultra-fast predictions ranging from seconds to hours, applicable to both pre-trained and custom model scenarios, thus proving its utility in real-world applications. Case studies highlight that EnrichRBP provides robust and interpretable predictions, demonstrating the power of deep learning in the functional analysis of RBP interactions. Finally, EnrichRBP aims to enhance the reproducibility of computational method analyses for RBP sequences, as well as reduce the programming and hardware requirements for biologists, thereby offering meaningful functional insights.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>EnrichRBP is available at https:\/\/airbp.aibio-lab.com\/. The source code is available at https:\/\/github.com\/wangyb97\/EnrichRBP, and detailed online documentation can be found at https:\/\/enrichrbp.readthedocs.io\/en\/latest\/.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaf018","type":"journal-article","created":{"date-parts":[[2025,1,13]],"date-time":"2025-01-13T16:39:27Z","timestamp":1736786367000},"source":"Crossref","is-referenced-by-count":2,"title":["EnrichRBP: an automated and interpretable computational platform for predicting and analysing RNA-binding protein events"],"prefix":"10.1093","volume":"41","author":[{"given":"Yubo","family":"Wang","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Jilin University , Changchun 130012,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7240-2696","authenticated-orcid":false,"given":"Haoran","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Jilin University , Changchun 130012,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yansong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Jilin University , Changchun 130012,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4556-139X","authenticated-orcid":false,"given":"Yuning","family":"Yang","sequence":"additional","affiliation":[{"name":"Information Science and Technology, Northeast Normal University , Changchun 130024,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujian","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Cyber Security, Chengdu University of Technology , Chengdu 610059,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7155-7760","authenticated-orcid":false,"given":"Jian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Technology, Xinyang Normal University , Xinyang 464000,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6062-733X","authenticated-orcid":false,"given":"Ka-chun","family":"Wong","sequence":"additional","affiliation":[{"name":"Department of Computer Science, City University of Hong Kong , Hong Kong SAR 999077,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8716-9823","authenticated-orcid":false,"given":"Xiangtao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Jilin University , Changchun 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