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Research Abstracts Online
January 2009 - March 2010

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University of Minnesota Twin Cities
Institute of Technology
Department of Electrical and Computer Engineering

PI: Marc Riedel

Design Automation for Digital Computation With Nanoscale Technologies and Biological Processes

In general discourse, disciplines of science are sometimes branded as "hard” or "soft” according to the perceived mathematical rigor of their endeavors. There is also a presumed food chain: the "pure” sciences produce new understanding; the "applied” sciences consume it. In such classification schemes, biology is labeled soft and purely descriptive; engineering, hard and purely applied. And yet such characterizations belie the nature of research in these fields. Quantitative analysis and simulation play a pervasive role in biology. Also, engineering methods for design are used in a deliberate way to validate scientific understanding.

This project aims at transformative approaches to design automation, guided by novel physical views of computation in disparate fields. A broad theme is the application of expertise from an established field (digital circuit design) to new areas (nanotechnology and synthetic biology). A specific theme that cuts across these domains is constructing and deconstructing probabilistic behavior. In the realm of synthetic biology, the project will develop techniques for designing biochemical pathways that produce different combinations of molecular types according to specified probability distributions. This will provide the ability to fine-tune the response, producing a precise distribution of different outcomes across a population of organisms or in a sequence of trials. This methodology has important applications in domains such as bio-sensing, drug delivery, and disease treatment. In the realm of nanotechnology, the project will develop techniques for designing digital circuits that process zeros and one probabilistically. This is a promising strategy for coping with the randomness that occurs due to noise and glitches as circuit components are scaled down in size to nanometers.