Source: https://github.com/aipoch/medical-research-skills

When to Use

• You need to look up a metabolite by common name (e.g., “Caffeine”) and retrieve its HMDB entry data.
• You have an HMDB ID (e.g., HMDB0000001) and want to extract standardized chemical/biological/clinical fields for downstream analysis.
• You want to build a local, scriptable pipeline to mine the HMDB XML dump instead of manually browsing the website.
• You need to map HMDB identifiers to external resources (e.g., KEGG, PubChem, ChEBI) for integration tasks.
• You are preparing metabolomics datasets and need pathway/enzyme/transporter annotations from HMDB entries.

Key Features

• Search metabolites by:
  • Text name
  • HMDB identifier (e.g., HMDB0000001)
  • Structure-related query (as supported by the parser/search implementation)
• Parse the HMDB XML dataset and extract:
  • Chemical data (formula, molecular weight, InChI/SMILES where available)
  • Biological data (pathways, enzymes, transporters)
  • Clinical data (disease associations, biofluid concentrations)
• Optional structuring of extracted results for analysis workflows (e.g., tabular outputs).
• Supports integration workflows by exposing identifiers suitable for cross-database mapping.

Dependencies

• Python >=3.9
• Standard library:
  • xml.etree.ElementTree (built-in)
• Optional:
  • pandas >= 1.5

Example Usage

1) Download HMDB XML

Download the HMDB metabolite XML dataset from:

• https://hmdb.ca/downloads

Assume you saved it as:

data/hmdb_metabolites.xml

2) Search and Extract Fields (Runnable Example)

from scripts.hmdb_parser import HMDBParser

def main():
    # Path to the HMDB XML dump downloaded from hmdb.ca/downloads
    xml_path = "data/hmdb_metabolites.xml"

    parser = HMDBParser(xml_path)

    # Search by metabolite name (text query)
    results = parser.search("Caffeine")

    # Print basic information from the first match (structure depends on implementation)
    if not results:
        print("No results found.")
        return

    first = results[0]
    print("Top match:")
    print(first)

if __name__ == "__main__":
    main()

3) Field Reference

For a curated list of extractable fields and how they map to HMDB XML elements, see:

• references/hmdb_data_fields.md

Implementation Details

• Data acquisition

  • Primary workflow uses the official HMDB downloadable XML dataset (recommended for bulk parsing).
  • Single-entry lookups can be done via the HMDB website, but this skill is designed around XML parsing.

• Parsing approach

  • The parser reads the HMDB XML and traverses metabolite entries using xml.etree.ElementTree.
  • Extracted fields should follow the definitions documented in references/hmdb_data_fields.md.

• Search behavior

  • Name/ID search typically matches against key textual identifiers (e.g., common name, synonyms, HMDB accession).
  • Structure-based search is dependent on what structural fields are indexed/exposed by HMDBParser (e.g., SMILES/InChI).

• Integration / cross-references

  • HMDB entries often include cross-references to external databases (e.g., KEGG, PubChem, ChEBI).
  • A common workflow is to extract these identifiers and build mapping tables for downstream joins.

• Spectral analysis (conceptual)

  • HMDB contains NMR/MS references for some metabolites; this skill can be extended to link parsed entries to spectral metadata.
  • Actual spectral matching/identification is not guaranteed unless implemented in the codebase.