Andreas Milias-Argeitis
Andreas Milias-Argeitis
Associate Professor, University of Groningen
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
In silico feedback for in vivo regulation of a gene expression circuit
A Milias-Argeitis, S Summers, J Stewart-Ornstein, I Zuleta, D Pincus, ...
Nature biotechnology 29 (12), 1114-1116, 2011
Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth
A Milias-Argeitis, M Rullan, SK Aoki, P Buchmann, M Khammash
Nature communications 7 (1), 12546, 2016
An optogenetic platform for real-time, single-cell interrogation of stochastic transcriptional regulation
M Rullan, D Benzinger, GW Schmidt, A Milias-Argeitis, M Khammash
Molecular cell 70 (4), 745-756. e6, 2018
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
Differential scaling between G1 protein production and cell size dynamics promotes commitment to the cell division cycle in budding yeast
A Litsios, DHEW Huberts, HM Terpstra, P Guerra, A Schmidt, K Buczak, ...
Nature cell biology 21 (11), 1382-1392, 2019
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
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
Attaining mean square boundedness of a marginally stable stochastic linear system with a bounded control input
F Ramponi, D Chatterjee, A Milias-Argeitis, P Hokayem, J Lygeros
IEEE Transactions on Automatic Control 55 (10), 2414-2418, 2010
Stochastic dynamics of genetic networks: modelling and parameter identification
E Cinquemani, A Milias-Argeitis, S Summers, J Lygeros
Bioinformatics 24 (23), 2748-2754, 2008
Assessment of the interaction between the flux‐signaling metabolite fructose‐1, 6‐bisphosphate and the bacterial transcription factors CggR and Cra
B Bley Folly, AD Ortega, G Hubmann, S Bonsing‐Vedelaar, HJ Wijma, ...
Molecular Microbiology 109 (3), 278-290, 2018
Dynamic single-cell NAD(P)H measurement reveals oscillatory metabolism throughout the E. coli cell division cycle
Z Zhang, A Milias-Argeitis, M Heinemann
Scientific Reports 8 (1), 2162, 2018
Inference of the high-level interaction topology between the metabolic and cell-cycle oscillators from single-cell dynamics
S Özsezen, A Papagiannakis, H Chen, B Niebel, A Milias-Argeitis, ...
Cell systems 9 (4), 354-365. e6, 2019
Local identification of piecewise deterministic models of genetic networks
E Cinquemani, A Milias-Argeitis, S Summers, J Lygeros
Hybrid Systems: Computation and Control: 12th International Conference, HSCC …, 2009
Stochastic focusing coupled with negative feedback enables robust regulation in biochemical reaction networks
A Milias-Argeitis, S Engblom, P Bauer, M Khammash
Journal of The Royal Society Interface 12 (113), 20150831, 2015
TORC1 and PKA activity towards ribosome biogenesis oscillates in synchrony with the budding yeast cell cycle
P Guerra, LAPE Vuillemenot, YB van Oppen, M Been, A Milias-Argeitis
Journal of Cell Science 135 (18), jcs260378, 2022
Parameter inference for stochastic single-cell dynamics from lineage tree data
I Kuzmanovska, A Milias-Argeitis, J Mikelson, C Zechner, M Khammash
BMC systems biology 11, 1-13, 2017
Elucidation of genetic interactions in the yeast GATA-factor network using Bayesian model selection
A Milias-Argeitis, AP Oliveira, L Gerosa, L Falter, U Sauer, J Lygeros
PLoS computational biology 12 (3), e1004784, 2016
Dynamic disorder in simple enzymatic reactions induces stochastic amplification of substrate
A Gupta, A Milias-Argeitis, M Khammash
Journal of the Royal Society Interface 14 (132), 2017
Optimization-based Lyapunov function construction for continuous-time Markov chains with affine transition rates
A Milias-Argeitis, M Khammash
Proceedings of 53rd IEEE Conference on Decision and Control December 15-17 …, 2014
The timing of Start is determined primarily by increased synthesis of the Cln3 activator rather than dilution of the Whi5 inhibitor
A Litsios, P Goswami, HM Terpstra, C Coffin, LA Vuillemenot, M Rovetta, ...
Molecular biology of the cell 33 (5), rp2, 2022
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