Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in A549 cells

ABSTRACT: Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in A549 cells

PROVIDER: PRJNA804181 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in SNU-398 cells

Project description:Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in SNU-398 cells

| PRJNA804180 | ENA

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MDA-MB-231 cells

Project description:Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MDA-MB-231 cells

| PRJNA804178 | ENA

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MIA PaCa-2 cells

Project description:Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MIA PaCa-2 cells

| PRJNA804179 | ENA

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in A549 cells

Project description:Comparing expression profiles : among comparable samples in which target genes are knocked down Global gene expression profiling has shown that more than 1500 (3.2%) genes over 2-fold gene fluctuations are differentially expressed in shTGF-β1-treated cells compared to control shRNA-treated cells.

2022-02-08 | GSE196286 | GEO

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in SNU-398 cells

Project description:Comparing expression profiles : among comparable samples in which target genes are knocked down Global gene expression profiling has shown that only 134 (0.3%) genes over 2-fold gene fluctuations are differentially expressed in shTGF-β1-treated cells compared to control shRNA-treated cells.

2022-02-08 | GSE196287 | GEO

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MDA-MB-231 cells

2022-02-08 | GSE196289 | GEO

Transcriptome analysis after knockdown of target genes (either HSP27 or TGF-β1, both HSP27 and TGF-β1) via shRNAs in MIA PaCa-2 cells

2022-02-08 | GSE196288 | GEO

Transcriptomic Changes in TGF-β1 Differentiated and PGE2 Dedifferentiated Myofibroblasts

Project description:These data show that the genes that distinguish myofibroblasts from fibroblasts are myriad, and that some genes not traditionally associated with myofibroblast differentiation may serve as novel therapeutic targets for fibrosing disorders. Gene expression levels were assessed from total RNA on the Affymetrix U219 microarray. Here, we use transforming growth factor-β1 (TGF-β1) and prostaglandin E2 (PGE2), which has recently been shown to reverse myofibroblast differentiation, to investigate the transcriptomic changes that occur during TGF-β1-induced differentiation and PGE2-induced de-differentiation of myofibroblasts.

2015-06-30 | E-GEOD-63659 | biostudies-arrayexpress

Transcriptome profiling of control cells or the A549 cells in the presence or absence of acetate following TGF-β1 stimulation

Project description:Purpose: To compare the transcriptome profiling of control cells or the A549 cells in the presence or absence of acetate following TGF-β1 stimulation. Methods: A549 cells were treated with control, TGF-β1 or TGF-β1 plus acetate for 2 days. And then, we performed RNA sequencing for transcription profiling of control cells or the A549 cells in the presence or absence of acetate following TGF-β1 stimulation. The raw data were processed with bcl2fastq software and HISAT2. Results: From the transcriptome profiling and analysis, we got gene expression data of control group and in the presence or absence of acetate following TGF-β1 stimulation using A549 cells. Conclusion: The gene expression data revealed the transcriptome variation by TGF-β1 treatment and acetate can reverse TGF-β1 effect.

2022-06-14 | GSE197132 | GEO

Transcriptomic profiling of MGT#1-mVenus-reporter harboring A549 and H1944 cells upon stimulation with GSK126 and TGF-β1.

Project description:Investigation of gene expression profiles of MGT#1-mVenus-reporter harboring A549 and H1944 lung cancer cell lines upon PRC2 inhibition (GSK126) and activation of TGF-β1 pathway (TGF-β1).

2023-08-20 | GSE240898 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data