Results 41 to 50 of about 221,267 (266)
scRNA-seq data of human skin from patients with atopic dermatitis
, 2023 This is the scRNA-seq data of non-lesional and lesional human skin from patients with atopic dermatitis, which is used for running the main CellChat tutorial entitled "CellChat-vignette" (Inference and analysis of cell-cell communication using CellChat ...
Suoqin Jin (14184602)
core +1 more source
Cancer Communications, 2020 Single‐cell RNA sequencing (scRNA‐seq) is a novel technology that allows transcriptomic analyses of individual cells. During the past decade, scRNA‐seq sensitivity, accuracy, and efficiency have improved due to innovations including more sensitive ...
Shuning Ding, Xiaosong Chen, Kunwei Shen
doaj +1 more source
Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE
Genome Biology, 2023 Long-read single-cell RNA sequencing (scRNA-seq) enables the quantification of RNA isoforms in individual cells. However, long-read scRNA-seq using the Oxford Nanopore platform has largely relied upon matched short-read data to identify cell barcodes. We
Yupei You +6 more
doaj +1 more source
scRNA-seq analysis for mycn mutant and WT embryos at 3 dpf.
, 2022 (A) Dot plot showing expressions of 2 selected marker genes in each cell type. Dot size indicates the percentage of cells expressing the indicated genes; dot color indicates the average expression level of indicated genes.
Yang Dong (234336) +19 more
core +1 more source
Methods, Challenges and Potentials of Single Cell RNA-seq [PDF]
, 2012 RNA-sequencing (RNA-seq) has become the tool of choice for transcriptomics. Several recent studies demonstrate its successful adaption to single cell analysis. This allows new biological insights into cell differentiation, cell-to-cell variation and gene
Daniel Hebenstreit, Hebenstreit, Daniel
core +1 more source
scRNA-seq analyses of iNs and other cells.
, 2023 (A) UMAP combining all 9 samples: WT, Per1-/-, and Per2-/- cells on days 4, 7, and 10. (B) Dot plot showing top 3 marker genes in each cluster. (C) Temporal profiles of the proportions of 6 clusters.
Seunghyun Lim (14809635) +6 more
core +1 more source
scRNA-seq constructs a reference for CM maturation.
, 2021 A. Mouse model used to generate perinatal maturation reference scRNA-seq library. In the aMHC-cre x mTmG mouse, CMs are labeled by GFP. This image was obtained and modified from “Brown Mouse Lab” by SVG-Clipart.com under a CC BY 4.0 license. B.
Suraj Kannan (10812701) +4 more
core +1 more source
Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
FEBS Letters, EarlyView.EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
wiley +1 more source
scRNA-seq analyses of CD8+ T cells responding to acute vs. chronic infection.
, 2023 (A) Experimental setup. CD8+CD45.1+ P14 T cells were adoptively transferred into separate CD45.2+ hosts 1 day prior to infection with either LCMV-Arm or LCMV-Cl13.
Lara Labarta-Bajo (9096773) +14 more
core +1 more source