Invention Reference Number
This invention introduces a computational platform that integrates artificial intelligence (AI), systems biology, and network-based reasoning to model and interpret complex traits in plants. By focusing on biological mechanisms rather than individual genes, this approach enables more targeted and interpretable insights into plant performance, with potential applications in crop yield, stress resilience, and nutrient efficiency.
Description
The platform uses a multi-layered network architecture to represent high-resolution biological data, organizing it into functionally relevant modules aligned with specific plant traits. These modules, referred to as mechanistic clades, correspond to dynamic biological processes such as regulatory pathways or metabolic interactions. Advanced AI methods, including large language models and reinforcement learning, operate within this structure to reveal how traits are influenced by genetics, environment, and potential interventions. The framework supports predictive modeling across diverse species and conditions, enabling trait simulation and optimization through explainable models. This approach facilitates scalable and biologically grounded strategies for plant biotechnology and breeding applications.
Benefits
- Enables predictive modeling of plant traits using systems biology and AI
- Improves interpretability and scalability in trait discovery and optimization
- Supports design of new trait combinations and interventions
Applications and Industries
- Crop improvement and agricultural biotechnology
- Precision breeding and trait deployment strategies
- Translational research in plant systems biology
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
