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Utilization Of Machine Learning Models In Modeling The Binding Of Aromatic Compounds To Insect Olfactory Receptor Neurons

Semester: Spring 2024

Presentation description

My research revolves around creating methods for designing machine learning models that can interpret 3D ligand-receptor binding models which are based based on real world data. We can then train these machine learning models to point towards which ligands/odorants have the greatest chance of successfully binding to the receptors of their insect of interest before conducting lab or field trials. This can also give researchers a better idea of what types of molecules best fit what receptors.

Presenter Name: Kobi Baker

Presentation Type: Poster
Presentation Format: In Person
Presentation #A72
College: Science
School / Department: Biological Sciences
Research Mentor: Martin Horvath
Date | Time: Tuesday, Apr 9th | 9:00 AM