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Towards a Computer Engineering Discipline with DNA

Towards a Computer Engineering Discipline with DNA. Marc Riedel. Associate Professor, Electrical and Computer Engineering Graduate Faculty, Biomedical Informatics and Computational Biology University of Minnesota. University of Wisconsin – Sept. 23, 2013 . Synthetic Biology.

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Towards a Computer Engineering Discipline with DNA

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  1. Towards a Computer Engineering Discipline with DNA Marc Riedel Associate Professor, Electrical and Computer Engineering Graduate Faculty, Biomedical Informatics and Computational BiologyUniversity of Minnesota University of Wisconsin – Sept. 23, 2013

  2. Synthetic Biology Positioned as an engineering discipline. “Novel functionality through design”. Repositories of standardized parts. • Driven by experimental expertise in particular domains of biology. • Gene-regulation, signaling, metabolism, protein structures …

  3. Building [interdisciplinary] Bridges Quantitative modeling. Mathematical analysis. Incremental and iterative design changes. "Think of how engineers build bridges. They design quantitative models to help them understand what sorts of pressure and weight the bridge can withstand, and then use these equations to improve the actual physical model. [In our work on memory in yeast cells] we really did the same thing.” – Pam Silver, Harvard2007 Engineering Design

  4. Biological Computers • Genetic Logic Gates by Knight, Weiss, et al. • “Transcriptor” by Drew Endy’s group • Biological “Transducer” by Keinan et al. • Synthetic Transcriptional AND gates by Shis and Bennet • DNA/RNA logic by Shapiro, Beneson et al. “AND” gate Memory

  5. Sequential Computation(e.g., filtering) Input Output 10, 2, 12, 8, 4, 8, 10, 2, … 5, 6, 7, 10, 6, 6, 9, 6, … Chemical Reactions Time-varying changes in concentrations of an input molecular type. Time-varying changes in concentrations of output molecular type. … …

  6. Circuit Representation

  7. Constant Multiplier Adder Delay Element

  8. Clock Signal Jiang, Riedel, and Parhi, “Synchronous Sequential Computation with Chemical Reactions,” DAC 2011. Delay Element

  9. An Asynchronous Methodology • No clock: self-timed. • Rate-independent (only coarse rates, e.g., “fast” and “slow”). Delay Element

  10. Inversion Produce a quantity of a type only in the absence of another type.

  11. Duplication Produce a quantity of a type equal to the quantity of another type:

  12. 3-Phase Scheme We use a three compartment configuration for delay elements: we categorize the types into three groups: red, green and blue. Every delay element Di is assigned Ri, Gi, and Bi

  13. Moving Average Filter ChemicalReactions time time y(n) = 0.5 x(n) + 0.5 x(n-1)

  14. Moving Average Filter New cycle!

  15. Moving Average Filter Transfer reactions Redabsence indicator Greenabsence indicator Computation reactions Blueabsence indicator

  16. Moving Average Filter (improved) Signal transfer Computation Absence indicator

  17. Technology Mapping:DNA Strand Displacement X1 X2 + X3 D. Soloveichiket al: “DNA as a Universal Substrate for Chemical Kinetics.” PNAS, Mar 2010

  18. Technology Mapping:DNA Strand Displacement X3 X1 + X2 D. Soloveichiket al: “DNA as a Universal Substrate for Chemical Kinetics.” PNAS, Mar 2010

  19. DNA Reactions for Moving Average FiltersAbsence Indicator Reactions

  20. DNA Reactions for Moving Average FiltersTransfer Reactions

  21. DNA Reactions for Moving Average FiltersComputation Reactions

  22. Simulation Results: Moving Average Filter input: X output: Y Concentration (nM) Time (Hours) Output obtained by ODE simulations at the DNA level.

  23. Biquad Filter

  24. Biquad Filter Absence indicator Signal transfer Computation

  25. Simulation Results: Biquad Filter • Output obtained by ODE simulations of chemical kinetics at the DNA level.

  26. More Complex Arithmetic

  27. Multiplication pseudo-code

  28. Multiplication

  29. Multiplication

  30. Exponentiation pseudo-code

  31. Raising-to-a-Power pseudo-code

  32. Discussion • Functionality: • Sequential computation is implemented with chemical reactions. • Robustness: • Computation is rate-independent. Implementation requires only coarse rate categories (“slow” and “fast”). • Complexity • Both number of molecular types and number of reactions are linear in number of delay elements in the system.

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