Using deep learning methods to redesign thermostable rubisco activase

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About This Project

Due to climate change, plants are subject to unprecedented levels of heat stress. Heat stress causes crucial thermolabile proteins, such as rubisco activase (RCA), to denature and aggregate, drastically reducing efficiency of carbon fixation. Using deep learning-based computational methods, however, we can design thermostable versions of RCA to confer thermotolerance, creating plants that can fix carbon and grow in increasingly extreme environments.

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Meet the Team

Joseph Min
Joseph Min
Graduate Student

Joseph Min

Hey! I'm Joe, a software-engineer-turned-grad-student. I'm broadly interested in applying computational methods of protein design to plants!

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