Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Diabetic_vaginal_samples

ABSTRACT: Mother vaginal microbiome and child type I diabetes: machine learning approach suggests altered bacteriome and mycobiome

PROVIDER: PRJNA751475 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR15330242.fastq.gz	Fastqsanger.gz
	SRR15330243.fastq.gz	Fastqsanger.gz
	SRR15330244.fastq.gz	Fastqsanger.gz
	SRR15330245.fastq.gz	Fastqsanger.gz
	SRR15330246.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 49

Similar Datasets

Fungal vaginal microbiome

Project description:Mother vaginal microbiome and child type I diabetes: machine learning approach suggests altered bacteriome and mycobiome

| PRJNA751714 | ENA

Longitudinal serum proteomics of mother-infant dyads with HLA-conferred type 1 diabetes risk

Project description:LC-MS/MS analysis formula was performed for sera from 22 mother-infant dyads with HLA-conferred susceptibility to type 1 diabetes that were weaned to either an extensively hydrolyzed or regular infant milk. The samples included three samples from each mother (at the beginning of third trimester, at the time of delivery and 3 months postpartum) and five samples from each child (cord blood, 3, 6, 9 and 12 months). Targeted proteomics was used to validate differences observed between the feeding groups.Correlations in protein intensities within the dyads were detected together with perinatal and age-related changes.

2024-05-27 | PXD046387 | Pride

Gut microbiome

Project description:HSP child-mother pairs and matched healthy child-mother pairs sequence.

| PRJNA497481 | ENA

Project description:Mother vaginal microbiome correlates with occurrence of child type I diabetes in a pilot study Raw sequence reads

| PRJNA433609 | ENA

Project description:The oral microbiome of ASD mother-child pairs and healthy mother-child pairs

| PRJNA559058 | ENA

Project description:Gut microbiota mother-child overlap

| PRJNA433118 | ENA

Proteomic datasets for the identification of endometrial cancer in minimally invasive samples (cervico-vaginal fluid and blood plasma).

Project description:The aim of the underlying study was to identify protein signatures for the detection of endometrial cancer in minimally invasive samples such as cervico-vaginal fluid and blood plasma. Plasma and Delphi Screener-collected cervico-vaginal fluid samples were acquired from post-menopausal women who were symptomatic with (n=53)and without(n=65)endometrial cancer. Digitised proteomic maps were developed for each sample by sequential window acquisition of all theoretical mass spectra (SWATH-MS). Machine learning was employed to identify the most discriminatory proteins and a set of high-perfoming biomarker signatures obtained.

2024-06-23 | PXD050276 | Pride

Preterm Birth Buccal Cell Epigenetic Biomarkers to Facilitate Preventative Medicine

Project description:Preterm birth is the major cause of newborn and infant mortality affecting nearly one in every ten live births. This study was designed to develop an epigenetic biomarker for susceptibility of preterm birth using buccal cells from the mother, father, and child (triads). MeDIP-seq was used to identify differential DNA methylation regions (DMRs) using a comparison of control term birth versus preterm birth triads. Epigenetic DMR associations with preterm birth were identified for both the mother and father that were distinct and suggest potential epigenetic contributions from both parents. The mother (165 DMRs) and female child (136 DMRs) at p<1e-04 had the highest number of DMRs and were highly similar suggesting potential epigenetic inheritance of the epimutations. The male child had negligible DMR associations. The DMR associated genes for each group involve previously identified preterm birth associated genes.

2022-03-09 | GSE194227 | GEO

Project description:WES of a DS child mother

| PRJNA1059249 | ENA

Single cell RNA-seq of human pancreatic endocrine cells from Juvenile, adult control and type 2 diabetic donors.

Project description:We successfully sequenced and annotated more than 400 cells from child, adult control, type 1 diabetes and type 2 diabetes donors. We detect donor-type specific transcript variation. We also report that cells from child donors have less defined gene signature. Cells from type 2 diabetes donors resemble juvenile cells in gene expression. Cells from three adult controls (56, 74, 92), one donor with type 1 diabetes (91), two donors with type 2 diabetes (75, 143), and two child donors (40, 72) were sequenced. Numbers in parathesis indicates number of cells sequenced.

2016-07-05 | E-GEOD-83139 | 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