4 papers
Panoramic modelling of single-cell transcriptomes at scale with CellNet
Xiaoqing Lian, Pei Liu, Jiahui Tan +10
Comprehensively characterizing cellular landscapes to elucidate cell diversity is a central goal in biology. Recent advances in single-cell profiling have created unprecedented opp…
Understanding Gene Expression-to-Image Learning: Spatial Structure and Information Fidelity
Xiaoqing Lian, Pei Liu, Jiahui Tan +3
Single-cell RNA sequencing (scRNA-seq) enables cell-level analysis of biological heterogeneity, but learning effective representations from high-dimensional, unordered gene express…
Empowering Chemical Structures with Biological Insights for Scalable Phenotypic Virtual Screening
Xiaoqing Lian, Pengsen Ma, Tengfeng Ma +9
Motivation: The scalable identification of bioactive compounds is essential for contemporary drug discovery. This process faces a key trade-off: structural screening offers scalabi…
Inductive-Associative Meta-learning Pipeline with Human Cognitive Patterns for Unseen Drug-Target Interaction Prediction
Xiaoqing Lian, Jie Zhu, Tianxu Lv +7
Significant differences in protein structures hinder the generalization of existing drug-target interaction (DTI) models, which often rely heavily on pre-learned binding principles…