Dynamics of Chemosensory Receptors

During odor-guided navigation, animals must interpret context-dependent information from fluctuating odor signals to make informed decisions. To understand how olfactory neurons encode this sensory information, I investigate the dynamics of ligand-receptor binding between odorants and olfactory receptors.

1. K. Choi*, W. Rosenbluth*, I.R. Graf, N. Kadakia, T. Emonet. 2024. “Bifurcation Enhances Temporal Information Encoding in the Olfactory Periphery.” PRX Life. 2, 043011. 10.1103/PRXLife.2.043011.

2. W.K. Kim, K. Choi, C. Hyeon, S.J. Jang. 2023. “General Chemical Reaction Network Theory for GPCR-Based Olfactory Sensing: Elucidation of Odorant Mixture Effects and Agonist–Synergist Threshold.” J. Phys. Chem. Lett. 14 (XXX), 8412–8420. 10.1021/acs.jpclett.3c02310.

Olfactory Coding and Decision Making

In addition to olfactory cues, navigational decision-making is shaped by the odor value, which is closely linked to its function and context. I am interested in understanding the principles behind how the brain encodes odors, how odor perception evolves, and how various navigational cues are integrated to guide informed decision-making.

1. K. Choi, W.K. Kim, C. Hyeon. 2024. “Unveiling the Odor Representation in the Inner Brain of Drosophila through Compressed Sensing.” Physical Review Research. 6 (2), 023298.10.1103/PhysRevResearch.6.023298.

Structure to Function in Neural Processing

The brain’s structural, spatial, and connective features govern neural dynamics. I investigate the relationship between neuron structure and function by analyzing and creating models based on large-scale connectomics and structural reconstruction data.

1. K. Choi, W.K. Kim, C. Hyeon. 2022. “Olfactory responses of Drosophila are encoded in the organization of projection neurons.” eLife. 11, e77748. 10.7554/eLife.77748.

2. S.H. Kim, J.H. Woo, K. Choi, M.Y. Choi, K. Han. 2022. “Neural information processing and computations of two-input synapses.” Neural Computation. 34 (10), 2102–2131. 10.1162/neco_a_01534.

3. J.H. Woo*, K. Choi*, S.H. Kim, K. Han, M.Y. Choi. 2021. “Characterization of multiscale logic operations in the neural circuits.” Front Biosci.-Landmark. 26 (10), 723–739. 10.52586/4983.

Softwares/Algorithms for Biological Systems

Biological processes are complex and demand advanced software tools and algorithms. I develop tools to analyze biological networks, including biochemical reactions, neural networks, and signaling pathways. My research also focuses on high-throughput optimization algorithms, network inference techniques, and innovative clustering methods for biological systems. Additionally, I work to enhance model reuse and reproducibility in biological modeling.

1. K. Choi, J.K. Medley, M. König, K. Stocking, L. Smith, S. Gu, H.M. Sauro. 2018. “Tellurium: An Extensible Python-based Modeling Environment for Systems and Synthetic Biology.” BioSystems. 171, 74–79. 10.1016/j.biosystems.2018.07.006.

2. K. Choi, W.K. Kim, C. Hyeon. 2022. “Polymer physics-based classification of neurons.” Neuroinformatics. 21, 177–193. 10.1007/s12021-022-09605-3.

3. C. Welsh, J. Xu, L. Smith, M. König, K. Choi, H.M. Sauro. 2023. “libRoadRunner 2.0: A High-Performance SBML Simulation and Analysis Library.” Bioinformatics. 39 (1), btac770. 10.1093/bioinformatics/btac770.