Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

The Microbial Detection Array for Detection of Emerging Viruses in Clinical Samples - A Useful Panmicrobial Diagnostic Tool

ABSTRACT: The Microbial Detection Array for Detection of Emerging Viruses in Clinical Samples - A Useful Panmicrobial Diagnostic Tool

PROVIDER: PRJNA227497 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

The Microbial Detection Array for Detection of Emerging Viruses in Clinical Samples - A Useful Panmicrobial Diagnostic Tool

Project description:Emerging viruses are usually endemic to tropical and sub-tropical regions of the world, but increased global travelling, climate changes and changes in lifestyle are believed to contribute to the spread of these viruses into new regions. For many of them, the disease symptoms are similar to each other, as well as to other more common diseases, making them difficult to diagnose. A rapid identification will help to decide about specific treatment and appropriate case management. Real-time PCR is commonly used for specific virus detection in clinical samples. A diagnostic microarray containing probes for all human viruses, could replace hundreds of specific PCR-reactions and identify all viruses by one assay and thereby remove the need for a clear clinical hypothesis. We show that the Microbial Detection Array successfully identifies emerging viruses present in both non-clinical and clinical samples. Fifteen clinical samples and 27 non-clinical samples (cell culture supernantants or purified viral DNA or RNA) were analyzed for presence of emerging viruses using the MDA microarray.

2013-11-15 | E-GEOD-52324 | biostudies-arrayexpress

The Microbial Detection Array for Detection of Emerging Viruses in Clinical Samples - A Useful Panmicrobial Diagnostic Tool

2013-11-15 | GSE52324 | GEO

The Microbial Detection Array for Detection of Emerging Viruses in Clinical Samples - A Useful Panmicrobial Diagnostic Tool--Array Version 2f

Project description:Emerging viruses are usually endemic to tropical and sub-tropical regions of the world, but increased global travelling, climate changes and changes in lifestyle are believed to contribute to the spread of these viruses into new regions. For many of them, the disease symptoms are similar to each other, as well as to other more common diseases, making them difficult to diagnose. A rapid identification will help to decide about specific treatment and appropriate case management. Real-time PCR is commonly used for specific virus detection in clinical samples. A diagnostic microarray containing probes for all human viruses, could replace hundreds of specific PCR-reactions and identify all viruses by one assay and thereby remove the need for a clear clinical hypothesis. We show that the Microbial Detection Array successfully identifies emerging viruses present in both non-clinical and clinical samples. Twenty-four clinical samples and 40 non-clinical samples (cell culture supernantants or purified viral DNA or RNA) were analyzed for presence of emerging viruses using the MDA microarray.

2014-03-05 | E-GEOD-55576 | biostudies-arrayexpress

The Microbial Detection Array for Detection of Emerging Viruses in Clinical Samples - A Useful Panmicrobial Diagnostic Tool--Array Version 2f

2014-03-05 | GSE55576 | GEO

The Microbial Detection Array for Detection of Emerging Viruses in Clinical Samples - A Useful Panmicrobial Diagnostic Tool--Array Version 2f

Project description:The Microbial Detection Array for Detection of Emerging Viruses in Clinical Samples - A Useful Panmicrobial Diagnostic Tool--Array Version 2f

| PRJNA240111 | ENA

The microbial detection array for detection of emerging viruses in clinical samples--a useful panmicrobial diagnostic tool.

Project description: Not available

| S-EPMC4070998 | biostudies-literature

The Microbial Detection Array Combined with Random Phi29-Amplification used as a Diagnostic Tool for Unbiased Virus Detection in Clinical Samples

Project description:A common technique used for sensitive and specific diagnostic virus detection in clinical samples is PCR. However, an unbiased diagnostic microarray containing probes for all human pathogens could replace hundreds of individual PCR-reactions and remove the need for a clear clinical hypothesis regarding a suspected pathogen. We have established such a diagnostic platform for unbiased random amplification and subsequent microarray identification of viral pathogens in clinical samples. We show that Phi29 polymerase-amplification of a diverse set of clinical samples generates enough viral material for successful identification by the Microbial Detection Array developed at the Lawrence Livermore National Laboratory, California, USA, demonstrating the potential of the microarray technique for broad-spectrum pathogen detection. We conclude that this method detects both DNA and RNA virus, present in the same sample, as well as differentiates between different virus subtypes. We propose this assay for unbiased diagnostic analysis of all viruses in clinical samples.

2011-04-14 | GSE28597 | GEO

The Microbial Detection Array Combined with Random Phi29-Amplification used as a Diagnostic Tool for Unbiased Virus Detection in Clinical Samples

2011-04-14 | E-GEOD-28597 | biostudies-arrayexpress

Design of a Diagnostic Pan-Pathogen Oligonucleotide Microarray including a sub-Array for Detection of Meningitis-Causing Bacterial Pathogens

Project description:Meningitis is a complex disease which can be caused by infection with either viral or bacterial pathogens. Viral meningitis is usually a sterile self-limiting disease with a good clinical prognosis, while bacterial meningitis is a potentially more serious disease with a higher mortality rate. Early diagnosis of bacterial meningitis is of paramount importance, as intervention with antimicrobial therapy increases the likelihood of a favourable clinical outcome. Routine diagnosis in many laboratories is still dependent to some degree on traditional methods e.g. culture, though molecular methods have been developed which can give a shorter time to diagnosis. However, there is not as yet a single test format that can detect all bacterial pathogens capable of causing meningitis. In addition, many tests e.g. real-time PCR have a finite limit for multiplexing and do not provide additional information such as strain or serogroup which is useful during outbreaks and for retrospective epidemiological surveillance. To this end we have developed a microarray probe set for detection of meningitis-associated bacterial pathogens including those in the N. meningitidis serogroups. Here we demonstrate utility of this array in specific detection of represented bacterial species and strains and in detection of pathogen signals in cerebrospinal fluid samples from patients with suspected bacterial meningitis. This method shows promise for development as a diagnostic tool; however, we discuss the technical issues encountered and suggest mechanisms to improve resolution of pathogen-specific signals in complex clinical samples.

2011-07-20 | GSE30794 | GEO

Tumor microRNA expression profiling identifies circulating microRNAs for earlier breast cancer detection

Project description:Due to their role in tumorigenesis and remarkable stability in body fluids, microRNAs (miRNAs) are emerging as a promising diagnostic tool. The aim of this study was to identify tumor miRNA signatures for the discrimination of breast cancer and the intrinsic molecular subtypes, and the study in plasma of the status of the most significant ones in order to identify potential circulating biomarkers for breast cancer detection.

2015-09-03 | GSE58606 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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