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OriGene

calendar_todayAdded Feb 25, 2026
categoryAgent & Tooling
codeOpen Source
PythonWorkflow AutomationMulti-Agent SystemModel Context ProtocolAI AgentsAgent FrameworkAgent & ToolingProtocol, API & IntegrationMedical & Biomedicine

A self-evolving virtual disease biologist developed by GENTEL-lab at Shanghai Jiao Tong University, powered by multi-agent systems and MCP protocol, integrating 600+ bioinformatics tools for automated therapeutic target discovery and molecular mechanism analysis.

Overview#

OriGene is a self-evolving virtual disease biologist developed by GENTEL-lab at Shanghai Jiao Tong University, officially released at the 2025 World Artificial Intelligence Conference (WAIC). The system addresses key challenges in drug discovery: heavy reliance on manual intuition, fragmented data sources, and lengthy analysis cycles.

Core Capabilities#

Intelligent Target Discovery: Automatically integrates 10+ authoritative databases (ChEMBL, PubChem, OpenTargets, NCBI, TCGA, DepMap, etc.) for target screening, ranking, and validation.

Self-Evolving Multi-Agent Architecture: Features self-learning and iterative optimization capabilities, supporting multi-step reasoning for complex biological problems while simulating human biologist research workflows.

Mechanism-Guided Analysis: Performs deep reasoning based on biological mechanism pathways rather than simple keyword matching, generating analysis reports with evidence chains.

Native MCP Protocol Support: Enables standardized invocation of 600+ bioinformatics tools (BLAST, ClustalW, etc.) through the OrigeneMCP server.

System Architecture#

Adopts master-slave MCP architecture:

  • Main Application: Handles user interaction, task planning, agent scheduling, and report generation
  • OrigeneMCP Server: Independent microservice encapsulating bioinformatics tools and database access logic

Supports multiple LLM backends (OpenAI, DeepSeek, CloseAI, etc.) for model-agnostic deployment.

Use Cases#

  • Target screening and validation in early-stage drug discovery
  • Molecular mechanism analysis for complex diseases
  • Comprehensive biomedical literature Q&A and knowledge graph construction
  • Clinical trial support and target-related trial information queries

Deployment#

Requirements: Docker Engine 20.10+ or Python 3.13+

Quick Start:

git clone https://github.com/GENTEL-lab/OriGene.git
cd OriGene
./setup.sh

Running Modes:

  • Interactive: make start
  • Quick Research: make quick QUERY="your question"
  • Detailed Report: make detailed QUERY="your query"

TRQA Benchmark#

Includes TRQA (Therapeutic Research Question Answering) benchmark with 1,921 expert-level questions for evaluating biomedical AI agent performance across literature selection, database queries, and short-answer formats.

Development Team#

GENTEL-lab (Shanghai Jiao Tong University), with fully open-source codebase and benchmarks.

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