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scientific-metabolomics-databases

Integrates HMDB, MetaCyc, Metabolomics Workbench for cross-database metabolite identification and pathway mapping via RefMet and ToolUniverse SMCP.

3|1|Updated Feb 11, 2026

Search Tags:#metabolomics #hmdb #biomarker #pathway #refmet #metacyc #mwb

Ready to run

npx skills add https://github.com/nahisaho/satori --skill scientific-metabolomics-databases

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scientific-metabolomics-databases
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-metabolomics-databases
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-metabolomics-databases

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Integrate HMDB, MetaCyc, and Metabolomics Workbench to enable cross-database metabolite identification, pathway mapping, and biomarker discovery, while leveraging RefMet naming and ToolUniverse SMCP tools for standardized analysis.

Core Features & Use Cases

Unified access to HMDB, MetaCyc, and Metabolomics Workbench for cross-database metabolite annotation and pathway exploration.
Metabolite identification and annotation from MS data across multiple databases with standardized naming.
Pathway mapping, biomarker discovery, and context-aware interpretation using RefMet normalization and ToolUniverse SMCP integration.
Use Case: When analyzing untargeted metabolomics data, identify metabolites by mass or name across databases and map them to pathways for biological interpretation.

Quick Start

Run the metabolomics workflow to identify metabolites by mass or name across HMDB, MetaCyc, and Metabolomics Workbench and map them to pathways with RefMet standardization.

Frequently Asked Questions about scientific-metabolomics-databases

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify metabolites across HMDB, MetaCyc, and Metabolomics Workbench in one query?▼

Cross-database metabolite identification matches metabolites by mass or name across HMDB, MetaCyc, and Metabolomics Workbench simultaneously. It applies standardized RefMet naming to unify annotations for untargeted and targeted metabolomics analyses.

What is RefMet naming and how does it standardize metabolomics database annotations?▼

RefMet naming standardizes metabolite annotations by providing a normalized reference framework across HMDB, MetaCyc, and Metabolomics Workbench. It ensures consistent metabolite identification and cross-reference annotations during biomarker discovery pipelines.

Can I map identified metabolites to biological pathways for biomarker discovery?▼

Pathway mapping links identified metabolites to biological pathways using cross-database annotations from MetaCyc and HMDB. This enables context-aware interpretation and biomarker discovery for pharmacometabolomics studies and untargeted metabolomics data.

Does this metabolomics workflow integrate with ToolUniverse SMCP tools?▼

ToolUniverse SMCP integration connects the cross-database querying and RefMet naming processes to standardized analysis tools. It ensures deterministic workflows and reproducible results for metabolite identification and pathway mapping.

What's the best way to handle cross-database metabolite annotation for untargeted metabolomics data?▼

Cross-database metabolite annotation identifies metabolites by mass or name across HMDB, MetaCyc, and Metabolomics Workbench. It leverages RefMet normalization to standardize naming and map results to pathways for biological interpretation.

When do I need cross-database querying for metabolomics biomarker discovery pipelines?▼

Cross-database querying is needed when biomarker discovery pipelines require cross-reference annotations and standardized naming across HMDB, MetaCyc, and Metabolomics Workbench. It ensures comprehensive metabolite identification and context-aware pathway interpretation.