Choi | Biomedical and Molecular Sciences | School of Medicine

Jihoon Choi PhD in Experimental Medicine, Queen’s University

Position(s)

Adjunct Professor

Contact Info

I began my academic training at Queen’s University, where I earned a Bachelor of Computing (B.CompH), followed by a PhD in Experimental Medicine with a specialization in Computational Genomics. During my doctoral studies, I developed and applied bioinformatics methodologies to investigate the molecular mechanisms underlying complex traits, with a particular focus on multi-omics integration and machine learning.

After completing my graduate training, I worked at Statistics Canada as a Lead Data Scientist, where I contributed to the development of a national epidemiological forecasting framework in response to the COVID-19 pandemic. My work involved constructing compartmental models to simulate infection dynamics and assess the impact of public health interventions and vaccination strategies. These models supported projections of medical equipment demand and played a critical role in informing federal policy and strategic decision-making during the public health crisis.

I currently hold dual roles as an adjunct faculty member in the Department of Biomedical and Molecular Sciences (DBMS) at Queen’s University and as a senior scientist in the Cross-Tech and Bioinformatics Division at F. Hoffmann-La Roche AG. My work focuses on the development and application of advanced statistical and computational methods for analyzing high-throughput biological data. A central focus of this research is the integration of diverse multi-omics datasets leveraging machine learning frameworks to advance translational research across R&D teams in both Canada and the United States.

At Queen’s, I engage in interdisciplinary research at the intersection of computational and biomedical sciences, supervise trainees, and contribute to curriculum design and instruction in applied biomedical computing and bioinformatics. I maintain active collaborations across academic, clinical, and industrial domains, with the goal of advancing integrative science and accelerating the real-world application of data-driven methodologies in biomedicine and healthcare.

Research Interests

A central focus of my research is the integrative analysis of multi-omics data, encompassing genomics, transcriptomics, epigenomics, proteomics, and metabolomics, as well as longitudinal clinical phenotypes and environmental exposure data. Recognizing the multifactorial nature of human health and disease, I adopt a systems-level, holistic approach that moves beyond single-omic methodologies. My work seeks to characterize the complex, often nonlinear relationships between molecular signals and phenotypic outcomes by leveraging tools such as network-based inference, latent variable modeling, and representation learning.

Specifically, my contributions span the design and implementation of deep learning models for biological feature extraction, the construction of gene and protein interaction networks, and the development of scalable, reproducible bioinformatics methodologies/pipelines optimized for high-throughput data environments, facilitating discovery at both the population and single-cell levels.

An important dimension of my work involves aligning computational innovation with real-world clinical utility. This includes identifying molecular biomarkers for disease risk and therapeutic response, building predictive models for stratified medicine, and elucidating biological mechanisms that may guide the development of targeted interventions. I am particularly interested in translating computational outputs into clinically actionable knowledge by integrating biological context, domain expertise, and rigorous validation strategies.

Selected Publications

Ambalavanan, L. Cheng, J. Choi, Y. Zhang, S. Stickley, Z, Fang, et al "Interactions with early-life exposures modulate polygenic risk of wheeze and asthma in preschool-aged children”, Nature Communications, Sept 2024. DOI: 10.1038/s41467-024-51743-6
D. Topouza, J. Choi, S. Nesdoly, A. Tarnouskaya, C. Nicol, Q. Duan, "Novel MicroRNA-Regulated Transcript Networks Are Associated with Chemotherapy Response in Ovarian Cancer", International Journal of Molecular Sciences, April 2022. DOI: 10.3390/ijms23094875
R. Dai, K. Miliku, S. Gaddipati, J. Choi, A. Ambala, M. Tran, et al, "Wheeze Trajectories: Determinants and Outcomes in the CHILD Cohort Study", The Journal of Allergy and Clinical Immunology, December 2021. DOI: 10.1016/j.jaci.2021.10.039
J. Choi, D. Topouza, A. Tarnouskaya, S. Nesdoly, M. Koti, Q. Duan, "Gene networks and expression quantitative trait loci associated with adjuvant chemotherapy response in high-grade serous ovarian cancer", BMC Cancer, May 2020. DOI: 10.1186/s12885-020-06922-1
M. Neville, J. Choi, J. Lieberman, Q. Duan, "Identification of deleterious and regulatory genomic variations in known asthma loci", Respiratory Research, December 2018. DOI: 10.1186/s12931-018-0953-2
J. Choi, K. Tantisira, Q. Duan, "Whole genome sequencing identifies high-impact variants in well-known pharmacogenomic genes", The Pharmacogenomics Journal, September 2018. DOI: 10.1038/s41397-018-0048-y

Team

Research Interests

Selected Publications

Faculty