2 citations · 2 across the 15 of their papers we have counts for
5 papers · 1 filter
Beyond Gene Reconstruction: Learning Cell Representations through Complementary Transcriptomic Views
Jiaqi Xiong, Yuntao hu, Yu Zheng +3
The rapid growth of single-cell transcriptomic data has enabled the development of foundation models pretrained primarily by reconstructing masked expression values. This objective…
Towards Universal Gene Regulatory Network Inference: Unlocking Generalizable Regulatory Knowledge in Single-cell Foundation Models
Jiaxin Qi, Hang Li, Yan Cui +2
Gene Regulatory Network (GRN) inference is essential for understanding complex cellular mechanisms, rendered tractable through single-cell transcriptomic data. With the emergence o…
In Search of Lost DNA Sequence Pretraining
Zhijiang Tang, Jiaxin Qi, Yan Cui +3
DNA sequence encoding is fundamental to gene function prediction, protein synthesis, and diverse downstream biological tasks. Despite the substantial progress achieved by large-sca…
Gene Incremental Learning for Single-Cell Transcriptomics
Jiaxin Qi, Yan Cui, Jianqiang Huang +1
Classes, as fundamental elements of Computer Vision, have been extensively studied within incremental learning frameworks. In contrast, tokens, which play essential roles in many r…
Graph Neural Networks as a Substitute for Transformers in Single-Cell Transcriptomics
Jiaxin Qi, Yan Cui, Jinli Ou +2
Graph Neural Networks (GNNs) and Transformers share significant similarities in their encoding strategies for interacting with features from nodes of interest, where Transformers u…