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Joint Chemistry + Biochemistry + Biology Seminar Series

This is a past event.

Friday, November 21, 2025 3:30pm to 5pm

263 College Avenue, Holland, MI 49423-3646

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SEMINAR SPEAKERDr. Luke Busta, University of Minnesota
 
TITLE“Leveraging Community Science and Large Language Models to Study the Chemistry of Plants”
 
ABSTRACT: Plants produce some of the most structurally complex and diverse molecules on Earth. I will begin this presentation by describing our laboratory work aimed at understanding how plants transport the molecules they produce from one location to another. I will end by touching on how we are using large language models to survey and systematize decades of scientific knowledge on plant chemical diversity. Throughout, I will emphasize phytochemistry as a key field at the intersection of analytical and organic chemistry, phylogenetics and genomics, as well as computation and machine learning.
 
BIODr. Busta is an Assistant Professor at the University of Minnesota Duluth (UMD) in the Swenson College of Science and Engineering, Department of Chemistry and Biochemistry. He completed his undergraduate studies at UMD, earned a Ph.D. in chemistry from the University of British Columbia while working with Reinhard Jetter, then was a postdoctoral fellow at University of Nebraska mentored by Dr. Edgar B. Cahoon, sponsored by the National Science Foundation’s Plant Genome Research Program. He started a faculty position at UMD in 2020 where his research laboratory investigates the chemistry of plants. Supported by the Research Corporation for Science Advancement and the United State Department of Agriculture, current projects include: (i) developing methods with which we can use large language models (‘artificial intelligence’) to predict the precise chemical reactions that are catalyzed by specific DNA and protein sequences and (ii) developing the crop Sorghum bicolor as a domestic source of natural waxes. Dr. Busta is also interested in developing and evaluating teaching tools and instructional modules designed to teach students about the strengths, weaknesses, and applications of language models systems.   

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