The inherent similarities between natural language and biological sequences have inspired the use of large language models in genomics, but current models struggle to incorporate chromatin interactions or predict in unseen cellular contexts. To address this, we propose EpiGePT, a transformer-based model designed for predicting context-specific human epigenomic signals. By incorporating transcription factor activities and 3D genome interactions, EpiGePT outperforms existing methods in epigenomic signal prediction tasks, especially in cell-type-specific long-range interaction predictions and genetic variant impacts, advancing our understanding of gene regulation. A free online prediction service is available athttp://health.tsinghua.edu.cn/epigept.

Zijing Gao

Qiao Liu

Wanwen Zeng

Rui Jiang

Wing Hung Wong

Genome Biology

基因组生物学涵盖从基因组和后基因组角度研究的生物学和生物医学的所有领域。内容包括研究、新方法和软件工具，以及评论、意见和评论。涵盖的领域包括但不限于：序列分析；生物信息学；深入了解分子、细胞和有机体生物学；功能基因组学；表观基因组学；群体基因组学；蛋白质组学；比较生物学和进化论；系统和网络生物学；基因组编辑和工程；疾病基因组学；和临床基因组学。

Genome Biology covers all areas of biology and biomedicine studied from the perspectives of genomics and post-genomics. The content includes research articles, new methods and software tools, as well as reviews and opinions. The fields covered include, but are not limited to: sequence analysis; bioinformatics; in-depth studies of molecular, cellular, and organismal biology; functional genomics; epigenomics; population genomics; proteomics; comparative biology and evolution; systems and network biology; genome editing and engineering; disease genomics; and clinical genomics.

《Genome Biology》期刊涵盖了从基因组和后基因组的角度研究生物学和生物医学的各个领域。内容包括研究论文、新方法和软件工具，以及评论和意见。涉及的领域包括但不限于：序列分析、生物信息学、分子、细胞和有机体生物学的深入研究、功能基因组学、表观基因组学、群体基因组学、蛋白质组学、比较生物学和进化论、系统和网络生物学、基因组编辑和工程、疾病基因组学以及临床基因组学。

EpiGePT: a pretrained transformer-based language model for context-specific human epigenomics

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Journal Info

Category	Quartile
GENETICS & HEREDITY	1