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Spatial Statistics|December 13, 2021
An interaction Neyman-Scott point process model for coronavirus disease-19Jaewoo Park, Won Chang, Boseung ChoiStatistics in Medicine|October 9, 2023
A spatio-temporal Dirichlet process mixture model for coronavirus disease-19Jaewoo Park, Seorim Yi, Won Chang, et al.Biometrics|June 18, 2024
A Bayesian convolutional neural network-based generalized linear modelYeseul Jeon, Won Chang, Seonghyun Jeong, et al.Biostatistics (Oxford, England)|August 13, 2011
Inference for discretely observed stochastic kinetic networks with applications to epidemic modelingBoseung Choi, Grzegorz A RempalaPlos Computational Biology|September 5, 2025
A history-dependent approach for accurate initial condition estimation in epidemic modelsDongju Lim, Kyeong Tae Ko, Hyukpyo Hong, et al.Methods in Molecular Biology (Clifton, N.J.)|December 10, 2021
Beyond the Michaelis-Menten: Bayesian Inference for Enzyme Kinetic AnalysisHyukpyo Hong, Boseung Choi, Jae Kyoung KimPharmaceutics|June 28, 2023
Immune-Modulating Lipid Nanomaterials for the Delivery of BiopharmaceuticalsSonghee Kim, Boseung Choi, Yoojin Kim, et al.Plos One|February 12, 2026
Inferring structure and parameters of stochastic reaction networks with logistic regressionBoseung Choi, Hye-Won Kang, Grzegorz A RempalaScientific Reports|December 7, 2017
Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parametersBoseung Choi, Grzegorz A Rempala, Jae Kyoung KimMathematical Biosciences|April 7, 2015
Estimating epidemic parameters: Application to H1N1 pandemic dataElissa J Schwartz, Boseung Choi, Grzegorz A RempalaPageof 73