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 …

The advent and success of foundation models such as GPT has sparked growing interest in
their application to single-cell biology. Models like Geneformer and scGPT have emerged …

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

Motivation Genetic perturbations (eg knockouts, variants) have laid the foundation for our
understanding of many diseases, implicating pathogenic mechanisms and indicating …

Abstract Large Language Models (LLMs) or foundation models have made significant
strides in both industrial and scientific domains. In this paper, we evaluate the performance …

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 …

Researching genes and their interactions is crucial for deciphering the fundamental laws of
cellular activity, advancing disease treatment, drug discovery, and more. Large language …

Transformer‐based foundation models such as ChatGPTs have revolutionized our daily life
and affected many fields including bioinformatics. In this perspective, we first discuss about …

This document is an interview with leading researchers in the field of AI and biology,
discussing the development and applications of Large Cellular Models (LCMs) in biological …