Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level
A. Davidovi, R.P. Chait, G. Batt, J. Ruess, PLoS Computational Biology 18 (2022).

Supporting text and results
J. Ruess, M. Pleska, C.C. Guet, G. Tkadik, (2019).

Molecular noise of innate immunity shapes bacteria-phage ecologies
J. Ruess, M. Pleska, C.C. Guet, G. Tkadik, PLoS Computational Biology 15 (2019).

Shaping bacterial population behavior through computer interfaced control of individual cells
R.P. Chait, J. Ruess, T. Bergmiller, G. Tkadik, C.C. Guet, Nature Communications 8 (2017).

Adaptive moment closure for parameter inference of biochemical reaction networks
C. Schilling, S. Bogomolov, T.A. Henzinger, A. Podelski, J. Ruess, Biosystems 149 (2016) 15–25.

Iterative experiment design guides the characterization of a light-inducible gene expression circuit
J. Ruess, F. Parise, A. Milias Argeitis, M. Khammash, J. Lygeros, PNAS 112 (2015) 8148–8153.

Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space
J. Ruess, Journal of Chemical Physics 143 (2015).

Adaptive moment closure for parameter inference of biochemical reaction networks
S. Bogomolov, T.A. Henzinger, A. Podelski, J. Ruess, C. Schilling, 9308 (2015) 77–89.

Moment-based methods for parameter inference and experiment design for stochastic biochemical reaction networks
J. Ruess, J. Lygeros, ACM Transactions on Modeling and Computer Simulation 25 (2015).

Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study
F. Parise, J. Lygeros, J. Ruess, Frontiers in Environmental Science 3 (2015).