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In the meantime, the conventional experimental procedures for predicting ac4C alteration sites are costly, time-consuming, and difficult. The precise recognition of ac4C modification sites in human mRNA has been greatly aided by computational prediction techniques using sequence data, machine learning (ML), deep learning (DL), and large language models (LLMs). The application of ML, DL, and LLM-based techniques for the identification of ac4C modification sites in human mRNA has been evaluated and contrasted in this review. Distinctively, we have also addressed the shortcomings of the existing methods and tools, as well as potential future developments. We anticipate that this study will provide sufficient information and awareness for ac4C modification research.<\/jats:p>","DOI":"10.1093\/bib\/bbag263","type":"journal-article","created":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T11:49:19Z","timestamp":1778240959000},"source":"Crossref","is-referenced-by-count":0,"title":["ac4C modification sites prediction in human mRNA: a complete review"],"prefix":"10.1093","volume":"27","author":[{"given":"Hasan","family":"Zulfiqar","sequence":"first","affiliation":[{"name":"Center for AI and Computational Biology, Institute of System Medicine, Peking Union Medical College, Chinese Academy of Medical Sciences , Suzhou 215123 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramala Masood","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China , Chengdu 611731 ,","place":["China"]},{"name":"Department of Plant Breeding and Genetics, University of Agriculture Faisalabad , Faisalabad 38000 ,","place":["Pakistan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6265-2862","authenticated-orcid":false,"given":"Hao","family":"Lin","sequence":"additional","affiliation":[{"name":"Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China , Chengdu 611731 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Long","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Materials Science and Engineering, Hainan University , Haikou 570228 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