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Yen Ting Lin

Postdoc
CNLS/t-6

Nonequilibrium statistical mechanics and biological physics

Yen Ting Lin

Office: TA-3, Bldg 1690, Room 138
Mail Stop: B258
Phone: (505) 606-8038
Fax: (505) 665-2659

yentingl@lanl.gov
home page

Research highlight
  • Y. T. Lin and N. E. Buchler, Efficient analysis of stochastic gene dynamics in the non-adiabatic regime using piecewise deterministic Markov processes. J. R. Soc. Interface 15: 20170804 (2018)

  • Y. T. Lin, Song Feng, and W. S. Hlavacek, Scaling methods to accelerate stochastic simulation for large and realistic chemical reaction networks (in final preparation for submission)

  • Y. T. Lin and N. E. Buchler, Efficient sampling algorithm for statistical inference and model selection using data from single-cell and single-molecule experiments (On-going project)
 Educational Background/Employment:
  • B.Sc. (2004) Department of Physics, National Taiwan University, TW
  • M.Sc. (2006) Theoretical physics, Department of Physics, National Taiwan University, TW
  • Ph.D. (2013) Department of Physics, University of Michigan -- Ann Arbor, USA
  • Employment:
    • Postdoctoral Fellow (2013-2014), Department of Biological Physics, Max Planck Institute for the Physics of Complex Systems, DE
    • Postdoctoral Research Associate (2015-2016), Theoretical Division, The University of Manchester, UK

Research Interests:

  • Non-equilibrium statistical physics
  • Applied stochastic processes
  • Biological physics
  • Asymptotic methods
  • Uncertainty quantification
  • Statistical inference
  • Computational system biology

Selected Recent Publications:

    
  1. A. Shirin, I. Klickstein, S. Feng, Y. T. Lin, W. S. Hlavacek, and F. Sorrentino, Optimal Drug Cocktails and Drug Dosages to Control Autophagy (in final preparation for submission)
  2. Y. T. Lin, Song Feng, and W. S. Hlavacek, Scaling methods to accelerate stochastic simulation for large and realistic chemical reaction networks (in final preparation for submission)
  3. W. Huang, Y. T. Lin, D. Frömberg, J. Shin, F. Jülicher, and V. Zaburdaev, Exactly solvable dynamics of forced polymer loops (submitted)
  4. P. Hufton, Y. T. Lin and T. Galla, Model reduction methods for classical stochastic systems with fast-switching environments: Reduced master equations, stochastic differential equations, and applications (submitted)
  5. Y. T. Lin, N. W. Lemons, L. A. Chylek, and W. S. Hlavacek, Using equation-free computation to accelerate stochastic simulation of chemical kinetics (submitted)
  6. P. Bokes, Y. T. Lin, A. Singh, High Cooperativity In Negative Feedback Can Amplify Noisy Gene Expression, Bull. Math. Biol. online first (2018)
  7. Ryan Suderman, Eshan D. Mitra, Yen Ting Lin, Keesha E. Erickson, Song Feng1,2, and William S. Hlavacek, Generalizing Gillespie’s Direct Method to Enable Network-Free Simulations, Bull. Math. Biol. online first (2018)
  8. Y. T. Lin, P. Hufton, E. Lee, D. Potoyan, A stochastic and dynamical view of pluripotency in mouse embryonic stem cells, PLoS Computational Biology 14(2): e1006000 (2018)
  9. Y. T. Lin and N. E. Buchler, Efficient analysis of stochastic gene dynamics in the non-adiabatic regime using piecewise deterministic Markov processes. J. R. Soc. Interface 15: 20170804 (2018)
  10. P. Hufton, Y. T. Lin and T. Galla, Phenotypic switching of populations of cells in a stochastic environment, J. Stat. Mech. 023501 (2018)
  11. Y. T. Lin, E. T. Y, Chang, J. Eatock, T. Galla, R. H. Clayton, Mechanisms of stochastic onset and termination of atrial fibrillation studied with a cellular automaton model, J. R. Soc. Interface 14: 20160968 (2017)
  12. P. Hufton, Y. T. Lin, T. Galla, and A. J. McKane, Intrinsic noise of population dynamics in randomly switching environments, Phys. Rev. E 93 052119 (2016)
  13. E. T. Y, Chang, Y. T. Lin, T. Galla, R. H. Clayton, and J. Eatock, A Stochastic Individual-Based Model of the Progression of Atrial Fibrillation in Individuals and Populations, PLoS ONE 11(4): e0152349 (2016)
  14. Y. T. Lin and C. R. Doering, Gene expression dynamics with stochastic bursts: construction and exact results for a coarse-grained model, Phys. Rev. E 93, 022409 (2016)
  15. Y. T. Lin and T. Galla, Bursting noise in gene expression dynamics: Linking microscopic and mesoscopic models, J. R. Soc. Interface 13: 20150772 (2016)
  16. Y. T. Lin, D. Frömberg, W. Huang, P. Delivani, M. Chacón, I. M. Tolic, F. Jülicher, and V. Zaburdaev, Pulled polymer loops as a model for the alignment of meiotic chromosomes, Phys. Rev. Lett. 115 208102 (2015)
  17. J. Eatock, Y. T. Lin, E. T. C. Chang, T. Galla, R. H. Clayton, Assessing Measures of Atrial Fibrillation Clustering via Stochastic Models of Episode Recurrence, Proceedings of Computing in Cardiology (2015)
  18. C. Weber, Y. T. Lin, N. Biais, and V. Zaburdaev, Formation and dissolution of bacterial colonies, Phys. Rev. E 92 032704 (2015)
  19. J. Taktikos, Y. T. Lin, H. Stark, N. Biais, and V. Zaburdaev, Pili-induced clustering of N. gonorrhoeae bacteria, PLoS ONE 10(9): e0137661 (2015)
  20. Y. T. Lin, H. Kim, and C. R. Doering, Demographic stochasticity and the evolution of dispersion II. Spatially inhomogeneous environments, J. Math. Biol. 70(3) 679-707 (2015, accepted in 2014, submitted in 2013).
  21. Y. T. Lin, H. Kim, and C. R. Doering, Demographic stochasticity and the evolution of dispersion I. Spatially homogeneous environments, J. Math. Biol. 70(3) 679-707 (2015, accepted in 2014, submitted in 2013).
  22. Y. T. Lin, H. Kim, and C. R. Doering, Features of fast living: On the weak selection for longevity in degenerate birth-death processes, J Stat. Phys. 148(4) 646-662 (2012)
  23. E. Khain, Y. T. Lin, and L. M. Sander, Fluctuations and stability in front propagation, Euro. Phys. Lett., 93 28001 (2011)
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