metabolomics-workbench-database

What problem does it solve?

Manually querying vast metabolomics data is slow and complex. This Skill automates access to the NIH Metabolomics Workbench, simplifying data retrieval for research and biomarker discovery. It eliminates the need for manual navigation through web interfaces, allowing researchers to focus on analysis rather than data acquisition.

Core Features & Use Cases

• Metabolite & Study Querying: Access 4,200+ studies, retrieve metabolite structures, identifiers, and comprehensive experimental data.
• Nomenclature Standardization: Utilize RefMet to standardize metabolite names and access hierarchical classifications, ensuring consistent data interpretation.
• MS/NMR Data Search: Perform mass-to-charge ratio (m/z) searches with specified ion adducts and tolerance levels for efficient compound identification.
• Use Case: Quickly find all human blood studies related to "Tyrosine" and download their experimental data for further analysis, saving hours of manual database navigation and data compilation.

Quick Start

List all available public studies

import requests response = requests.get('https://www.metabolomicsworkbench.org/rest/study/study_id/ST/available/json') print(response.json())

Find studies containing a specific metabolite (e.g., Tyrosine)

response = requests.get('https://www.metabolomicsworkbench.org/rest/study/refmet_name/Tyrosine/summary/json') print(response.json())