Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Spike-in experiments (Structure-informed deep generation enables de novo metabolite annotation in untargeted metabolomics)

ABSTRACT: MetGenX is a structure-informed encoder-decoder neural network that enables efficient and controllable generation of metabolite structures directly from MS2 spectra. By reformulating the spectrum-to-structure task as a structure-to-structure generation problem, MetGenX significantly improves generation accuracy and chemical space coverage. This dataset collection covers NIST plasma and Mouse liver with 200 metabolite standards spiked. This dataset provide a valuable resource for the development, benchmarking, and validation of metabolomics annotation algorithms across diverse biological matrices.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Homo Sapiens (ncbitaxon:9606) Mus Musculus (ncbitaxon:10090)

SUBMITTER: Zhu Zheng-Jiang

PROVIDER: MSV000101078 | MassIVE | Mon Mar 09 19:46:00 GMT 2026

REPOSITORIES: MassIVE

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

MetDNA3 Astral datasets (Knowledge and Data-driven Two-layer Networking for Accurate Metabolite Annotation in Untargeted Metabolomics)

Project description:MetDNA3 Astral datasets were generated using the high-resolution Thermo Fisher Orbitrap Astral mass spectrometry platform and annotated with MetDNA3, which integrates a Knowledge- and Data-driven Two-layer Networking strategy for accurate metabolite annotation in untargeted metabolomics. This dataset collection covers a variety of sample types, including: NIST plasma, NIST urine, Mouse liver. These datasets provide a valuable resource for the development, benchmarking, and validation of metabolomics annotation algorithms across diverse biological matrices.

2025-05-19 | MSV000097914 | MassIVE

MetDNA3 Exploris 480 datasets (Knowledge and Data-driven Two-layer Networking for Accurate Metabolite Annotation in Untargeted Metabolomics)

Project description:MetDNA3 Exploris 480 datasets were generated using the high-resolution Thermo Fisher Exploris 480 mass spectrometry platform and annotated with MetDNA3, which integrates a Knowledge- and Data-driven Two-layer Networking strategy for accurate metabolite annotation in untargeted metabolomics. This dataset collection covers a variety of sample types, including: NIST plasma, NIST urine, BV2 cell, Mouse brain, Mouse liver. These datasets provide a valuable resource for the development, benchmarking, and validation of metabolomics annotation algorithms across diverse biological matrices.

2025-05-19 | MSV000097913 | MassIVE

A systematic and validated Fe(II)-EDTA method of hydroxyl radical generation for oxidative protein footprinting

Project description:Correlating the structure and dynamics of proteins with biological function is critical to understanding normal and dysfunctional cellular mechanisms. We describe a quantitative method of hydroxyl radical generation via Fe(II)-EDTA catalyzed Fenton chemistry that provides easy access to oxidative protein footprinting using equipment commonly found in research and process control laboratories. Robust and reproducible dose-dependent oxidation of protein samples is observed and quantitated by mass spectrometry with as fine as single residue resolution. An oxidation analysis of lysozyme provides a readily accessible benchmark for our method. The efficacy of our oxidation method is demonstrated through mapping the interface of a RAS monobody complex, the surface of the NIST mAb, and the interface between PRC2 complex components. These studies are executed using standard laboratory tools and a few pennies of reagents; the mass spectrometry analysis can be streamlined to map protein structure with single amino acid residue resolution. All mass spectrometry raw files for this study are included here.

| MSV000092853 | MassIVE

3D chromatin structure in colon cancer

Project description:We report the application of in situ Hi-C technology to 40 colorectal cancer patients and 10 paired-normal tissue to identify CRC specific changes in 3D chromatin structure. The chromatin contact matrices were generated by the sequencing data and image processing/deep learning-based algorithm was proposed to identify long-range abnormal chromatin interaction patterns in the contact matrices. The tumor specific 3D chromatin structure changes and the enhancer-promoter rewiring mediated by the identified chromatin structure changes were analyzed. The complex chromosome-wide rearrangements such as chromothripsis and its effect to 3D chromatin structure were also observed.

2023-07-27 | GSE137188 | GEO

Next Generation Sequencing on HMEC-1 or HUVEC residing on SOFT or STIFF matrices

Project description:Next Generation Sequencing on HMEC-1 or HUVEC residing on SOFT or STIFF matrices

| PRJNA557476 | ENA

Next-generation sequencing of anterior cingulate cortex neurons in a social problem setting in rats

Project description:Next-generation sequencing of anterior cingulate cortex neurons in a social problem setting in rats

| PRJNA643543 | ENA

A supervised Bayesian method for time (re)annotation of transcriptomics data

Project description:We propose a Bayesian method based on Gaussian process regression modeling to solve the problem. We use it to perform time annotation in old \textit{Clostridium botulinum} microarray experiments by utilising recently collected RNA-Seq time series. Additionally, we apply the method to time annotate RNA-Seq experiments and test its robustness toward noise on synthetically generated data.

2025-03-26 | GSE261398 | GEO

An extracellular matrix niche secreted by epithelial cells drives intestinal organoid formation (RNA-seq)

Project description:An ill-defined laminin-rich three-dimensional (3D) extracellular matrix (ECM) is typically used for the generation of organoids, but little is known about its function. Here, using tunable and chemically defined 3D hydrogels, we systematically explored the role of the ECM during murine intestinal organoid development. Our results highlight the utility of chemically defined matrices for studying ECM biology in tissue engineering and pave the way for the replacement of animal-derived matrices in organoid culture.

2025-05-21 | GSE293374 | GEO

Metagenome representing 10 spiked-in bacteria

Project description:NIST - CosmosID Metagenomics MVP Challenge

| PRJNA495173 | ENA

Project description:NIST RM 8376 Use Cases

| PRJNA1074773 | ENA