Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network

ABSTRACT: Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network

PROVIDER: PRJNA1160196 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR26377662.fastq.gz	Fastqsanger.gz
	SRR26377663.fastq.gz	Fastqsanger.gz
	SRR26377664.fastq.gz	Fastqsanger.gz
	SRR26377665.fastq.gz	Fastqsanger.gz
	SRR26377666.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 30

Similar Datasets

Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network [RNA-Seq]

Project description:Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network [RNA-Seq]

| PRJNA1027795 | ENA

Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network [ChIP-Seq]

Project description:Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network [ChIP-Seq]

| PRJNA1159787 | ENA

Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network

Project description:This SuperSeries is composed of the SubSeries listed below.

2025-03-25 | GSE277002 | GEO

Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network [RNA-Seq]

Project description:We profiled gene expression in iCas9-expressing HCEC-1CT and HME1 cells that were either WT or knockout for ARID1A or CREBBP, to determine the cell type variability in expression levels of epigenetic regulators and the transcriptional consequences of epigenetic regulator loss.

2025-03-25 | GSE245297 | GEO

Systematic genetic perturbation reveals principles underpinning robustness of the epigenetic regulatory network [ChIP-Seq]

Project description:We profiled the H3K27ac mark on chromatin, in HCEC-1CT parental cells and a CREBBP KO single cell clone, to determine whether or not there are differences in the levels and/or distribution of the mark between WT and CREBBP KO cells

2025-03-25 | GSE276948 | GEO

Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (ChIP-Seq)

Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. DNA binding of TSC22D3 in Th17 cells compared to WCE

2013-03-07 | E-GEOD-43949 | biostudies-arrayexpress

Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (Th17 differentiation timecourse)

Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. Time course microarray data for Th17 differentiation, including Th0 control

2013-03-07 | E-GEOD-43955 | biostudies-arrayexpress

Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (RNA-Seq)

Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. RNA-seq of knockdown of 12 genes in Th17 cell differentiation

2013-03-07 | E-GEOD-43948 | biostudies-arrayexpress

Systematic Perturbation of Thousands of Retroviral LTRs in Mouse Embryos

Project description:Systematic Perturbation of Thousands of Retroviral LTRs in Mouse Embryos

| PRJNA1011387 | ENA

Reconstruction of the dynamic regulatory network that controls Th17 cell differentiation by systematic perturbation in primary cells (Affymetrix timecourse IL23 KO)

Project description:Despite their enormous importance, the molecular circuits that control the differentiation of Th17 cells remain largely unknown. Recent studies have reconstructed regulatory networks in mammalian cells, but have focused on short-term responses and relied on perturbation approaches that cannot be applied to primary T cells. Here, we develop a systematic strategy – combining transcriptional profiling at high temporal resolution, novel computational algorithms, and innovative nanowire-based tools for performing gene perturbations in primary T cells – to derive and experimentally validate a temporal model of the dynamic regulatory network that controls Th17 differentiation. The network is arranged into two self-reinforcing and mutually antagonistic modules that either suppress or promote Th17 differentiation. The two modules contain 12 novel regulators with no previous implication in Th17 differentiation, which may be essential to maintain the appropriate balance of Th17 and other CD4+ T cell subsets. Overall, our study identifies and validates 39 regulatory factors that are embedded within a comprehensive temporal network and identifies novel drug targets and organizational principles for the differentiation of Th17 cells. Time course microarray data for Th17 differentiation, comparing IL23r-/- to WT

2013-03-07 | E-GEOD-43969 | biostudies-arrayexpress

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