Build mechanistic networks
with AI agents
Flash-P agents mine literature, construct causal networks, and validate them with existing perturbations in the literature using three propagation algorithms. All from a single query.
Networks built by Flash-P
From phenotype query to validated causal network — each constructed and refined by AI agents.
Shoot Branching
Arabidopsis thaliana
Lignin Biosynthesis
Populus trichocarpa
Drought Response
Oryza sativa
Flowering Time
Arabidopsis thaliana
Root Architecture
Zea mays
Seed Dormancy
Triticum aestivum
Shoot Branching
Arabidopsis thaliana
Lignin Biosynthesis
Populus trichocarpa
Drought Response
Oryza sativa
Flowering Time
Arabidopsis thaliana
Root Architecture
Zea mays
Seed Dormancy
Triticum aestivum
The Fastest Network Constructor
How Flash-P Works
Watch the full pipeline in action — from your biological question to a validated, publication-ready causal network.
Your Query
- Choose a species (e.g., Oryza sativa)
- Choose a phenotype (e.g., Tiller Number)
- The agents take it from here
WHY FLASH-P
AI agents that build, validate, and refine causal networks — all from a single query.
5 Specialized AI Agents
Flash-P uses 5 specialized agents — Curator, Perturbation, Builder, Validator, Refinement — each expert in a stage of the pipeline. They mine literature, construct networks, and iteratively improve them.
From a single query to a validated causal network.
- Literature mining with DOI-linked evidence
- Automated perturbation dataset creation
- Network construction with causal equations
- Iterative refinement with biological reasoning
3 Independent Validation Methods
Every network is validated using three independent propagation algorithms — algebraic rules, ODE with Hill functions, and Random Walk with Restart. If all three agree, the prediction is robust.
- Flash-P algebraic propagation rules
- ODE with Hill function dynamics
- Random Walk with Restart (RWR)
- Concordance scoring across all three
Full Transparency
Every edge has a DOI. Every prediction has an equation. Every validation is reproducible. No black boxes — inspect every node, every edge, every equation in the desktop app.
Every claim is traceable to published literature.
- DOI-linked evidence for every edge
- Step-through propagation simulation
- Interactive network visualization
- Exportable results and equations
Runs on a Laptop
No GPU. No cluster. No cloud account. Flash-P runs entirely on your machine with just Python and an internet connection. The heavy GWAS computation is already done — Flash-P interprets the results.
- Desktop app with full pipeline access
- Offline mode with cached data
- Auto-updates via Tauri
- Claude Code integration for AI features
Plugin Ecosystem
Connect Flash-P to external databases and tools through lightweight API plugins. Map GWAS hits through causal networks, query Ensembl, UniProt, Phytozome — or build your own with MCP.
- SNP-to-Gene Mapper via Ensembl
- GWAS hit tracing through causal networks
- Phytozome comparative genomics
- Custom MCP plugins
The Vision
Flash-P is more than a desktop app. We're building a platform where AI agents and domain experts co-create validated biological knowledge.
Community Hub
Share validated networks, contribute perturbation data, and review edges with scientists worldwide. Every contribution makes every network better.
- Network sharing & discovery
- Perturbation data pooling
- ORCID-linked citations
- Leaderboard & recognition
Tools & Plugins
Connect Flash-P to Ensembl, UniProt, Phytozome, and more through lightweight MCP plugins. Map GWAS hits to causal mechanisms in seconds.
- SNP-to-Gene Mapper
- GWAS Catalog integration
- Breeder toolkit
- Custom MCP plugins
Run Flash-P on your desktop
Build networks locally with the Flash-P desktop app. Full pipeline access, offline mode, and direct Claude Code integration.
Download Flash-PFree and open source. Requires Claude Code for AI features.