genetic networks
Intelligent Genetic & Genomic Networks
Genetic and genomic network architectures for sensing, computing, decision-making, reporting, and adaptive biological behavior.
- genetic networks
- intelligence
- biocomputation
Intelligent genetic and genomic networks are biological systems designed to sense information, process it, make decisions, and generate useful outputs. DRAGGON Lab explores how computational specifications can be translated into genetic constructs and, eventually, genomic-scale programs.
Design levels
At the part level, the lab will mine genomes, design new genetic parts, compose synthetic genes, and characterize expression in context. At the genetic-network level, characterized parts become engineering kits for circuits and dynamical programs. At the genomic-network level, designs can scale toward consortia, multicellular systems, and ecosystems with emergent behavior.
Computational goals
Near-term targets include dynamic biological signals, noise-robust phase-based genetic networks, reservoir computing, and in vivo biological intelligence. These systems may combine DNA, RNA, proteins, chemicals, and environmental signals as computationally meaningful nodes and edges.
Impact direction
The long-term vision is to program organisms and communities with sensing, computing, production, and reporting capabilities that support medicine, agriculture, environmental resilience, and closed-loop interactions with machines.