Monday, January 9, 2023, 10am

Engineering synthetic gene networks with desired behavior for robust adaptation or tailor decision-making is challenging. Currently approaches rely on different negative strategies and/or logic-based operators, which suffer from suboptimal performance. To address these limitations, we introduce two design principles: (1) ultrasensitive input-output behavior with (2) tunable thresholds. Here, we engineered ultrasensitive-based networks to both achieve adaptive behavior through feedback control and building synthetic programs for molecular pattern recognition by implementing neuromorphic computing in mammalian cells.

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Christian Cuba Samaniego received the B.S. degrees in Mechatronic Engineering from the "Universidad Nacional de Ingenieria, Peru”, in 2013, and Ph.D. degrees in Mechanical Engineering from University of California Riverside, CA, USA, in 2017. He was a postdoctoral with the university of Massachusetts Institute of Technology from 2017 to 2019. Currently, he is a postdoctoral research associate with the University of California Los Angeles, CA, USA. His research interests lies at the intersection of Control Theory, Systems Biology, and Synthetic Biology. He is specially interested in the design, analysis and applications of biomolecular feedback control and biomolecular neural networks for tailor decision-making in living cells.

In Person and Zoom Participation. See announcement.

Event Type: Talks
Room Number: In Person and Remote
Building: Gates Hillman 8102 and Zoom
Speaker's Name: CHRISTIAN CUBA SAMANIEGO
Speaker Website: christiansami.wixsite.com…
Speaker's Professional Title: Postdoctoral Research Associate, University of California, Los Angeles
Talk Title: Neuromorphic computing and feedback control in living cells
For More Information: aricarte@andrew.cmu.edu
Affiliations: Computational Biology Department (CBD)
Organization(s): SCS