Individual skill
tooluniverse-network-pharmacology
Compound-target-disease network construction and analysis for drug repurposing, polypharmacology discovery, and multi-target drug design. Uses STRING, BioGRID, ChEMBL, DGIdb, OMIM, OpenTargets. Use for off-target effect prediction, network-based drug repurposing, and identifying molecules with desired multi-target profile.
skills/tooluniverse-network-pharmacology/SKILL.md
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- Last checked
- Nov 5, 2026
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- Repository last updated
- Nov 7, 2026
- License
- Apache-2.0
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- agents Repository topic
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ANALYSIS_PROCEDURES.mddoc · 16,052 bytesQUICK_START.mddoc · 12,425 bytesREPORT_TEMPLATE.mddoc · 5,115 bytesSCORING_REFERENCE.mddoc · 3,037 bytesSKILL.mdcore · 14,199 bytesSKILL.mdcore · 14,199 bytesSKILL.mdcore · 14,199 bytesTOOL_REFERENCE.mddoc · 10,629 bytesUSE_PATTERNS.mddoc · 3,469 bytesscripts/network_proximity.pyruns · 6,310 bytestest_network_pharmacology.pyruns · 48,021 bytes
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## COMPUTE, DON'T DESCRIBE
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
# Network Pharmacology Pipeline
Construct and analyze compound-target-disease (C-T-D) networks to identify drug repurposing opportunities, understand polypharmacology, and predict drug mechanisms using systems pharmacology approaches.
**LOOK UP DON'T GUESS** - Retrieve actual target lists, network data, and clinical evidence from tools. Do not infer network relationships from drug class alone.
**IMPORTANT**: Always use English terms in tool calls, even if the user writes in another language. Respond in the user's language.
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## Polypharmacology Reasoning (Start Here)