The advent of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics has revolutionized our understanding of disease pathogenesis by providing unprecedented resolution into cellular heterogeneity and tissue architecture. This collection showcases cutting-edge research that leverages these transformative technologies to decode disease mechanisms and accelerate clinical translation.

Single-cell transcriptomics has revealed remarkable cellular diversity within dysfunctional tissues, uncovering rare cell populations, disease-specific cell states, and novel therapeutic targets previously masked by bulk analyses. Spatial transcriptomics preserves crucial tissue context, mapping gene expression patterns within their native microenvironments and revealing how cellular communication networks become disrupted in pathological conditions. Together, these approaches are redefining our understanding of the molecular basis of cancer, neurodegeneration, autoimmune disorders, aging, and infectious diseases.

This collection emphasizes studies that bridge mechanistic discovery and clinical application. We seek research demonstrating how single-cell and spatial insights inform biomarker development, drug discovery, precision medicine strategies, and therapeutic monitoring. Priority is given to research focusing on disease models, developing protocols and methodologies for analyzing diseased samples, identifying novel pathological mechanisms, establishing clinically relevant cellular signatures, and creating computational frameworks to translate complex multi-dimensional data into actionable clinical knowledge.

By bringing together leading researchers at the intersection of computational biology, disease biology, and clinical medicine, this collection aims to accelerate translation of cellular-resolution discoveries into improved patient outcomes. We welcome original research articles, methodology papers, and comprehensive reviews that advance disease understanding through cellular and spatial transcriptomics.