Perspectives on integrating artificial intelligence and single‐cell omics for cellular plasticity research

Cellular plasticity enables cells to dynamically adapt to environmental changes by altering their phenotype. This plasticity plays a crucial role in tissue repair and regeneration and contributes to pathological processes such as cancer metastasis. Advances in single-cell omics have significantly advanced the study of cellular states and provided new opportunities for accurate cell classification and uncovering cellular transitions. In this perspective, we emphasize integrating chromatin accessibility data and extrinsic factors, such as microenvironmental cues, with single-cell transcriptomic data to develop holistic models for identifying plastic cell states. Additionally, coupling artificial intelligence with single-cell omics offers transformative potential to address existing challenges and fill gaps in identifying and characterizing plastic cells. We envision the development of a universal plasticity metric, a standardized metric for quantifying cellular plasticity. This metric would enable consistent measurement across diverse studies, creating a unified framework that bridges fields such as developmental biology, cancer research, and regenerative medicine. Fostering innovative approaches to identifying and analyzing cellular plasticity promises not only to deepen our understanding of cellular plasticity but also to accelerate therapeutic advancements, paving the way for novel precision medicine strategies to treat complex diseases such as cancer.