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DNA Computing for DNA Data Storage and Disease Diagnosis

ECE Colloquia Seminar

Location: ECJ 1.312
Georg Seelig
University of Washington

In this talk, I will briefly introduce the field of DNA computing starting with work by Adleman. I will then highlight two different applications for DNA computing. First, I will introduce an approach for performing computation in the context of DNA data storage. Synthetic DNA has the potential to store the world’s continuously growing amount of data in an extremely dense and durable medium. Current proposals for DNA-based digital storage systems include the ability to retrieve individual files by their unique identifier, but not by their content. Here, we demonstrate content-based retrieval from a DNA database by learning a mapping from images to DNA sequences such that an encoded query image will retrieve visually similar images from the database via DNA hybridization. We encoded and synthesized a database of 1.6 million images and queried it with a variety of images, showing that each query retrieves a sample of the database containing visually similar images are retrieved at a rate much greater than chance.  Second, I will give an example of using DNA computation for disease diagnosis. Our workflow begins by training a computational classifier on labelled gene expression data. This in silico classifier is then realized at the molecular level to enable expression analysis and classification of previously uncharacterized RNA samples. Classification occurs through a series of molecular interactions between RNA inputs and engineered DNA probes designed to differentially weigh each input according to its importance. 


Georg Seelig is a professor in the Department of Electrical & Computer Engineering and the Paul G. Allen School of Computer Science & Engineering at the University of Washington. He is an adjunct professor in Bioengineering. The Seelig group is interested in understanding how biological organisms process information using complex biochemical networks and how such networks can be engineered to program cellular behavior.  Seelig holds a PhD in physics from the University of Geneva in Switzerland and did postdoctoral work in synthetic biology and DNA nanotechnology at Caltech. He received a Burroughs Wellcome Foundation Career Award at the Scientific Interface, an NSF Career Award, a Sloan Research Fellowship, a DARPA Young Faculty Award and an ONR Young Investigator Award.

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