J. Ruess

发表

Moment-based inference predicts bimodality in transient gene expression

J. Lygeros, M. Peter, H. Koeppl, 2012, Proceedings of the National Academy of Sciences.

Moment estimation for chemically reacting systems by extended Kalman filtering.

J. Lygeros, A. Milias-Argeitis, J. Ruess, 2011, The Journal of chemical physics.

Molecular noise shapes bacteria-phage ecologies

G. Tkačik, J. Ruess, C. Guet, 2018, bioRxiv.

Using Stochastic Models to Control Gene Expression Under a Microscope

G. Batt, J. Ruess, Z. Fox, 2022 .

To quarantine, or not to quarantine: A theoretical framework for disease control via contact tracing

Jakob Ruess, Gregory Batt, Davin Lunz, 2020, Epidemics.

To isolate, or not to isolate: a theoretical framework for disease control via contact tracing

D. Lunz, G. Batt, J. Ruess, 2020, medRxiv.

External control of microbial populations for bioproduction: A modeling and optimization viewpoint

Jakob Ruess, Grégory Batt, François Bertaux, 2021, Current Opinion in Systems Biology.

Estimating information in time-varying signals

Jakob Ruess, Gašper Tkačik, Sarah Anhala Cepeda-Humerez, 2018, PLoS Comput. Biol..

Molecular noise of innate immunity shapes bacteria-phage ecologies

Jakob Ruess, Gašper Tkačik, Maroš Pleška, 2019, PLoS Comput. Biol..

Using single-cell models to predict the functionality of synthetic circuits at the population scale

J. Ruess, F. Bertaux, Chetan Aditya, 2021, bioRxiv.

Optimal control of bioproduction in the presence of population heterogeneity

J. Ruess, D. Lunz, J. Bonnans, 2023, Journal of Mathematical Biology.

Revisiting moment-closure methods with heterogeneous multiscale population models.

J. Ruess, D. Lunz, J. Bonnans, 2022, Mathematical Biosciences.

Beyond the chemical master equation: Stochastic chemical kinetics coupled with auxiliary processes

J. Ruess, D. Lunz, J. Bonnans, 2021, PLoS Comput. Biol..

A light tunable differentiation system for the creation and control of consortia in yeast

J. Ruess, F. Bertaux, Chetan Aditya, 2021, Nature Communications.

Shaping bacterial population behavior through computer-interfaced control of individual cells

Jakob Ruess, Remy Chait, Tobias Bergmiller, 2017, Nature Communications.

Moment-Based Methods for Parameter Inference and Experiment Design for Stochastic Biochemical Reaction Networks

John Lygeros, Jakob Ruess, J. Lygeros, 2015, ACM Trans. Model. Comput. Simul..

Designing experiments to understand the variability in biochemical reaction networks

John Lygeros, Jakob Ruess, Andreas Milias-Argeitis, 2013, Journal of The Royal Society Interface.

Sensitivity estimation for stochastic models of biochemical reaction networks in the presence of extrinsic variability.

Heinz Koeppl, Jakob Ruess, Christoph Zechner, 2017, The Journal of chemical physics.

Bayesian inference for stochastic individual-based models of ecological systems: a pest control simulation study

John Lygeros, Jakob Ruess, Francesca Parise, 2015, Front. Environ. Sci..

Enabling reactive microscopy with MicroMator

J. Ruess, F. Bertaux, Z. Fox, 2022, Nature Communications.

Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level

R. Chait, J. Ruess, A. Davidović, 2021, bioRxiv.

Minimal moment equations for stochastic models of biochemical reaction networks with partially finite state space.

Jakob Ruess, J. Ruess, 2015, The Journal of chemical physics.

Grey-box techniques for the identification of a controlled gene expression model

John Lygeros, Jakob Ruess, Francesca Parise, 2014, 2014 European Control Conference (ECC).

Approximating the solution of the chemical master equation by combining finite state projection and stochastic simulation

John Lygeros, Aron Hjartarson, Jakob Ruess, 2013, 52nd IEEE Conference on Decision and Control.

Iterative experiment design guides the characterization of a light-inducible gene expression circuit

John Lygeros, Jakob Ruess, Andreas Milias-Argeitis, 2015, Proceedings of the National Academy of Sciences.

Shaping bacterial population behavior through computer-interfaced control of individual cells

G. Tkačik, R. Chait, J. Ruess, 2017, Nature Communications.

Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks

Thomas A. Henzinger, Sergiy Bogomolov, Christian Schilling, 2015, CMSB.

Identifying stochastic biochemical networks from single-cell population experiments: A comparison of approaches based on the Fisher information

John Lygeros, Jakob Ruess, J. Lygeros, 2013, 52nd IEEE Conference on Decision and Control.

MicroMator: Open and Flexible Software for Reactive Microscopy

J. Ruess, F. Bertaux, Z. Fox, 2021, bioRxiv.

Bayesian filtering for model predictive control of stochastic gene expression in single cells

J. Ruess, Z. Fox, Grégory Batt, 2023, Physical biology.

Can optimal experimental design serve as a tool to characterize highly non-linear synthetic circuits?

Jakob Ruess, Gregory Batt, Arthur Carcano, 2019, 2019 18th European Control Conference (ECC).