What is the Metabolomics Workbench?

The Metabolomics Workbench is an NIH-sponsored platform hosted at UCSD that serves as the primary repository for metabolomics research data, providing access to over 4,200 processed studies.

Does this skill support different analytical methods?

Yes, it can filter studies and data based on analytical platforms including LC-MS, GC-MS, and NMR, as well as chromatography types like HILIC and RP.

Can I retrieve gene and protein data with this skill?

Yes, the skill can query gene and protein information associated with specific metabolic pathways, including cross-references to RefSeq and UniProt IDs.

What is RefMet nomenclature?

RefMet is a standardized naming convention for metabolites. This skill uses it to resolve naming ambiguities and ensure consistent classification across different scientific datasets.

How does this skill assist with mass spectrometry?

It allows you to perform m/z (mass-to-charge ratio) searches with specified ion adducts and tolerance levels to identify potential metabolites directly within your AI workflow.

Metabolomics Workbench Database

Name: Metabolomics Workbench Database
Author: ricable

byricable

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Ciencia de Datos y ML

Integrates with the NIH Metabolomics Workbench REST API to query metabolite data, standardized nomenclature, and experimental studies for biomarker discovery.

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This skill provides programmatic access to the NIH Common Fund-sponsored Metabolomics Workbench, the primary repository for metabolomics research. It allows users to query over 4,200 processed studies, access standardized metabolite nomenclature through RefMet, and perform mass spectrometry searches using m/z values. Whether performing biomarker discovery, standardizing chemical names, or retrieving experimental datasets from GC-MS, LC-MS, and NMR platforms, this tool streamlines scientific research by connecting AI analysis with verified experimental data.

Características Principales

Access to 4,200+ processed metabolomics studies and detailed metadata
Mass spectrometry search capabilities by m/z ratio and ion adducts
Integration of gene and protein-metabolite association data
Metabolite nomenclature standardization using the RefMet database
Retrieval of metabolite structures, identifiers (PubChem, KEGG), and classifications
1 GitHub stars

Casos de Uso

Standardizing chemical nomenclature in research datasets to facilitate meta-analysis
Identifying disease-specific metabolomics studies across different analytical platforms
Automating metabolite identification from raw mass spectrometry m/z data

Acerca de

Características Principales

Access to 4,200+ processed metabolomics studies and detailed metadata
Mass spectrometry search capabilities by m/z ratio and ion adducts
Integration of gene and protein-metabolite association data
Metabolite nomenclature standardization using the RefMet database
Retrieval of metabolite structures, identifiers (PubChem, KEGG), and classifications
1 GitHub stars

Casos de Uso

Standardizing chemical nomenclature in research datasets to facilitate meta-analysis
Identifying disease-specific metabolomics studies across different analytical platforms
Automating metabolite identification from raw mass spectrometry m/z data