3 citations · 5 across the 5 of their papers we have counts for
5 papers
Benchmarking AI scientists for omics data driven biological discovery
Erpai Luo, Jinmeng Jia, Yifan Xiong +6
Recent advances in large language models have enabled the emergence of AI scientists that aim to autonomously analyze biological data and assist scientific discovery. Despite rapid…
Querying structural and functional niches on spatial transcriptomics data
Mo Chen, Minsheng Hao, Xinquan Liu +8
Cells in multicellular organisms coordinate to form structural and functional niches. With spatial transcriptomics (ST) enabling gene expression profiling in spatial contexts, it h…
scDiffusion: conditional generation of high-quality single-cell data using diffusion model
Erpai Luo, Minsheng Hao, Lei Wei +1
Single-cell RNA sequencing (scRNA-seq) data are important for studying the laws of life at single-cell level. However, it is still challenging to obtain enough high-quality scRNA-s…
xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data
Jing Gong, Minsheng Hao, Xingyi Cheng +6
Advances in high-throughput sequencing technology have led to significant progress in measuring gene expressions at the single-cell level. The amount of publicly available single-c…
MMA-RNN: A Multi-level Multi-task Attention-based Recurrent Neural Network for Discrimination and Localization of Atrial Fibrillation
Yifan Sun, Jingyan Shen, Yunfan Jiang +3
The automatic detection of atrial fibrillation based on electrocardiograph (ECG) signals has received wide attention both clinically and practically. It is challenging to process E…