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My research focuses on programming new cellular behaviors by designing and embedding synthetic gene networks that perform desired functions in single cells and multi-cellular environments. We genetically engineer a variety of cell types including bacteria, yeast, and mammalian stem cells. This nascent field of Synthetic Biology holds promise for a wide range of applications such as programmed tissue engineering, environmental biosensing and effecting, biomaterial fabrication, and an improved understanding of naturally occuring biological processes.
The construction of de-novo genetic circuits begins with the assembly and characterization of genetic parts, or building blocks. We have assembled a library of genetic components that regulate transcription, translation, phosphorylation, and synthesis of and response to signaling molecules such as acyl-homoserine lactones in bacteria and cytokinins in Eukaryotes. We then combine these parts into various network topologies that elicit new behaviors in a programmable fashion. In single cells, we have constructed transcriptional cascades and other network topologies with feedback and feed-forward motifs. We have shown theoretically and experimentally that these networks can perform digital computation, attenuate gene expression noise, or exhibit analog programmed functions such as pulse generation. Through the construction and analysis of such fundamental network motifs, we aim to demonstrate sophisticated programmed control over gene expression as well as improve our quantitative understanding of naturally occurring complex gene networks.
The construction of de-novo genetic circuits begins with the assembly and characterization of genetic parts, or building blocks. We have assembled a library of genetic components that regulate transcription, translation, phosphorylation, and synthesis of and response to signaling molecules such as acyl-homoserine lactones in bacteria and cytokinins in Eukaryotes. We then combine these parts into various network topologies that elicit new behaviors in a programmable fashion. In single cells, we have constructed transcriptional cascades and other network topologies with feedback and feed-forward motifs. We have shown theoretically and experimentally that these networks can perform digital computation, attenuate gene expression noise, or exhibit analog programmed functions such as pulse generation. Through the construction and analysis of such fundamental network motifs, we aim to demonstrate sophisticated programmed control over gene expression as well as improve our quantitative understanding of naturally occurring complex gene networks.
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IEEE ROBOTICS AND AUTOMATION LETTERSno. 2 (2024): 1819-1826
Yonger Xue,Yuebao Zhang,Yichen Zhong,Shi Du,Xucheng Hou,Wenqing Li, Haoyuan Li, Siyu Wang,Chang Wang,Jingyue Yan,Diana D. Kang, Binbin Deng,
Nature Communicationsno. 1 (2024): 1-13
Taciani de Almeida Magalhaes, Jingjing Liu,Charlene Chan,Kleiton Silva Borges,Jiuchun Zhang,Andrew J. Kane,Bradley M. Wierbowski, Yunhui Ge, Zhiwen Liu,Prabhath Mannam,Daniel Zeve,Ron Weiss,
DEVELOPMENTAL CELLno. 2 (2024): 244-+
arXiv (Cornell University)no. 2 (2024): 1819-1826
IEEE Robotics and Automation Lettersno. 2 (2024): 1819-1826
Noreen Wauford, Akshay Patel,Jesse Tordoff,Casper Enghuus, Andrew Jin,Jack Toppen,Melissa L Kemp,Ron Weiss
Cell systemsno. 9 (2023): 806-818.e5
SCIENCE ADVANCESno. 48 (2023)
Journal of visualized experiments : JoVE (2023)
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