The biological compiler

Applied Evolution is developing BioC: the compiler for programming biological function into living systems.

Biology as software: executable design, compressing iteration cycles, and radically accelerating biological development.

01

Cost

Reduce the cost structure of bioengineering by moving design iteration out of the wet lab and into software. Move beyond repeated empirical failure with focused validation of the strongest candidate designs.

02

Speed

Accelerate bioengineering by turning slow experiments into rapid software-driven design cycles. Compress months of manual redesign with compile-test-select loops around the strongest candidates.

03

Scalability

Scale bioengineering with modular genetic compilation workflows. Replace one-off system engineering with repeatable pipelines that expand across organisms, functions, and applications.

BioScript captures the language specification. BioC lowers that specification into context-aware genetic material, connecting high-level biological function to concrete implementation.

01

BioScript

Encode biological intent as explicit, modular structure that can be parsed, constrained, compiled, and checked. Represent genes, molecules, proteins, and regulatory logic in a form BioC can reason over directly.

02

BioC

Compile high-level biological specifications into candidate DNA-level implementations. Enable deterministic, traceable compilation so every generated system can be inspected, constrained, and validated for biosafety.

03

DNA

Compile functional genetic systems for plasmid or chromosomal implementation. Account for biological context across host strain, regulation, and expression environment.

BioC currently spans compiler design, a working language front end, and experimental grammar induction.

01

Compiler Architecture

A stage-by-stage specification of BioC, defining each search problem and where learned grammars constrain the search.

02

Front End

A lexer and parser for prototype BioScript, translating programs into context-ignorant structural genes.

03

Grammar Induction

An evolutionary algorithm recovering exact target-language semantics in 80% of trials from positive only examples.