Automated Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks
Author Information
Author(s): Jacob Beal, Ting Lu, Ron Weiss
Primary Institution: BBN Technologies, Cambridge, Massachusetts, United States of America; Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
Hypothesis
Can a high-level programming language facilitate the design and optimization of synthetic biological systems?
Conclusion
The platform provides a user-friendly tool for the automated design of complex synthetic biological systems, significantly improving the efficiency of gene network design.
Supporting Evidence
- The platform allows for the automated design of complex biological systems.
- Compiler optimizations can significantly reduce the number of genes and latency in engineered gene networks.
- Simulations validate the behavior of the generated genetic regulatory networks.
Takeaway
This study shows how scientists can use a special programming language to create and improve biological systems more easily, like building with LEGO blocks.
Methodology
The study developed a platform that compiles high-level programming language specifications into optimized genetic regulatory networks.
Limitations
The current version of the platform may not ensure biological feasibility of the engineered systems.
Digital Object Identifier (DOI)
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