BIMSA > 生物信息讨论班 Self-supervised learning on millions of pre-mRNA sequences improves sequence-based RNA splicing prediction
Self-supervised learning on millions of pre-mRNA sequences improves sequence-based RNA splicing prediction
组织者
丘成栋
演讲者
孙楠
时间
2023年10月26日 22:00 至 22:30
地点
Online
摘要
RNA splicing, a crucial post-transcriptional process in eukaryotic gene expression, can be predicted using a novel self-supervised model, SpliceBERT. Pre-trained on vertebrate pre-mRNA sequences, SpliceBERT enhances RNA splicing prediction, including variant effects and branch point prediction, across species, emphasizing the potential of pre-trained models for understanding RNA splicing.
演讲者介绍
孙楠目前是北京雁栖湖应用数学研究院的博士后。她的研究方向包括生物信息学、机器学习和应用数学，在The Innovation, Computational and Structural Biotechnology Journal, BMC Bioinformatics, Frontiers in Cellular and Infection Microbiology, Journal of Computational Biology, Genes等期刊发表多篇论文，参与多项国家自然科学基金及北京市自然科学基金项目，主持中国博士后科学基金第78批面上资助。