For interdisciplinary journals, the asterisk (*) and the dagger (†) indicate the (co) first and the (co) corresponding authorship, respectively.
23. Minjun Kim, Seokhwan Moon, and Jinsu Kim, Classification for dynamics of Markov chains on non-negative integers with arbitrary transition rates and its application, submitted, 2025.
22. Dongju Lim*, Seokhwan Moon*, Yun Min Song, Minjun Kim, Jinyeong Kim, Kangsan Kim, Byung-Kwan Cho, Jinsu Kim†, Jae Kyoung Kim†, Toward Single-Cell Control: Noise-Robust Perfect Adaptation in Biomolecular Systems, Nature Communications, 2025.
21. Louis Wai-Tong Fan, Jinsu Kim, and Chaojie Yuan, Boundary-induced slow mixing for Markov chains and its application to stochastic reaction networks, submitted, 2024.
20. Sunghwa Kang* and Jinsu Kim†, Noise-robust training of artificial neural networks using chemical reaction networks, APL Machine Learning, 3, 036102, 2025. Featured as a Scilight paper.
19. Jinsu Kim*†, Christine Sütterlin, Ming Tan, and German Enciso†, Statistical analysis supports size control mechanism of Chlamydia development, PLOS Computational Biology, 21(7): e1013227, 2025.
18. Minjun Kim and Jinsu Kim, A path method for non-exponential ergodicity of Markov chains and its application for chemical reaction systems, Journal of Statistical Physics, Vol 192, Article number 74, 2025.
17. David F. Anderson, Daniele Cappelletti, Wai-Tong Louis Fan, and Jinsu Kim, A new path method for exponential ergodicity of Markov processes on $\mathbb Z^d$, with applications to stochastic reaction networks, SIAM Journal on Applied Dynamical Systems, Vol. 24, Iss. 2, 2025.
16. Jinsu Kim. A review of mathematical perspectives on chemical reaction computing, Journal of Korea Society for Industrial and Applied Mathematics. 28.4 (2024): 120-139.
15. Jinyoung Kim*, Sean D. Lawley, and Jinsu Kim†. A reaction network model of microscale liquid-liquid phase separation reveals effects of spatial dimension, [arxiv], Journal of Chemical Physics, 2024, 161, 204110, (Selected in 2024 JCP Emerging Investigators Special Collection).
14, Keunsu Kim, Hanbaek Lyu, Jinsu Kim, and Jae-Hun Jung, Supervised low-rank semi-nonnegative matrix factorization with frequency regularization for forecasting spatio-temporal data, Journal of Scientific Computing, 2024, 100, 29.
13. Hyukpyo Hong, Bryan S. Hernandez, Jinsu Kim, and Jae Kyoung Kim, Computational translation framework identifies biochemical reaction networks with special topologies and their long-term dynamics, SIAM Journal on Applied Mathematics, 2023, 83(3), 1025-1048.
12. David F. Anderson and Jinsu Kim, Mixing times for two classes of stochastically modeled reaction networks, Mathematical Biosciences and Engineering, 2023, 20(3), 4690-4713.
11. Jinsu Kim*, Katherine Sheu*, Quen Cheng, Alexander Hoffmann†, and German Enciso†. Stochastic models of nucleosome dynamics reveal regulatory rules of stimulus-induced epigenome remodeling, Cell Reports, 40(2), 111076, 2022.
Errata 1: on page e9 Equation 17, K_{n-1,n}=p+qK_{n-2,n} so that K_{0,n}=(r/r-1)*(r^n-1)/(r-1)-n/(r-1). Errata 2: on page e9, T_{7,8}=p_6+q_6T_{6,8} so that T_{7,8}=1+(q_6/p_6)T_6,7}
10. German Enciso and Jinsu Kim, Accuracy of Multiscale Reduction for Stochastic Reaction Systems, SIAM Multiscale Modeling and Simulation, 19(4), 1633–1658, 2021. arXiv.
9. Hyuckpyo Hong*, Jinsu Kim*, M Ali Al-Radhawi, Eduardo Sontag, and Jae Kyoung Kim†. Derivation of stationary distributions of biochemical reaction networks via structure transformation, Communications Biology, 4, 620, 2021.
8. German Enciso, Radek Erban, and Jinsu Kim, Identifiability of Stochastically Modelled Reaction Networks, European Journal of Applied Mathematics, 1-23, 2021. arXiv
7. Jinsu Kim*†, Jason Dark, German Enciso, and Suzanne Sindi, Slack Reactants: A State-Space Truncation Framework to Estimate Quantitative Behavior of the Chemical Master Equation, The Journal of Chemical Physics. 153, 054117, 2020.
6. Enrico Bibbona*, Jinsu Kim, and Carsten Wiuf, Stationary distributions of systems with Discreteness Induced Transitions, Journal of The Royal Society Interface. 1720200243, 2020.
5. David F. Anderson, Daniele Cappelletti, Jinsu Kim, and Tung Nguyen, Tier structure of strongly endotactic reaction networks, Stochastic Processes and their Applications, 130, 7218-7259, 2020.
4. David F. Anderson, Daniele Cappelletti, and Jinsu Kim, Stochastically modeled weakly reversible reaction networks with a single linkage class, Journal of Applied Probability. 57(3), 792-810, 2020
3. Jinsu Kim* and German Enciso†, Absolutely Robust Controllers for Chemical Reaction Networks, Journal of The Royal Society Interface 17: 20200031, 2020.
2. German Enciso and Jinsu Kim, Embracing noise in chemical reaction networks, Bulletin of Mathematical Biology. 81, 1261–1267, 2019.
1. David F. Anderson and Jinsu Kim, Some network conditions for positive recurrence of stochastically modeled reaction networks, SIAM Journal on Applied Mathematics, 78(5), 2692-2713, 2018.
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