Recent advances in single-cell technologies have enabled high-throughput molecular
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …

Single-cell transcriptomics (scRNA-seq) has become essential for biomedical research over
the past decade, particularly in developmental biology, cancer, immunology, and …

Many spatially resolved transcriptomic technologies do not have single-cell resolution but
measure the average gene expression for each spot from a mixture of cells of potentially …

Spatial omics has been widely heralded as the new frontier in life sciences. This term
encompasses a wide range of techniques that promise to transform many areas of biology …

Deciphering the principles and mechanisms by which gene activity orchestrates complex
cellular arrangements in multicellular organisms has far-reaching implications for research …

Spatial transcriptomics (ST) technologies generate multiple data types from biological
samples, namely gene expression, physical distance between data points, and/or tissue …

Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly
evolving, making it possible to comprehensively characterize cells and tissues in health and …

Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but
does not capture their spatial distribution nor reveal local networks of intercellular …

The function of many biological systems, such as embryos, liver lobules, intestinal villi, and
tumors, depends on the spatial organization of their cells. In the past decade, high …

The natural history of cancers can be understood through the lens of evolution given that the
driving forces of cancer development are mutation and selection of fitter clones. Cancer …