Target Prioritization

Takes a gene list from differential expression and builds multi-source dossiers by hitting UniProt, OpenTargets, PubMed, Human Protein Atlas, and ChEMBL in parallel, then re-ranks by a composite score weighing druggability, disease genetics, tissue specificity, CRISPR essentiality, gnomAD constraint, and expression context. Ships tuned for autoimmune/T-cell work but you can retarget by editing a few disease-term arrays. Outputs a markdown report with per-gene rationales (Claude fills those), a sortable CSV, and raw JSON audit trails. Honest take: this is opinionated scaffold code, not a black box. The weights are exposed in YAML and the fetchers are standalone scripts you'll probably want to tweak once you see what signal matters for your program.

skills.sh installs: 2.9K
GitHub stars: 100
last updated: Aug 21, 2026

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Install

$ npx -y skills add agents365-ai/365-skills --skill target-prioritization --agent claude-code

Installs into .claude/skills of the current project.

Files

Target Prioritization

A multi-source drug-target due-diligence pipeline for ranked gene lists.

When this skill triggers

The user has a list of candidate genes (typically from a DE / DEG / scRNA-seq analysis) and wants a per-gene dossier across multiple evidence dimensions plus a composite re-ranking. The DE statistical rank is just the entry point; the final priority is informed by protein biology, genetics, druggability, and research maturity.

Common input shapes:

A CSV with a gene column (DE output like expression_table_pass_either_1s.csv)
A plain-text gene list (one symbol per line)
A list of symbols inline in the user's message