Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

GNPS - Monotropa mzml file annotation

ABSTRACT: Untargeted metabolomic profile for Monotropa uniflora in both the positive and negative modes.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Monotropa Uniflora (ncbitaxon:50148)

SUBMITTER: Josh J Kellogg

PROVIDER: MSV000095253 | GNPS | Thu Jul 04 20:39:00 BST 2024

REPOSITORIES: GNPS

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Monotropa mzml file annotation

Project description:Untargeted metabolomic profile for Monotropa uniflora in both the positive and negative modes.

2024-07-04 | MSV000095253 | MassIVE

Monotropa_MS2 Analysis for Molecular Networking

Project description:Untargeted LC-MS profiling of M. uniflora in the positive and negative modes for MS2 molecular networking and annotation.

2024-06-24 | MSV000095135 | MassIVE

Ancient DNA teeth

Project description:The data set contains MS/MS data on teeth extracts for Ancient DNA teeth samples ran in both positive and Negative ionization modes

2018-12-19 | MSV000083264 | MassIVE

Liver-specific deletion of Agpat5 protects against liquid sucrose induced hyperinsulinemia and glucose intolerance

Project description:Untargeted lipidomics of liver samples, both in positive and negative mode

2024-11-20 | MSV000096473 | MassIVE

Untargeted metabolomics in seeds of Arabidopsis wild-type, TT7 KO and other flavonoid mutants

Project description:Seeds of Arabidopsis thaliana wild type and knockout-mutants for flavonoid genes (tt7 [3 lines], fls1, tt3, tt4, tt7tt4 [2 lines] ) were subjected to untargeted metabolomic analyses (LC-MS/MS) in positive and negative ionisation mode.

2024-10-25 | MSV000096214 | MassIVE

Whole chromosome duplications drive antimicrobial resistance in Aspergillus fumigatus

Project description:Secondary metabolite profiles of Aspergillus fumigatus aneuploids, WT, and nscROE strains under FK506 stress. Data include both positive and negative ionization modes from a 25-minute reverse-phase run conducted in 2025.

2025-11-08 | MSV000099800 | MassIVE

Untargeted Serum Metabolomics Reveals Differential Signatures in Gallstone-Associated and Gallstone-Free Gallbladder Cancer

Project description:<p>Gallbladder cancer (GBC) is an aggressive malignancy often associated with gallstones (GBCGS), a condition distinct from gallstone disease (GSD). Both GBC and GBCGS are rare, with unclear pathogenesis and no established biomarker-based solutions. This pilot study aimed to identify distinct metabolic signatures in GBC and GBCGS for early diagnosis and stratification of high-risk GSD patients. A comparative untargeted serum metabolomic profiling was performed across three patient groups: GBC (n1=9), GBCGS (n2=11), and GSD (n3=10). A total of 35,385 mass-features in both positive and negative ionization modes with MS/MS characteristics were detected and annotated into 736 biochemicals.</p>

2025-12-22 | MTBLS12514 | MetaboLights

Decoding the metabolomic composition of Punarnava (Boerhavia diffusa L.), a component of Ayurvedic medicines

Project description:Punarnava [Boerhaavia diffusa L.] is a medicinal plant and constituent of several Indian traditional medicines. According to Ayurveda, this plant is a rich source of nutrients. Traditionally, it is used to provide relief against various gastrointestinal disorders, treat wounds, reduce joint pains, and as an anti-stress agent. Despite its pharmacological importance, detailed characterization of the metabolite composition of this plant has not been reported to date. Therefore, we have taken up metabolomic profiling of Punarnava choorna, as part of a larger project of metabolomic profiling of ayurvedic drugs. We carried out a global metabolomic analysis using a high-resolution mass spectrometry to investigate metabolite composition of Punarnava choorna. In total 1747 and 4031 features were identified at MS1 using XCMS in the positive and negative modes, respectively. Using MS2Compound, we identified 1229 and 709 features in the positive and negative modes, respectively. We also identified 362 and 191 metabolites at MS2 level in the positive and negative modes, respectively using the MS2Compound tool. The data were searched against the PlantCyc, KEGG, PhenolExplorer and HMDB databases. A large number of nutritionally important metabolites including amino acids, sugars and vitamins were identified in Purnarnava choorna. Further, the identified metabolites were mapped to their potential protein interactors using BindingDB tool. Highest number of interactions was observed for plant serotonins. The data provides molecular evidence to accelerate the discovery of mode of action of Purnarnava choorna.

2021-08-11 | MSV000087969 | MassIVE

Metabolomic and Proteomic Analysis of Renal Function After Liver Transplantation

Project description:Background: Renal dysfunction is a common and serious complication in patients with end-stage liver diseases. While some patients recover renal function after liver transplantation (LT), others do not. Additionally, patients with normal kidney function (Normal-KF) before LT may develop post-transplant renal dysfunction. Early identification of patients at risk for impaired kidney function (Impaired-KF) post-LT is critical to improving outcomes. This study integrated metabolomic and proteomic analyses to investigate molecular profiles distinguishing Normal-KF from Impaired-KF post-LT. Methods: Nine LT recipients were classified into Normal-KF (n=5) and Impaired-KF (n=4) groups. One additional recipient with pre-transplant renal function impairment who recovered renal function after LT, was analyzed separately. Plasma samples were collected at 2- and 5-weeks post-LT. The metabolomic and proteomic profiles were assessed by untargeted liquid chromatography-tandem mass spectrometry. Results: Metabolomic analysis identified 29 significantly altered metabolites between Normal-KF and Impaired-KF (fold change>2, p<0.05). Proteomic analysis revealed 45 differentially expressed proteins (fold change>1.25, p<0.05). For the recovered patient, the metabolomic profile closely resembled Normal-KF, whereas the proteomic profile remained aligned with Impaired-KF at both 14- and 35-days post-LT. From week 2 to week 5, both the metabolomic and proteomic profiles of the recovered patient showed trends toward the Normal-KF. Conclusion: This study revealed distinct metabolomic and proteomic signatures associated with renal dysfunction post-LT. Proteomic profiles indicated a delayed recovery compared to metabolomic profiles, suggesting a dynamic and muti-layered renal recovery process. Further research is warranted to elucidate the functional implications of the differential proteins and metabolites for improved monitoring and therapeutic strategies.

2025-05-26 | PXD062924 | Pride

Untargeted serum metabolomics of ulcerative colitis patients vs healthy subjects using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry

Project description:Metabolic profiling of serum samples were performed on an Agilent 1290 infinity system (Agilent technologies, Santa-Clara, California, USA) coupled to an AB SCIEX Triple TOF 6600 System (AB SCIEX, Framingham, MA, USA) with an electrospray ion (ESI) source in both positive and negative ion modes. There were 30 differential metabolites under positive ion mode and 23 differential metabolites under negative ion mode, respectively.

2024-09-27 | MTBLS7438 | MetaboLights

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