What is RefMet and why is it used?

RefMet is a standardized nomenclature system for metabolites. This skill uses it to resolve inconsistent naming across different research platforms and studies.

How does this skill help with mass spectrometry?

It allows Claude to search for compounds using mass-to-charge (m/z) ratios across databases like LIPIDS and RefMet with specified ion adducts and mass tolerances.

Does this skill support gene and protein associations?

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

What is the Metabolomics Workbench?

The Metabolomics Workbench is a comprehensive NIH-sponsored platform that serves as a repository for metabolomics research data, providing access to thousands of processed studies and metabolite structures.

Can I use this for biomarker discovery?

Yes, you can filter studies by species, sample source, and disease state (e.g., Cancer or Diabetes) to identify relevant metabolites and experimental results.

Metabolomics Workbench Database

Name: Metabolomics Workbench Database
Author: jimmc414

byjimmc414

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324

Data Science & ML

Accesses NIH Metabolomics Workbench to query over 4,200 studies, metabolite structures, and standardized biochemical nomenclature.

About

This skill provides Claude with programmatic access to the NIH Common Fund-sponsored Metabolomics Workbench, the primary repository for metabolomics research data. It enables users to perform complex queries across thousands of studies, standardize metabolite nomenclature using RefMet, and execute mass spectrometry searches by m/z values. Whether you are performing biomarker discovery, cross-referencing metabolite identifiers, or retrieving gene-protein-metabolite associations, this skill streamlines the integration of deep scientific data into research workflows and autonomous discovery tasks.

Key Features

Mass spectrometry m/z searches with ion adduct and tolerance settings
Access to 4,200+ processed metabolomics studies and raw experimental data
Metabolite nomenclature standardization using the RefMet database
Retrieval of molecular structures and cross-database compound identifiers
Filtering of studies by analytical method, species, sample source, and disease
324 GitHub stars

Use Cases

Identifying unknown compounds from mass spectrometry experimental data
Standardizing metabolite names across diverse datasets for meta-analysis
Retrieving experimental results and metadata for disease-specific biomarker discovery

About

Key Features

Mass spectrometry m/z searches with ion adduct and tolerance settings
Access to 4,200+ processed metabolomics studies and raw experimental data
Metabolite nomenclature standardization using the RefMet database
Retrieval of molecular structures and cross-database compound identifiers
Filtering of studies by analytical method, species, sample source, and disease
324 GitHub stars

Use Cases

Identifying unknown compounds from mass spectrometry experimental data
Standardizing metabolite names across diverse datasets for meta-analysis
Retrieving experimental results and metadata for disease-specific biomarker discovery