Untangling the Wires: an Integrated Framework for Probing Signal Encoding and Decoding in Cellular Circuits
PKA is one of the cell's busiest hubs. It is a pipeline used to transmit many environmental signals, each of which elicits an exquisitely specific response. Dr. Hana El-Samad aims to understand how the PKA system achieves this feat, and in general to uncover the spectrum of strategies that organisms use in order to send a large number of different signals over a constrained hardwired infrastructure. In this pursuit, Hana and her team have been able to develop broadly applicable technologies, both experimental and computational that push the precision and resolution of cell biological investigations.
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- Hana El-Samad | 2016 Allen Frontiers Symposium
Hana El-Samad, Ph.D.
University of California, San Francisco
Hana El-Samad is an associate professor in the department of Biochemistry and Biophysics at the University of California, San Francisco and the California Institute for Quantitative Biosciences (QB3), where she holds the Grace Boyer Junior Endowed Chair in Biophysics and is the deputy director of the UCSF Systems and Synthetic Biology Center. She is the recipient of many honors and awards, including a 2009 Packard Fellowship, a 2011 Donald P. Eckman Award and the 2012 CSB2 prize in Systems Biology. Dr. El-Samad joined UCSF after obtaining a doctorate degree in Mechanical Engineering from the University of California, Santa Barbara, preceded by a Masters Degree in Electrical Engineering from the Iowa State University. Dr. El-Samad's research group emphasizes the role of control theory and dynamical systems in the study of biological networks. Her research interests include a synthesis of systems and synthetic biology approaches for the investigation of stress responses and cell-cell variability, with the aim of extracting the overarching principles that underlie biological homeostasis and robustness. Her research group is also involved in the establishment of computational and technological infrastructures that allow for the integration and analysis of the complex dynamics of biological networks.