metabolomics-workbench-database

You query the NIH Metabolomics Workbench API by using this Skill to programmatically retrieve metabolite structures, study metadata, experimental results, and mass spectrometry data. It provides direct REST API access to over 4,200 metabolomics studies.

Yes, you can standardize metabolite names using RefMet nomenclature. The Skill facilitates nomenclature standardization by accessing the RefMet system within the NIH Metabolomics Workbench to ensure consistent metabolite identification across studies.

You search for mass spectrometry compounds by providing m/z values to the Skill, which queries the NIH Metabolomics Workbench REST API to identify matching compounds and retrieve associated experimental results from metabolomics studies.

Yes, the NIH Metabolomics Workbench API supports gene and protein information integration. The Skill enables access to associated biological database information, allowing you to retrieve gene and protein data alongside metabolomics experimental results.

The best way to retrieve experimental results is by using the Skill to query the NIH Metabolomics Workbench for specific studies and metabolites. You can filter studies by disease like diabetes and metabolites like glucose, then extract the experimental data.

Yes, you need the requests library installed in your Python environment to use this Skill. The Skill depends on the requests library to handle the HTTP calls required for programmatic access to the NIH Metabolomics Workbench REST API.