{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T17:50:52Z","timestamp":1791654652213,"version":"4.3.4"},"reference-count":198,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T00:00:00Z","timestamp":1791590400000},"content-version":"vor","delay-in-days":282,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Office Of The Director, National Institutes Of Health of the National Institutes of Health","award":["R03OD038391"],"award-info":[{"award-number":["R03OD038391"]}]},{"name":"National Institute Of Alcohol Abuse And Alcoholism of the National Institutes of Health","award":["R21AA032098"],"award-info":[{"award-number":["R21AA032098"]}]},{"name":"National Cancer Institute of the National Institutes of Health","award":["R03CA317707"],"award-info":[{"award-number":["R03CA317707"]}]},{"DOI":"10.13039\/100000001","name":"U.S. National Science Foundation","doi-asserted-by":"publisher","award":["2500836 and 2614824"],"award-info":[{"award-number":["2500836 and 2614824"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The subcellular localization of RNAs, including long non-coding RNAs, messenger RNAs, microRNAs and other smaller RNAs, plays a critical role in determining their biological functions. Understanding RNA localization sheds light on processes like gene expression regulation with spatial and temporal precision. However, traditional wet lab methods for determining RNA localization, such as in situ hybridization, are often time-consuming, resource-demanding, and costly. To overcome these challenges, computational methods leveraging artificial intelligence (AI) and machine learning (ML) have emerged as powerful alternatives, enabling large-scale prediction of RNA subcellular localization. This paper provides a comprehensive review of the latest advancements in AI-based approaches for RNA subcellular localization prediction, covering various RNA types and focusing on sequence-based, image-based, and hybrid methodologies that combine both data types. We highlight the potential of these methods to accelerate RNA research, uncover molecular pathways, and guide targeted disease treatments. Furthermore, we critically discuss the challenges in AI\/ML approaches for RNA subcellular localization, such as data scarcity and lack of benchmarks, and opportunities to address them. This review aims to serve as a valuable resource for researchers seeking to develop innovative solutions in the field of RNA subcellular localization and beyond.<\/jats:p>","DOI":"10.1093\/bfgp\/elag011","type":"journal-article","created":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T12:18:51Z","timestamp":1790425131000},"source":"Crossref","is-referenced-by-count":0,"title":["A comprehensive review on RNA subcellular localization prediction"],"prefix":"10.1093","volume":"25","author":[{"given":"Cece","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Cell & Systems Biology, University of Toronto , Ramsay Wright Laboratories, 25 Harbord St, Toronto, ON M5S 3G5 ,","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuehuan","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Engineering, University of California , 7400 Boelter Hall, Los Angeles, CA 90095, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nick","family":"Peterson","sequence":"additional","affiliation":[{"name":"Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center , 42nd & Emile St, Omaha, NE 68198, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2040-9552","authenticated-orcid":false,"given":"Jieqiong","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Neurological Sciences, University of Nebraska Medical Center , 42nd & Emile St, Omaha, NE 68198 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0661-2684","authenticated-orcid":false,"given":"Shibiao","family":"Wan","sequence":"additional","affiliation":[{"name":"Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center , 42nd & Emile St, Omaha, NE 68198, United 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