Taesung Park

Professor

Seoul National University

South Korea

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About

Taesung Park is a Professor at Seoul National University in South Korea. His research focuses on microbiome markers, drug-induced liver injury, metabolomics related to type 2 diabetes, and COVID-19 dynamics. He has contributed to significant studies on causal effects of diabetes and obesity traits on COVID-19 severity, as well as advanced methodologies in genomic data analysis.

Articles (18)

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2025

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2023

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2022

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2022

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2022

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2022

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2022

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2022

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2022

Collaborators (3)

Jang Jin-Young

Seoul National University Hospital

SOUTH KOREA

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Seungyeoun Lee

Professor

Sejong University

SOUTH KOREA

View details

Sungyoung Lee

Seoul National University Hospital

SOUTH KOREA

View details

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Taesung Park

Research Interests

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About

Articles (18)

Identification of microbiome markers for ordered groups

Comprehensive analysis of high-throughput transcriptomics to distinguish drug-induced liver injury (DILI) phenotypes

Longitudinal Cohort Study of Metabolomic Markers Associated With Type 2 Diabetes Risk in Korean Adults

Hierarchical structural component model for pathway analysis of multinomial phenotypes

Fractional derivative model in COVID-19 dynamics: application to symptom severity and hospital resource allocation in South Korea

Assessing the causal effects of type 2 diabetes and obesity-related traits on COVID-19 severity

Enhanced adaptive permutation test with negative binomial distribution in genome-wide omics datasets

Erratum: Correction of Fig. 2 in the Article “Temporal Radiographic Trajectory and Clinical Outcomes in COVID-19 Pneumonia: A Longitudinal Study”

Temporal Radiographic Trajectory and Clinical Outcomes in COVID-19 Pneumonia: A Longitudinal Study

Kernel-based hierarchical structural component models for pathway analysis on survival phenotype

Korea BioData Station (K-BDS)

Kernel-based hierarchical structural component models for pathway analysis

Comparison of survival prediction models for pancreatic cancer: Cox model versus machine learning models

MP-LASSO chart: a multi-level polar chart for visualizing group LASSO analysis of genomic data

DeepHisCoM: deep learning pathway analysis using hierarchical structural component models

Bayesian analysis of longitudinal traits in the Korea Association Resource (KARE) cohort

Identification of the associations between genes and quantitative traits using entropy-based kernel density estimation

Mathematical modeling of the impact of Omicron variant on the COVID-19 situation in South Korea

Collaborators (3)

Jang Jin-Young

Seungyeoun Lee

Sungyoung Lee

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