Single-cell molecular profiling technologies are gaining rapid traction, but the manual
process by which resulting cell types are typically annotated is labor intensive and rate …

Here we demonstrate that the large language model GPT-4 can accurately annotate cell
types using marker gene information in single-cell RNA sequencing analysis. When …

Accurate cell-type annotation from spatially resolved single cells is crucial to understand
functional spatial biology that is the basis of tissue organization. However, current …

Single-cell technologies are offering unparalleled insight into complex biology, revealing the
behavior of rare cell populations that are masked in bulk population analyses. One current …

Single-cell genomics has now made it possible to create a comprehensive atlas of human
cells. At the same time, it has reopened definitions of a cell's identity and of the ways in …

Although tremendous effort has been put into cell-type annotation, identification of
previously uncharacterized cell types in heterogeneous single-cell RNA-seq data remains a …

In recent years there has been tremendous progress towards deep molecular
characterization of cell types using single-cell transcriptome sequencing, creating so-called …

Single cell technologies are rapidly generating large amounts of data that enables us to
understand biological systems at single-cell resolution. However, joint analysis of datasets …

Technical advances have enabled the collection of genome and transcriptome data sets
with single-cell resolution. However, single-cell characterization of the epigenome has …

Because of the stochasticity associated with high-throughput single-cell sequencing, current
methods for exploring cell-type diversity rely on clustering-based computational approaches …