Yun Min Song - Research

Publications

†: co-1st author, *: co-corresponding Author

In preparation

Vu, N.-A. T.†, Song, Y. M., Yun, H.-Y.*, Kim, S. K.*, Lee, S.*, Kim, J. K.*, Chae, J.-W.*, Beyond the Michaelis-Menten: Evaluation of a Novel IVIVE Approach for Predicting In Vivo Intrinsic Clearance from Hepatocyte Assays. (In revision, CPT:PSP)
Chae, S. J.†, Kim, J. I.†, Jo, H., Song, Y. M., Jeon, S., Moon, S.-Y., Lee, J.-H., Oh, S., Chung, S., Kim, J. K.*, Kim, J.-H.*, Identifying risk factors of PTSD among a nationwide cohort of firefighters using a machine learning algorithm. (Submitted)
Song, Y. M.†, Jeon, S.†, Cho, A., Chung, S., Ahn, Y., Kim, J. K.*, Suh, S.*, Individual and occupational predictors of sleep intervention response among shift-working firefighters. (Submitted)
Lim, D.†, Moon, S.†, Song, Y. M., Kim, J., Kim, K., Cho, B-K, Kim, J.*, Kim, J. K.*, Toward single-cell control: noise-robust perfect adaptation in biomolecular systems. (In revision, Nature Communications)

2025

Lee, J.†, Song, Y. M.†, Yoon, H.-Y., Choi, S.*, Kim, J. K.*, (2025). Beyond Michaelis-Menten: A modified enzyme kinetics equation improves drug metabolism prediction in bottom-up PBPK modeling. European Journal of Pharmaceutical Sciences
Song, Y. M.†, Choi, S. J.†, Lim, D., Wijaya, R. H., Jang, H. J., Park, H. R., Joo, E. Y.*, Kim, J. K.*, (2025). A digital, real-time, history-based sleep-management tool to enhance alertness. Sleep
Jang, H. J.†, Song, Y. M.†, Jeon, J. S., Yun, H., Kim, S. K.*, Kim, J. K.*, (2025). Optimizing enzyme inhibition analysis: Precise estimation with a single inhibitor concentration. Nature Communications.
Lim, D.†, Choi, S. J.†, Song, Y. M., Park, H. R., Joo, E. Y.*, Kim, J. K.*, (2025). Enhanced circadian phase tracking: A 5-hour DLMO sampling protocol using wearable data. Journal of Biological Rhythms.
Song, Y. M.†, Lee, K, Kim, J. K.*, (2025). Validity of the total QSSA in stochastic biochemical reaction networks, JKSIAM

2024

Lim, D.†, Jeong, J.†, Song Y. M., Lee, H.-J.*, Kim J. K.*, (2024). Highly accurate prediction of mood episodes in mood disorder patients using sleep and circadian rhythm features from wearables. npj Digital Medicine.
Song, Y. M.†, Kim, J. K.*, (2024). What’s driving rhythmic gene expression: Sleep or the clock?, Cell Systems.
Song, Y. M.†, Jeong, J.†, de los Reyes, A. V.†, Lim, D., Cho, C.-H., Yeom, J. W., Lee, T., Lee, J.-B., Lee, H.-J.*, Kim, J. K.*, (2024). Causal dynamics of sleep, circadian rhythm, and mood in major depression and bipolar disorder patients: Insights from longitudinal wearable device data. eBiomedicine.
Song, Y. M.†, Campbell, S.†, Shiau, L., Kim, J. K.*, Ott, W.*, (2024). Noisy delay denoises biochemical oscillators. Physical Review Letters.

2023

Lee, M. P.†, Hoang, K.†, Park, S., Song, Y. M., Joo, E. Y., Chang, W.*, Kim, J. H.*, Kim, J. K.*, (2023). Imputing missing sleep data from wearables with neural networks in real-world settings. Sleep.
Song, Y. M.†, Choi, S. J.†, Park, S. H., Lee, S. J., Joo, E. Y.*, Kim, J. K.*, (2023). A real-time, personalized sleep intervention using mathematical modelling and wearable devices. Sleep.
Vu, N. T.†, Song, Y. M.†, Tran, Q. T.†, Yun, H., Kim, S. K.*, Chae, J., Kim*, J. K.*, (2023). Beyond the Michaelis-Menten: accurate prediction of drug interactions through cytochrome P450 3A4 induction. Clinical Pharmacology & Therapeutics.

2022

Jeong, E. M.†, Song, Y. M., & Kim, J. K.*, (2022). Combined multiple transcriptional repression mechanisms generate ultrasensitivity and oscillations. Interface Focus.
Song, Y. M.†, Hong, H.†, & Kim, J. K.*, (2021). Universally valid reduction of multiscale stochastic biochemical systems using simple non-elementary propensities. PLoS Comp Biol.

2014

Kwon, G., Park, S. H., Song, Y. M., Choi, S. W., Park, P. S.*, (2014). A study on solutions of Jisuguimundo using the range of magic sums. Journal for History of Mathematics.

Patents

개인 맞춤형 수면 패턴 제공 시스템 Personalized sleep pattern providing system (출원번호: 10-2023-0088588 (2023.07.07))
효소 억제 분석 방법 Enzyme inhibition analysis method (출원번호: 10-2024-0139208 (2024.10.14))

Biological Research Interests

Analyzing human activity and sleep-wake data to develop digital medicine solutions

My goal is to analyze human activity and sleep-wake data from wearable devices by integrating mechanistic models with data-driven approaches. I apply mathematical models of sleep regulation and alertness prediction, combined with machine learning techniques, to uncover key factors influencing sleep quality, mood changes, and overall health. This fusion of mechanistic and data-driven modeling not only supports the development of applications that provide users with optimal sleep-wake patterns but also enables disease prediction and early detection from multimodal data. Ultimately, I aim to create personalized digital health solutions that are both scientifically rigorous and practically impactful.

Mathematical Research Interests

Development of reduction methods for multi-scale deterministic/stochastic systems

Biochemical systems are often modeled using ordinary differential equations or chemical master equations. In cases of timescale separation, these models can be simplified by replacing fast species with their Quasi-Steady-State-Approximations, resulting in non-elementary reaction rates. My focus is to determine the validity conditions for these methods and variants and to develop new reduction methods. I apply these methods in real-world scenarios such as biological oscillators and pharmacokinetics, which can provide valuable insights into biological systems and accurate drug pharmacokinetic predictions.