FET: SMALL: New Abstraction and Design Automation for Complex Computations with DNA Using Fractional Coding

Grants and Contracts Details


This project will enable systematic design of efficient molecular circuits for fast computation of complex mathematical functions. The design of molecular computing circuits will be systematic because the project will develop a new level of design abstraction that accepts mathematical representation of desired computations. It will create an end-to-end compiler that transfers the mathematical representation to CRNs, and then generates candidate DNA reactions and sequences. The developed circuits will be fast because they work based on fractional coding. Unlike traditional encodings that need to wait for the equilibrium concentrations of molecules, for fractional coding, inputs/outputs are ratios of pairs of molecular concentrations. The ratios reach their final values much faster than molecular concentrations. This project will expand the computational power of molecular computing circuits to complex computations through two approaches: 1) it will map all stochastic computing logic circuits to molecular circuits, 2) it will implement finite state Markov chains by molecular reactions. Finally, the project will develop new approaches for performing ANNs and signal processing algorithms with molecular reactions. This project will have a significant impact on the field of bio-design automation because it will introduce and attempt to realize the idea of automated design of molecular circuits, starting from high level mathematical or algorithmic representation. If successful, the project will deliver a complete framework and associated software tool that enables a person who is not a skilled biologist to design and study complex biological systems. In the realm of biomolecular computation, there is established prior work in molecular circuits for computing different sorts of mathematical functions such as polynomials [41],[42], and logarithms [43],[44]. As of now, however, no systematic method has been proposed for computing complex general mathematical functions within a molecular circuit.
Effective start/end date10/1/219/30/24


  • National Science Foundation: $399,396.00


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