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 …

Spatial transcriptomics approaches have substantially advanced our capacity to detect the
spatial distribution of RNA transcripts in tissues, yet it remains challenging to characterize …

Aging is characterized by a progressive deterioration of physiological integrity, leading to
impaired functional ability and ultimately increased susceptibility to death. It is a major risk …

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 …

Spatial transcriptomic technologies and spatially annotated single-cell RNA sequencing
datasets provide unprecedented opportunities to dissect cell–cell communication (CCC) …

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

Spatial transcriptomics technologies are used to profile transcriptomes while preserving
spatial information, which enables high-resolution characterization of transcriptional patterns …