tooluniverse-systems-biology

Analyze pathway enrichment and protein-pathway relationships across Reactome, KEGG, WikiPathways, and BioModels.

1.7k|254|Updated Mar 3, 2025
One-click install
npx skills add https://github.com/mims-harvard/ToolUniverse --skill tooluniverse-systems-biology
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tooluniverse-systems-biology
Source: https://github.com/mims-harvard/ToolUniverse/tree/main/plugins/tooluniverse/skills/tooluniverse-systems-biology
Command: npx skills add https://github.com/mims-harvard/ToolUniverse --skill tooluniverse-systems-biology

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires tooluniverse.

What problem does it solve?

Interpreting gene lists or proteins at the systems level requires querying multiple pathway databases that disagree on membership and use different identifiers, making cross-database pathway analysis slow and error-prone.

Core Features & Use Cases

  • Pathway Enrichment Analysis: Run FDR-corrected over-representation analysis on gene lists using Reactome, Enrichr, and STRING with adjusted p-value reporting.
  • Protein-Pathway Mapping: Map a UniProt accession to all Reactome pathways it participates in and retrieve detailed reactions and subpathways.
  • Multi-Database Keyword Search: Search KEGG, WikiPathways, Pathway Commons, and BioModels in parallel for pathways and SBML computational models matching a biological process.
  • Use Case: Given differentially expressed genes from an RNA-seq experiment, identify statistically enriched pathways, cross-validate findings across at least two databases, and generate a markdown report with pathway IDs, p-values, and overlapping genes.

Quick Start

Analyze pathways for the gene list TP53, BRCA1, EGFR, MYC, and KRAS and report enriched pathways with cross-database validation.

Frequently Asked Questions about tooluniverse-systems-biology

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

FAQPage Schema
How do I perform pathway enrichment analysis on a gene list?

Submit gene symbols to Enrichr or Reactome pathway enrichment tools, then sort results by adjusted p-value below 0.05. Report the top 10-20 pathways with IDs, p-values, and overlapping genes, and note explicitly if no enrichment is found.

How do I find which pathways a protein participates in?

Map the protein's UniProt accession to Reactome pathways using the Reactome mapping tool, then retrieve detailed reactions and subpathways for the most relevant hits. If Reactome returns empty results, verify the UniProt ID or fall back to keyword search with the protein name.

Reactome vs KEGG vs WikiPathways for pathway analysis?

Reactome offers detailed human-curated mechanistic pathways with reactions, KEGG covers metabolic maps and disease pathways, and WikiPathways contains community-curated emerging pathways. Cross-validate key findings across at least two sources since databases disagree on pathway membership.

Why does pathway enrichment return no significant results?

Enrichment can fail when gene lists are too small, use IDs instead of gene symbols, or when the gene set genuinely lacks pathway overlap. Try alternative Enrichr libraries like Reactome or GO Biological Process, and check that symbols are correctly cased.

What are the limitations of multi-database pathway search?

Reactome has limited coverage for non-model organisms, KEGG keyword search may miss synonyms, WikiPathways has variable curation quality, and BioModels often returns no results. Broaden keywords and check pathway version dates when results are sparse.