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 …

Foundation models hold great promise for analyzing single-cell omics data, yet various
challenges remain that require further advancements. In this Comment, we discuss the …

Developing a universal representation of cells which encompasses the tremendous
molecular diversity of cell types within the human body and more generally, across species …

Single-cell RNA-seq (scRNA-seq) has profiled hundreds of millions of human cells across
organs, diseases, development, and perturbations to date. Mining these growing atlases …

Single-cell RNA-seq (scRNA-seq) studies have profiled over 100 million human cells across
diseases, developmental stages, and perturbations to date. A singular view of this vast and …

Discovering genes with similar functions across diverse biomedical contexts poses a
significant challenge in gene representation learning due to data heterogeneity. In this …

Despite the wealth of single-cell multi-omics data, it remains challenging to predict the
consequences of novel genetic and chemical perturbations in the human body. It requires …

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

The ability to generate visceral sensory neurons (VSN) from induced pluripotent stem (iPS)
cells may help to gain insights into how the gut–nerve–brain axis is involved in neurological …

Cultured meat has the potential to provide a complementary meat industry with reduced
environmental, ethical, and health impacts. However, major technological challenges …