Maerkl: Difference between revisions
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My lab is interested in applying state of the art microfluidic technology to relevant problems in systems biology. We have developed highly-integrated microfluidic devices containing thousands of functional elements. With these devices it is possible to drastically improve throughput in biology, allowing us to interrogate and characterize complex biological networks in unprecedented scale, while maintaining a high degree of fidelity. Our microfluidic platform has been successfully applied to characterizing protein-DNA, protein-RNA, and protein-protein interactions as well as to drug discovery. | |||
The labs biological interests lie in the analysis of yeast interaction networks, including transcriptional regulatory networks as well as protein-protein interaction networks to understand the principal parameters governing these systems. A second focus of our lab is in vivo single cell analysis of protein expression, localization, and noise patterns to understand the dynamic properties of biological networks. | |||
Revision as of 03:07, 16 August 2008
Maerkl Lab, EPFL
My lab is interested in applying state of the art microfluidic technology to relevant problems in systems biology. We have developed highly-integrated microfluidic devices containing thousands of functional elements. With these devices it is possible to drastically improve throughput in biology, allowing us to interrogate and characterize complex biological networks in unprecedented scale, while maintaining a high degree of fidelity. Our microfluidic platform has been successfully applied to characterizing protein-DNA, protein-RNA, and protein-protein interactions as well as to drug discovery.
The labs biological interests lie in the analysis of yeast interaction networks, including transcriptional regulatory networks as well as protein-protein interaction networks to understand the principal parameters governing these systems. A second focus of our lab is in vivo single cell analysis of protein expression, localization, and noise patterns to understand the dynamic properties of biological networks.
