IN/SBLab
Integrative NeuroAI-Systems Biology Group at Keimyung University
We study the principles that govern olfaction, from receptor dynamics to perception and decision-making.
Using the Drosophila olfactory system as a model, we inestigate how the brain transforms complex sensory inputs into adaptive behavior. Our work follows olfactory processing across scales, from the physical dynamics of ligand-receptor binding to the neural computations that guide navigation.
We integrate computational modeling, artificial intelligence, and quantitative experiments to understand how biological systems—from signaling pathways to the Drosophila brain—detect signals, transform information, and generate responses.
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🔬 What we study
1. Olfactory Perception & Decision-Making
We investigate how animals use olfactory information to make decisions in complex environments. By combining behavioral experiments with artificial intelligence, we seek to identify the neural computations that link odor perception to navigation in Drosophila.
2. Dynamics of Chemosensory Receptors
We study the dynamics of chemosensory receptors to understand how cells reliably encode external stimuli. Our goal is to define the fundamental limits of sensory encoding at the molecular interface.
3. Machine Learning for Biological Discovery
We apply machine learning to extract interpretable structure from complex biological data. We develop models to predict functional properties from molecular structure and use explainable AI to investigate the principles underlying biological phenomena.
4. Information Processing in Biological Systems
We use olfaction as a model to uncover general principles of biological computation. We investigate how biological networks—from biochemical signaling pathways to neural circuits—process information while remaining robust to perturbations.
5. Biological Algorithm Development
We develop computational methods for network inference, optimization, and clustering to analyze high-dimensional biological data.
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