in-silico-perturbation-oracle

name	in-silico-perturbation-oracle
description	Virtual gene knockout simulation using foundation models to predict transcriptional changes
version	1.0.0
category	AI/Tech
tags	[]
author	AIPOCH
license	MIT
status	Draft
risk_level	High
skill_type	Hybrid (Tool/Script + Network/API)
owner	AIPOCH
reviewer
last_updated	2026-02-06

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.

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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.

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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-dimensional target scoring and ranking	✅
📈 Visualization Report	Generate interpretable charts and reports	✅
🔗 Wet Lab Interface	Export wet lab validation recommendations	✅

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Supported Models

Model	Description	Applicable Scenarios
Geneformer	Transformer-based gene expression foundation model	General gene regulatory network inference
scGPT	Single-cell multi-omics foundation model	Single-cell level perturbation prediction
scFoundation	Large-scale single-cell foundation model	Cross-cell type generalization prediction
Custom	User-defined models