The study is useful for advancing spatial transcriptomics through its novel regression-based linear model (glmSMA) that integrates single-cell RNA-seq with spatial reference atlases, though its ...

All analyses were performed using R (version 4.4.2). Key analysis packages included Seurat (v5.1.0) for single-cell analysis and clusterProfiler (v4.12.6) for pathway enrichment analysis. A complete ...

pacman::p_load('dplyr','data.table','fst','plyr','tidyr','Hmisc','tableone','zoo','mgcv','splines',BiocManager,stringr,dplyr,progress,survival,openxlsx,plotRCS ...

We employed Seurat version 3.1.4 for unbiased cell clustering analysis ... variability in FOLR1 expression may contribute to the development of adaptive drug resistance (9). Our single-cell analysis ...

A gene associated with the early progression of MI was identified based on single cell RNA sequencing data. To further validate the predictive value of the gene, the mouse models of MI were ...

Research on gastrointestinal diseases, especially cancer, has mainly focused on epithelial cells, which line the surfaces of ...

The Single-Cell Analysis Market is experiencing robust expansion, driven by surging demand for precision medicine, advancements in genomics, and rising investments in life sciences research.

However, studying these cells using single-cell RNA sequencing (scRNA ... and prepared using identical methods to allow for the analysis of the same set of cells with both D-scRNA and P-scRNA ...

Shihabeddin et al utilized single-cell RNA-Seq analysis of adult P23H zebrafish animals to identify transcription factors (e2fs, Prdm1a, Sp1) expressed selectively in neural progenitors and immature ...

In episode one of this podcast, you’ll hear a group of experts discussing base editing and how the technology is helping scientists engineer powerful cell therapies for various diseases including ...