Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Next Generation Sequencing Facilitates Quantitative Analysis of overexpression of KLF14 in mouse primary hepatocytes and control cells

ABSTRACT: Purpose: KLF14 gene is closely linked to the development of Type 2 diabetes. The goals of this study are to compare KLF14-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

ORGANISM(S): Mus musculus

PROVIDER: GSE105048 | GEO | 2020/10/16

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Bat3-/- BMDC Transcriptomes II

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2022-01-11 | GSE169550 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of control smooth muscle cells and Tet3-inactivation smooth muscle cells transcriptomes

2022-09-20 | GSE166816 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and osmads58-/- Panicles Transcriptomes

Project description:Purpose: The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Conclusions: Our study represents the detailed analysis of panicles transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles.

2021-08-12 | GSE181713 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Normal Human Kidney Transcriptomes

Project description:Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived normal human kidney transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2014-08-06 | GSE60119 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of BALB/C mice skin Transcriptomes

Project description:Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived skin transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2023-07-29 | GSE238152 | GEO

Quantitative Analysis of transcriptome in organoids derived from TP190 wildtype(WT) and Williams Syndrome(NSUN-GTF2ird2+/-) human induced Pluripotent Stem Cell

2022-09-23 | GSE195505 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Zfyve19-/- hepatic Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived hepatic transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2021-03-27 | GSE169737 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild and spinal cord injury mice

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived intervertebral disc transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2021-06-26 | GSE178930 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild and intervertebral disc degeneration mice

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived intervertebral disc transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2024-10-16 | GSE189551 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild and Myocardial ischemia-reperfusion injury

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived myocardial transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2024-07-15 | GSE180142 | 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