人工智能技术有助于对表观转录组分布的理解。
AI techniques have facilitated the understanding of epitranscriptome distribution.
作者信息
Huang Daiyun, Meng Jia, Chen Kunqi
机构信息
Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, School of Basic Medical Sciences, Fuzhou 350122, China; Wisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China; School of Life Sciences, Fudan University, Shanghai 200092, China.
Department of Biosciences and Bioinformatics, Center for Intelligent RNA Therapeutics, Suzhou Key Laboratory of Cancer Biology and Chronic Diseases, School of Science, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China; Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L7 8TX, UK.
出版信息
Cell Genom. 2024 Dec 11;4(12):100718. doi: 10.1016/j.xgen.2024.100718.
N-methyladenosine (m6A), the most prevalent internal mRNA modification in higher eukaryotes, plays diverse roles in cellular regulation. By incorporating both sequence- and genome-derived features, Fan et al. designed a novel Transformer-BiGRU framework that achieves superior performance in computational m6A identification, thus demonstrating the potential of AI in genomic studies.
N-甲基腺苷（m6A）是高等真核生物中最普遍的内部mRNA修饰，在细胞调控中发挥着多种作用。通过整合序列和基因组衍生特征，Fan等人设计了一种新型的Transformer-BiGRU框架，该框架在计算m6A识别方面表现出色，从而证明了人工智能在基因组研究中的潜力。
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