Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: RNA-Seq data of Cyrtorhinus lividipennis

PROVIDER: PRJNA671572 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR12886579_1.fastq.gz	Fastqsanger.gz
	SRR12886579_2.fastq.gz	Fastqsanger.gz
	SRR12886580_1.fastq.gz	Fastqsanger.gz
	SRR12886580_2.fastq.gz	Fastqsanger.gz
	SRR12886581_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 16

Similar Datasets

Project description:RNA-Seq data of Cyrtorhinus lividipennis

| PRJNA699972 | ENA

Cyrtorhinus lividipennis

Project description:Cyrtorhinus lividipennis overview

| PRJNA503283 | ENA

Cyrtorhinus lividipennis

Project description:Cyrtorhinus lividipennis Raw sequence reads

| PRJNA348378 | ENA

Cyrtorhinus lividipennis

Project description:Cyrtorhinus lividipennis Raw sequence reads

| PRJNA421236 | ENA

Cyrtorhinus lividipennis

Project description:Cyrtorhinus lividipennis Genome sequencing and assembly

| PRJNA668646 | ENA

Cyrtorhinus lividipennis

Project description:Cyrtorhinus lividipennis adults antennal Raw sequence reads

| PRJNA428895 | ENA

Project description:Novel gene rearrangement in the complete mitochondrial genome of Cyrtorhinus lividipennis Reuter (Hemiptera: Miridae)

| PRJNA848123 | ENA

Diel multi-tissue genome-scale metabolic models of Vitis vinifera

Project description:The first GSSM of V. vinifera was reconstructed (MODEL2408120001). Tissue-specific models for stem, leaf, and berry of the Cabernet Sauvignon cultivar were generated from the original model, through the integration of RNA-Seq data. These models have been merged into diel multi-tissue models to study the interactions between tissues at light and dark phases.

2024-09-02 | MODEL2408160001 | BioModels

Benchmarking differential expression, imputation and quantification methods for proteomics data

Project description:Data analysis is a critical part of quantitative proteomics studies in interpreting biological questions. Numerous computational tools including protein quantification, imputation, and differential expression (DE) analysis were generated in the past decade. However, searching optimized tools is still an unsolved issue. Moreover, due to the rapid development of RNA-Seq technology, a vast number of DE analysis methods are created. Applying these newly developed RNA-Seq-oriented tools to proteomics data is still a question that needs to be addressed. In order to benchmark these analysis methods, a proteomics dataset constituted the proteins derived from human, yeast, and drosophila with different ratios were generated. Based on this dataset, DE analysis tools (including array-based and RNA-Seq based), imputation algorithms, and protein quantification methods were compared and benchmarked. This study provided useful information on analyzing quantitative proteomics datasets. All the methods used in this study were integrated into Perseus which are available at https://www.maxquant.org/perseus.

2022-11-16 | PXD029891 | JPOST Repository

A data-independent acquisition (DIA)-based proteomic analysis ofAcer truncatum Seeds

Project description:We performed RNA-seq and Ribo-seq analyses to elucidate the translation in seeds at 85 and 115 DAF. We also completed a data-independent acquisition (DIA)-based proteomic analysis, while also examining relevant lipid metabolites.

2023-03-01 | PXD040512 |

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