Conference Papers & Book Chapters

Conference Papers & Book Chapters

2019

22. Paulino NMG, Foo M, Kim J, Bates DG, PID and state feedback controllers using DNA strand displacement reactions, IEEE Conference on Decision and Control, p., 2019.

Prior to POSTECH

21. Paulino NMG, Foo M, Kim J, Bates DG, Uncertainty modelling and stability robustness analysis of nucleic acid-based feedback control systems, IEEE Conference on Decision and Control, p. 1077-1082, 2018.
20. Jafarnejadsani H, Kim J, Kulkarni VV, Hovakimyan N, Load capacity improvements in nucleic acid based systems using discrete-time feedback control, The 5th International Conference on Control, Decision and Information Technology (CoDIT), p. 1–6, 2018.
19. Green AA, Kim J, Ma D, Silver PA, Collins JJ, Yin P, Ribocomputing devices for sophisticated in vivo logic computation, The 3rd ACM International Conference on Nanoscale Computing and Communication, p. 11, 2016.
18. Mardanlou V, Green LN, Subramanian HK, Hariadi RF, Kim J, Franco E, A coarse-grained model of DNA nanotube population growth, The 22nd International Conference on DNA Computing and Molecular Programming, p. 135–147, 2016.
17. Jafarnejadsani H, Kim J, Hovakimyan N, Kulkarni VV, Load capacity improvements in transcriptional systems using discrete-time L1-adaptive control, Proceedings on 8th International Workshop on Bio-Design Automation, p. 75–76, 2016.
16. Foo M, Sawlekar R, Kim J, Bates DG, Stan G-B, Kulkarni V, Biomolecular implementation of nonlinear system theoretic operators, IEEE European Control Conference, p. 1824–1831, 2016.
15. Schwarz-Schilling M, Kim J, Cuba C, Weitz M, Franco E, Simmel FC, Building a synthetic transcriptional oscillator, Methods in Molecular Biology 1342:185-199, 2016.
14. Yeung E, Kim J, Gonçalves J, Murray RM, Global network identification from reconstructed dynamical structure subnetworks: Applications to biochemical reaction networks, IEEE Conference on Decision and Control, p. 881–888, 2015.
13. Tuza ZA, Siegal-Gaskins D, Kim J, Szederkényi G, Analysis-based parameter estimation of an in vitro transcription-translation system, IEEE European Control Conference, p. 1560–1566, 2015.
12. Sun ZZ, Kim J, Singhal V, Murray RM, Protein degradation in a TX-TL cell-free expression system using ClpXP protease, Technical Report, 2015.
11. Yeung E, Ng A, Kim J, Sun ZZ, Murray RM, Modeling the effects of compositional context on promoter activity in an E. coli extract based transcription-translation system, IEEE Conference on Decision and Control, p. 5405–5412, 2014.
10. Sen S, Kim J, Murray RM, Designing robustness to temperature in a feedforward loop circuit, IEEE Conference on Decision and Control, p. 4629–4634, 2014.
9. Kim J, Franco E, Synthetic biochemical devices for programmable dynamic behaviors, Chapter 12 in A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems, Kulkarni V, Stan G-B, Raman K (eds.), Springer, 2014.
8. Yeung E, Kim J, Murray RM, Resource competition as a source of non-minimum phase behavior in transcription-translation systems, IEEE Conference on Decision and Control, p. 4060–4067, 2013.
7. Tuza ZA, Singhal V, Kim J, Murray RM, An in silico modeling toolbox for rapid prototyping of circuits in a biomolecular ‘breadboard’ system, IEEE Conference on Decision and Control, p. 1404–1410, 2013.
6. Franco E, Kim J, Simmel FC, Transcription Oscillators, Chapter 4 in Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain, Misha (Meyer) Z. Pesenson (ed.), Wiley-VCH Verlag GmbH & Co. KGaA, 2013.
5. Yeung E*, Kim J*, Yuan Y, Gonçalves J, Murray RM, Quantifying crosstalk in biochemical systems, IEEE Conference on Decision and Control, p. 5528–5535, 2012. *, co-corresponding authors.
4. Kulkarni VV, Chanyaswady T, Riedel M, Kim J, Robust tunable in vitro transcriptional oscillator networks, 50th Annual Allerton Conference on Communication, Control, and Computing, p. 114–119, 2012.
3. Kim J, Murray RM, Analysis and design of a synthetic transcriptional network for exact adaptation, IEEE Biomedical Circuits and Systems Conference, p. 345–348, 2011.
2. Kim J, Synthetic Networks, Chapter 10 in Automation in proteomics and genomics: an engineering case-based approach, Alterovitz G, Benson R, Ramoni M (eds.), John Wiley & Sons, 2009.
1. Kim J, Hopfield JJ, Winfree E, Neural network computation by in vitro transcriptional circuits, Advances in Neural Information Processing Systems 17:681–688, 2004.