108 citations · 109 across the 6 of their papers we have counts for
5 papers · 1 filter
CellChain: Benchmarking Cross-Scale Evidence Use for Perturbation Reasoning
Xue Xia, Yue Wang, Shuizhou Chen +6
Recent advances in foundation models and large-scale cellular perturbation datasets have driven growing interest in using LLMs to predict and reason about cellular responses. Biolo…
SciForge: An AI-Native, Multimodal Workbench for Scientific Discovery
SciForge Team, Zhangyang Gao, Minghao Fang +10
Scientific work increasingly spans heterogeneous artifacts -- papers, code, datasets, scientific file formats, model outputs, figures, manuscripts, and team decisions -- yet genera…
What drives performance in molecular MPNNs? An operator-level factorial benchmark
Panyu Jiao, Shuizhou Chen, Yiheng Shen +3
Message-passing neural networks (MPNNs) are widely used for molecular property prediction, but their deployment as monolithic architectures makes it difficult to identify how speci…
Benchmarking virtual cell models for in-the-wild perturbation response
Xinjie Mao, Songming Zhang, Qianhong Wen +10
Virtual cell (VC) models aim to predict cellular responses to any perturbations in silico and have emerged as a promising approach for drug discovery and precision medicine. Yet, a…
SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction
Shuizhou Chen, Lang Yu, Xueqin Lin +12
Virtual-cell models aim to predict how cell populations respond to perturbations, but control and treated cells are measured as unpaired populations, complicating the learning of p…