tooluniverse-target-research

Compile citation-backed biological target profiles with evidence grading and Open Targets data.

1.6k|244|Updated Mar 3, 2025

Search Tags:#literature #PPI #pathway-analysis #GO #OpenTargets #target-research #druggability

Ready to run

npx skills add https://github.com/mims-harvard/ToolUniverse --skill tooluniverse-target-research

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tooluniverse-target-research
Source: https://github.com/mims-harvard/ToolUniverse/tree/main/skills/tooluniverse-target-research
Command: npx skills add https://github.com/mims-harvard/ToolUniverse --skill tooluniverse-target-research

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill aggregates deep target intelligence across nine parallel research paths to enable rapid, evidence-based drug target evaluation and validation.

Core Features & Use Cases

Multi-path target profiling: Identity, structure, interactions, pathways, expression, variants, drug interactions, and literature in a unified report.
Evidence grading: Assigns T1-T4 levels to claims and sources for transparent prioritization.
Open Targets integration: Explicit coverage of target associations and safety/druggability metrics.
Report-first workflow: Creates the complete target report before data collection and audits completeness.

Quick Start

Use the tool to generate a Target Intelligence Report for EGFR.

Frequently Asked Questions about tooluniverse-target-research

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

FAQPage Schema

How do I compile a comprehensive drug target profiling report across pathways, interactions, and variants?▼

Drug target profiling aggregates identity, structure, function, pathways, interactions, expression, variants, drug interactions, and literature into a unified, citation-backed report. It applies to targets specified by gene symbol, UniProt accession, Ensembl ID, or gene name to produce a complete Open Targets-informed assessment.

What is evidence grading in biological target research and how does it prioritize data?▼

Evidence grading in target research assigns T1-T4 levels to claims and sources for transparent prioritization. It enforces mandatory citations and collision-aware literature search to ensure data-minimum checks are met before completing the final assessment.

Can I use a UniProt accession or Ensembl ID for Open Targets druggability assessment?▼

Yes, Open Targets druggability assessment accepts UniProt accessions and Ensembl IDs alongside gene symbols or names. It explicitly covers target associations and safety or druggability metrics to generate a complete target intelligence report.

How do I perform collision-aware literature search for pathway analysis and GO annotations?▼

Collision-aware literature search for pathway analysis and GO annotations enforces data-minimum checks within a report-first workflow. It compiles citation-backed profiles across multiple parallel research paths to ensure accurate target evaluation.

Best way to evaluate target druggability using multi-path target intelligence?▼

Multi-path target intelligence evaluates druggability by aggregating deep research across nine parallel paths including structure, interactions, and variants. It creates a complete target report before data collection and audits completeness to enable rapid, evidence-based drug target validation.

What are the limitations of using automated target research for pathway analysis and variant assessment?▼

Automated target research for pathway analysis and variant assessment requires strict data-minimum checks and mandatory citations to mitigate limitations. It enforces a report-first workflow and evidence grading to prevent incomplete or unverified biological target profiles.