Georg Seelig is an associate professor of Electrical & Computer Engineering and of computer science and engineering. He is also an adjunct associate professor of bioengineering. Seelig holds a Ph.D. 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 in 2008, an NSF Career Award in 2010, a Sloan Research Fellowship in 2011, a DARPA Young Faculty Award in 2012 and an ONR Young Investigator Award in 2014.
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. The focus of our research is the identification of systematic design rules for the de novo construction of biological control circuits with DNA and RNA components. Our approach integrates the design of molecular circuitry in the test tube and in the cell with the investigation of existing biological pathways. Engineered circuits are being applied to problems in disease diagnostics and therapy.
Awards and Honors
- MSR Outstanding Collaborator Award, 2016, Microsoft Research (Microsoft's Prestigious Collaborator Award)
- Outstanding Faculty Award, 2015, Department of Electrical Engineering
- Young Investigator Award, 2014, ONR
- Young Faculty Award, 2012, DARPA (Seelig Receives DARPA Young Faculty Award)
- Sloan Research Fellowship, 2011, Alfred P. Sloan Foundation
- CAREER Award, 2010, National Science Foundation (Georg Seelig Receives 2010 CAREER Award)
- Career Award at the Scientific Interface, 2008, Burroughs Wellcome Fund
- Paul J. Sample, Ban Wang, David W. Reid, Vladimir Presnyak, Iain McFadyen, David R. Morris and Georg Seelig, Human 5'UTR design and variant effect prediction from a massively parallel translation assay, Nature Biotechnology 37, 803, (2019). Earlier version on bioRxiv.
- Nicholas Bogard*, Johannes Linder*, Alexander B. Rosenberg and Georg Seelig, A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation, Cell 178, 91 (2019).
- Randolph Lopez, Ruofan Wang, and Georg Seelig, A molecular multi-gene classifier for disease diagnostics, Nature Chemistry 10, 746 (2018).
- Alexander B Rosenberg*, Charles Roco*, Richard A Muscat, Anna Kuchina, Paul Sample, Sumit Mukherjee, Wei Chen, David J Peeler, Zizhen Yao, Suzie H Pun, Drew L Sellers, Bosiljka Tasic, and Georg Seelig, Single cell profiling of the developing mouse brain and spinal cord with split-pool barcoding, Science 360, 176 (2018).
- Gourab Chatterjee, Neil Dalchau, Richard A Muscat, Andrew Phillips and Georg Seelig, A spatially localized architecture for fast and modular DNA computing, Nature Nanotechnology 12, 920 (2017). An earlier version is on bioRxiv. See also News & Views by Esteves-Torres and Rondelez.