Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Pathogen detection

PROVIDER: PRJNA944830 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR23871800_1.fastq.gz	Fastqsanger.gz
	SRR23871800_2.fastq.gz	Fastqsanger.gz
	SRR23871801_1.fastq.gz	Fastqsanger.gz
	SRR23871801_2.fastq.gz	Fastqsanger.gz
	SRR23871802_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 18

Similar Datasets

Optimization and Clinical Validation of a Pathogen Detection Microarray

Project description:This series includes microarrays from 36 patient samples and 2 cell-culture controls, used to optimize and validate the pathogen detection microarray (Wong, et. al. 2007) Keywords: viral pathogen detection

2007-05-29 | GSE7779 | GEO

Project description:Pathogen Detection Assembly Project

| PRJNA514245 | ENA

Project description:Detection of pathogen with mNGS

| PRJNA842783 | ENA

Homo sapiens

Project description:Pathogen detection in human serum

| PRJNA516238 | ENA

Dual spatially resolved transcriptomics for SARS-CoV-2 host-pathogen colocalization studies in humans

Project description:To advance our understanding of cellular host-pathogen interactions, technologies that facilitate the co-capture of both host and pathogen spatial transcriptome information are needed. Here, we present an approach to simultaneously capture host and pathogen spatial gene expression information from the same formalin-fixed paraffin embedded (FFPE) tissue section using the spatial transcriptomics technology. We applied the method to COVID-19 patient lung samples and enabled the dual detection of human and SARS-CoV-2 transcriptomes at 55 Ã‚Âµm resolution. We validated our spatial detection of SARS-CoV-2 and identified an average specificity of 94.92% in comparison to RNAScope and 82.20% in comparison to in situ sequencing (ISS). COVID-19 tissues showed an upregulation of host immune response, such as increased expression of inflammatory cytokines, lymphocyte and fibroblast markers. Our colocalization analysis revealed that SARS-CoV-2+ spots presented shifts in host RNA metabolism, autophagy, NFÃŽÂºB, and interferon response pathways. Future applications of our approach will enable new insights into host response to pathogen infection through the simultaneous, unbiased detection of two transcriptomes.

| EGAS00001006186 | EGA

Methylome of Salmonella enterica subsp. Enterica serovar Javiana str. CFSAN001992 by PacBio SMRT Sequencing

Project description:Single-molecule read technologies allow for detection of epigenomic base modifications during routine sequencing by analysis of kinetic data during the reaction, including the duration between base incorporations at the elongation site (the "inter-pulse duration.") Methylome data associated with a closed de novo bacterial genome of Salmonella enterica subsp. enterica serovar Javiana str. CFSAN001992 was produced and submitted to the Gene Expression Omnibus. Single-sample sequencing and base modification detection of cultured isolate of a foodborne pathogen.

2013-03-15 | E-GEOD-45178 | biostudies-arrayexpress

Project description:Clinical Pathogen Detection Using PMSEQ Technology

| PRJNA811310 | ENA

DNA microarray for STD pathogen detection

Project description:DNA microarray for STD pathogen detection

| PRJNA285757 | ENA

An Emerging Threat to Honey Bees from the Parasitic Phorid Fly Apocephalus borealis

Project description:Pathogen detection microarrays analyzing honeybee samples taken after parasitization with a predatory fly, oligos correspond to specific pathogens or pathogen families of viruses, bacteria, fungi, protists, and other parasites Samples were analyzed with the E-Predict analysis package.

2012-08-01 | GSE29749 | GEO

Temporal Analysis of the Honey Bee Microbiome Reveals Four Novel Viruses and Seasonal Prevalence of Known Viruses, Nosema, and Crithidia

Project description:Pathogen detection microarrays analyzing honeybee samples taken from the same hives over the course of a year, oligos correspond to specific pathogens or pathogen families of viruses, bacteria, fungi, protists, and other parasites Samples were analyzed with the E-Predict analysis package

2011-06-06 | GSE28235 | 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