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Your certificate is now private

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Certificate of Completion

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THIS ACKNOWLEDGES THAT

HAS COMPLETED THE FALL 2024 DATA SCIENCE BOOT CAMP

Jaehyoun Seiler

Roman Holowinsky, PhD

December 11, 2024

DIRECTOR

DATE

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TEAM

ML Based QSAR On TRPM8

Jaehyoun Seiler, Adedolapo Ojoawo, Carmen Al Masri, Jessica Pan

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Our goal for this project was to use Quantitative structure-activity relationship (QSAR) to predict inhibitors for transient receptor potential cation channel subfamily M member 8 (TRPM8), an ion channel that mediates both cold and pain. QSAR enables the prediction of the molecule's potency based on its physical, chemical and structural properties. In this project, we developed a QSAR workflow, and then chose TRPM8 as a representative protein to test our process. We chose TRPM8 because there are no approved drugs for it. Creating a model that would allow us to screen thousands of molecules and computationally score their inhibitor ability would be immensely useful, as it cuts down on the costly and lengthy process of screening these molecules in the lab.

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