Biological function is governed by highly integrated networks that exhibit nonlinear dynamics at all biochemical/molecular, cellular, and organismal levels. We believe that engineering principles can be employed to better understand, predict, and control complex biological functions, and that these principles need to be informed by biology.
The Modeling Dynamic Life Systems (MODYLS) Lab operates at the evolving interface between engineering and biology, promoting a diverse, creative research environment consisting of engineers and basic scientists that share the common mission of advancing medicine and biology. Through this collective effort, we aim to identify design principles that underlie complex biological function, and modulate extrinsic factors to optimize therapeutic interventions.
Interested in joining the lab? Click here for more information.
Announcements
Jacob Evarts receives an NSF Graduate Research Fellowship for his work on decomposing information sources in agent-based models.
April 2023
Jason Cain publishes The in silico lab: Improving academic code using lessons from biology.
January 2023
Kate Dray successfully defends her thesis!
October 2022
Alex Prybutok publishes Mapping CAR T-cell design space using agent-based models in collaboration with the Leonard lab.
July 2022
Alex Prybutok is awarded the inaugural Distinguished Graduate Service Award in the Department of Chemical and Biological Engineering at Northwestern University.
June 2022
Neda Bagheri is invited as the Plenary Speaker for the International Federation of Automatic Control symposium on Dynamics and Control of Process Systems in Busan, Korea.
June 2022
Alex Prybutok successfully defends her thesis!
April 2022
Alex Prybutok publishes a preprint of Mapping CAR T-cell design space using agent-based models in collaboration with the Leonard lab.
April 2022
Mugdha Sathe showcases her research in the ASCB Emerging Researcher Talk Series.
March 2022
Alex Prybutok and Jason Cain publish Fighting fire with fire: deploying complexity in computational modeling to effectively characterize complex biological systems in collaboration with the Leonard lab.
February 2022
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