Recent efforts to construct reference maps of cellular phenotypes have expanded the
volume and diversity of single-cell omics data, providing an unprecedented resource for …

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene
expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has …

Hundreds of millions of single cells have been analyzed using high-throughput
transcriptomic methods. The cumulative knowledge within these datasets provides an …

The immune system comprises diverse specialized cell types that cooperate to defend the
host against a wide range of pathogenic threats. Recent advancements in single-cell and …

Cells are essential to understanding health and disease, yet traditional models fall short of
modeling and simulating their function and behavior. Advances in AI and omics offer …

Large-scale foundation models, which are pre-trained on massive, unlabeled datasets and
subsequently fine-tuned on specific tasks, have recently achieved unparalleled success on …

Abstract Foundation Models (FMs) have made significant strides in both industrial and
scientific domains. In this paper, we evaluate the performance of FMs for single-cell …

Tissue makeup relies fundamentally on the cellular microenvironment. Spatial single-cell
genomics allows probing the underlying cellular interactions in an unbiased, scalable …

Despite advancements in antifibrotic therapy, idiopathic pulmonary fibrosis (IPF) remains a
medical condition with unmet needs. Single-cell RNA sequencing (scRNA-seq) has …

Single-cell RNA sequencing (scRNA-seq) datasets contain true single cells, or singlets, in
addition to cells that coalesce during the protocol, or doublets. Identifying singlets with high …