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

The interplay between chromatin, transcription factors and genes generates complex
regulatory circuits that can be represented as gene regulatory networks (GRNs). The study …

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

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods,
together with associated computational tools and the growing availability of public data …

In the past decade, single-cell technologies have proliferated and improved from their
technically challenging beginnings to become common laboratory methods capable of …

Hundreds of millions of single cells have been analyzed using high-throughput
transcriptomic methods. The cumulative knowledge within these datasets provides an …

Although cellular senescence drives multiple age-related co-morbidities through the
senescence-associated secretory phenotype, in vivo senescent cell identification remains …

Technological advances have made it possible to study a patient from multiple angles with
high-dimensional, high-throughput multiscale biomedical data. In oncology, massive …

A key aspect of nearly all single-cell sequencing experiments is dissociation of intact tissues
into single-cell suspensions. While many protocols have been optimized for optimal cell …

Single-cell omics technologies have revolutionized the study of gene regulation in complex
tissues. A major computational challenge in analyzing these datasets is to project the large …