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

As an emerging sequencing technology, single-cell RNA sequencing (scRNA-Seq) has
become a powerful tool for describing cell subpopulation classification and cell …

Large pretrained models have become foundation models leading to breakthroughs in
natural language processing and related fields. Developing foundation models for …

Single-cell RNA sequencing (scRNA-seq) is a revolutionary breakthrough that determines
the precise gene expressions on individual cells and deciphers cell heterogeneity and …

Sample preparation for single-cell proteomics is generally performed in a one-pot workflow
with multiple dispensing and incubation steps. These hours-long processes can be labor …

Background: Spatial transcriptomics technologies fully utilize spatial location information,
tissue morphological features, and transcriptional profiles. Integrating these data can greatly …

Single-cell RNA sequencing (scRNA-seq) provides insights into gene expression
heterogeneities in diverse cell types underlying homeostasis, development and pathological …

Advances in high-throughput sequencing technology have led to significant progress in
measuring gene expressions at the single-cell level. The amount of publicly available single …

Colorectal cancer (CRC) has a high degree of heterogeneity and identifying the genetic
information of individual tumor cells could help enhance our understanding of tumor biology …

Due to the sustained proliferative potential of cancer cells, inducing cell death is a potential
strategy for cancer therapy. Paraptosis is a mode of cell death characterized by endoplasmic …