Proteomics

Dataset Information

0

Molecular Signatures of Preeclampsia and Gestational Diabetes Mellitus Utilizing Multi-Omics Analyses, Part 2


ABSTRACT: The application of multi-omic evaluations, multi-dimensional analysis methods, and new cheminformatics-based visualization tools to provide an in depth understanding of the molecular changes taking place in preeclampsia (PRE) and gestational diabetes mellitus (GDM) patients. Since PRE and GDM are two prevalent pregnancy complications that result in adverse health effects for both the mother and fetus during pregnancy and later in life, a better understanding of each is essential. The multi-omic evaluations performed here provide new insight into the end-stage molecular profiles of each disease, thereby supplying crucial information for earlier diagnosis and potential treatments. Datasets here represent lipid samples analyzed via Ion Mobility Mass Spectrometry.

INSTRUMENT(S): 6510 Quadrupole Time-of-Flight LC/MS

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Erin S. Baker   Kristin E. Burnum-Johnson  

PROVIDER: MSV000085361 | MassIVE | Sat May 02 17:51:00 BST 2020

REPOSITORIES: MassIVE

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1
altmetric image

Publications

Unveiling molecular signatures of preeclampsia and gestational diabetes mellitus with multi-omics and innovative cheminformatics visualization tools.

Odenkirk Melanie T MT   Stratton Kelly G KG   Gritsenko Marina A MA   Bramer Lisa M LM   Webb-Robertson Bobbie-Jo M BM   Bloodsworth Kent J KJ   Weitz Karl K KK   Lipton Anna K AK   Monroe Matthew E ME   Ash Jeremy R JR   Fourches Denis D   Taylor Brandie D BD   Burnum-Johnson Kristin E KE   Baker Erin S ES  

Molecular omics 20200923 6


To fully enable the development of diagnostic tools and progressive pharmaceutical drugs, it is imperative to understand the molecular changes occurring before and during disease onset and progression. Systems biology assessments utilizing multi-omic analyses (e.g. the combination of proteomics, lipidomics, genomics, etc.) have shown enormous value in determining molecules prevalent in diseases and their associated mechanisms. Herein, we utilized multi-omic evaluations, multi-dimensional analysi  ...[more]

Similar Datasets

2020-05-01 | MSV000085357 | MassIVE
2020-05-01 | MSV000085357 | GNPS
2021-12-31 | GSE154414 | GEO
2021-12-16 | MSV000088572 | MassIVE
2017-04-22 | GSE98043 | GEO
2020-07-07 | GSE144276 | GEO
2023-08-28 | BIOMD0000001075 | BioModels
2021-02-02 | ST001681 | MetabolomicsWorkbench
2024-07-30 | GSE263483 | GEO
| PRJNA430482 | ENA