Moment-based inference predicts bimodality in transient gene expression C Zechner, J Ruess, P Krenn, S Pelet, M Peter, J Lygeros, H Koeppl Proceedings of the National Academy of Sciences 109 (21), 8340-8345, 2012 | 262 | 2012 |
Shaping bacterial population behavior through computer-interfaced control of individual cells R Chait, J Ruess, T Bergmiller, G Tkačik, CC Guet Nature communications 8 (1), 1535, 2017 | 113 | 2017 |
Iterative experiment design guides the characterization of a light-inducible gene expression circuit J Ruess, F Parise, A Milias-Argeitis, M Khammash, J Lygeros Proceedings of the National Academy of Sciences 112 (26), 8148-8153, 2015 | 81 | 2015 |
Designing experiments to understand the variability in biochemical reaction networks J Ruess, A Milias-Argeitis, J Lygeros Journal of The Royal Society Interface 10 (88), 20130588, 2013 | 80 | 2013 |
Moment estimation for chemically reacting systems by extended Kalman filtering J Ruess, A Milias-Argeitis, S Summers, J Lygeros The Journal of chemical physics 135 (16), 2011 | 48 | 2011 |
A light tunable differentiation system for the creation and control of consortia in yeast C Aditya, F Bertaux, G Batt, J Ruess Nature Communications 12, 5829, 2021 | 43 | 2021 |
Enabling reactive microscopy with MicroMator ZR Fox, S Fletcher, A Fraisse, C Aditya, S Sosa-Carrillo, J Petit, S Gilles, ... Nature Communications 13 (1), 2199, 2022 | 32 | 2022 |
Estimating information in time-varying signals SA Cepeda-Humerez, J Ruess, G Tkačik PLoS computational biology 15 (9), e1007290, 2019 | 31 | 2019 |
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 (TOMACS) 25 (2), 1-25, 2015 | 30 | 2015 |
To quarantine, or not to quarantine: A theoretical framework for disease control via contact tracing D Lunz, G Batt, J Ruess Epidemics 34, 100428, 2021 | 24 | 2021 |
Beyond the chemical master equation: Stochastic chemical kinetics coupled with auxiliary processes D Lunz, G Batt, J Ruess, JF Bonnans PLoS Computational Biology 17 (7), e1009214, 2021 | 18 | 2021 |
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, 42, 2015 | 16 | 2015 |
Adaptive moment closure for parameter inference of biochemical reaction networks S Bogomolov, TA Henzinger, A Podelski, J Ruess, C Schilling Computational Methods in Systems Biology: 13th International Conference …, 2015 | 16 | 2015 |
Identifying stochastic biochemical networks from single-cell population experiments: A comparison of approaches based on the Fisher information J Ruess, J Lygeros 52nd IEEE conference on decision and control, 2703-2708, 2013 | 16 | 2013 |
Using single-cell models to predict the functionality of synthetic circuits at the population scale C Aditya, F Bertaux, G Batt, J Ruess Proceedings of the National Academy of Sciences 119 (11), e2114438119, 2022 | 13 | 2022 |
Adaptive moment closure for parameter inference of biochemical reaction networks C Schilling, S Bogomolov, TA Henzinger, A Podelski, J Ruess Biosystems 149, 15-25, 2016 | 13 | 2016 |
Optimal control of an artificial microbial differentiation system for protein bioproduction E Weill, V Andreani, C Aditya, P Martinon, J Ruess, G Batt, F Bonnans 2019 18th European Control Conference (ECC), 2663-2668, 2019 | 12 | 2019 |
Optimal control of bioproduction in the presence of population heterogeneity D Lunz, JF Bonnans, J Ruess Journal of Mathematical Biology 86 (3), 43, 2023 | 10 | 2023 |
External control of microbial populations for bioproduction: A modeling and optimization viewpoint F Bertaux, J Ruess, G Batt Current Opinion in Systems Biology 28, 100394, 2021 | 9 | 2021 |
MicroMator: Open and flexible software for reactive microscopy ZR Fox, S Fletcher, A Fraisse, C Aditya, S Sosa-Carrillo, S Gilles, ... bioRxiv, 2021.03. 12.435206, 2021 | 8 | 2021 |