Mustafa Khammash

Mechanical Engineering University of California, Santa Barbara, Santa Barbara, CA, United States 
Mechanical Engineering
"Mustafa Khammash"


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Hana El-Samad grad student (Cell Biology Tree)
Hana El Samad grad student 2004 UC Santa Barbara
Keith B. Purvis grad student 2007 UC Santa Barbara
Gabriele Lillacci grad student 2012 UC Santa Barbara
Patrick W. Sheppard grad student 2012 UC Santa Barbara
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Aoki SK, Lillacci G, Gupta A, et al. (2019) A universal biomolecular integral feedback controller for robust perfect adaptation. Nature
Dürrenberger P, Gupta A, Khammash M. (2019) A finite state projection method for steady-state sensitivity analysis of stochastic reaction networks. The Journal of Chemical Physics. 150: 134101
Gupta A, Khammash M. (2018) Sensitivity Analysis for Multiscale Stochastic Reaction Networks Using Hybrid Approximations. Bulletin of Mathematical Biology
Lillacci G, Benenson Y, Khammash M. (2018) Synthetic control systems for high performance gene expression in mammalian cells. Nucleic Acids Research
Briat C, Gupta A, Khammash M. (2018) Antithetic proportional-integral feedback for reduced variance and improved control performance of stochastic reaction networks. Journal of the Royal Society, Interface. 15
Briat C, Khammash MH. (2018) Perfect adaptation and optimal equilibrium productivity in a simple microbial biofuel metabolic pathway using dynamic integral control. Acs Synthetic Biology
Gupta A, Rathinam M, Khammash M. (2018) Estimation of Parameter Sensitivities for Stochastic Reaction Networks Using Tau-Leap Simulations Siam Journal On Numerical Analysis. 56: 1134-1167
Gupta A, Mikelson J, Khammash M. (2017) A finite state projection algorithm for the stationary solution of the chemical master equation. The Journal of Chemical Physics. 147: 154101
Briat C, Khammash M. (2017) Robust and structural ergodicity analysis of stochastic biomolecular networks involving synthetic antithetic integral controllers Ifac-Papersonline. 50: 10918-10923
Briat C, Gupta A, Khammash M. (2016) Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks. Cell Systems. 2: 15-26
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