in-silico-perturbation-oracle
Virtual gene knockout simulation using foundation models to predict transcriptional changes
npx skills add majiayu000/claude-skill-registry --skill in-silico-perturbation-oracle --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# In Silico Perturbation Oracle **ID**: 207 **Category**: Bioinformatics / Genomics / AI-Driven Drug Discovery **Status**: ✅ Production Ready **Version**: 1.0.0 **⚠️ Note: This tool provides a framework for in silico perturbation analysis. Actual predictions require integration with biological foundation models (Geneformer, scGPT, etc.) and wet lab validation data.** --- ## Overview In Silico Perturbation Oracle is a computational biology tool based on biological foundation models (Geneformer, scGPT, etc.) for performing "virtual gene knockout (Virtual KO)" in silico to predict changes in cellular transcriptome states after specific gene deletions. This tool provides AI-driven decision support for target screening before wet lab experiments, significantly reducing drug development time and costs. --- ## Features | Function Module | Description | Status | |---------|------|------| | 🧬 Gene Knockout Simulation | In silico KO prediction based on pre-trained models | ✅ | | 📊 Differential Expression Analysis | Predict DEGs (Differentially Expressed Genes) after knockout | ✅ | | 🔄 Pathway Enrichment Analysis | GO/KEGG pathway change prediction | ✅ | | 🎯 Target Scoring | Multi-dimensi
- Overview
- Features
- Supported Models
- Installation
- Usage
- Quick Start
- Python API
- Input Specification
- Required Parameters
- Optional Parameters
- Cell Type Standard Naming
- Output Specification
- 1. Differential Expression Results (degresults.csv)
- 2. Pathway Enrichment Results (pathwayenrichment.json)
Basic dependencies pip install torch transformers scanpy scvi-tools Bioinformatics tools pip install gseapy enrichrpy Model-specific dependencies pip install geneformer scgpt Single gene knockout prediction python scripts/main.py \ Batch target screening Python dependencies
What does the in-silico-perturbation-oracle skill do?
Virtual gene knockout simulation using foundation models to predict transcriptional changes
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill in-silico-perturbation-oracle --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.