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A new algorithm, iDRO (integrated deep-learning-based mRNA optimization), is developed to optimize multiple components of mRNA sequences based on given amino acid sequences of target protein. Considering the biological constraints, we divided iDRO into two steps: open reading frame (ORF) optimization and 5\u2032 untranslated region (UTR) and 3\u2032UTR generation. In ORF optimization, BiLSTM-CRF (bidirectional long-short-term memory with conditional random field) is employed to determine the codon for each amino acid. In UTR generation, RNA-Bart (bidirectional auto-regressive transformer) is proposed to output the corresponding UTR. The results show that the optimized sequences of exogenous genes acquired the pattern of human endogenous gene sequence. In experimental validation, the mRNA sequence optimized by our method, compared with conventional method, shows higher protein expression. To the best of our knowledge, this is the first study by introducing deep-learning methods to integrated mRNA sequence optimization, and these results may contribute to the development of mRNA therapeutics.<\/jats:p>","DOI":"10.1093\/bib\/bbad001","type":"journal-article","created":{"date-parts":[[2023,1,16]],"date-time":"2023-01-16T00:26:51Z","timestamp":1673828811000},"source":"Crossref","is-referenced-by-count":44,"title":["Integrated mRNA sequence optimization using deep learning"],"prefix":"10.1093","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5661-4090","authenticated-orcid":false,"given":"Haoran","family":"Gong","sequence":"first","affiliation":[{"name":"West China Biomedical Big Data Center, West China Hospital, Sichuan University , Chengdu 610041 , China"},{"name":"Med-X Center for Informatics, Sichuan University , Chengdu 610041 , 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