AI/ML
AI Models for Gene Expression
Graph, sequence, hybrid, and foundation models for predicting gene expression and regulation from standardized biological designs.
Project directions are public starting points for students, collaborators, contributors, and partners.
AI/ML
Graph, sequence, hybrid, and foundation models for predicting gene expression and regulation from standardized biological designs.
autonomous laboratories
Facility orchestration, humanoid robotics, equipment integration, and safe recovery for sustained autonomous DBTL campaigns.
digital twins
Agent-based simulations for engineered microbial communities, host-microbiome systems, and plant-associated ecosystems.
genetic networks
Genetic network architectures for biological sensing, computing, reporting, adaptation, and decision-making.
DBTL
Modular workflows that connect LOICA, PUDU, BuildCompiler, Flapjack, SynBioHub, and SeqTrainer across the engineering cycle.
standards
Standards-enabled data infrastructure that makes genetic design, build metadata, and experimental measurements reusable.