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Over ons Praktische zaken Waar vindt u ons A. (Andreas) Milias Argeitis, Prof

Publicaties

Transfer Learning from Synthetic Data for Cell Segmentation and Tracking

Temporal segregation of biosynthetic processes is responsible for metabolic oscillations during the budding yeast cell cycle

A convolutional neural network for segmentation of yeast cells without manual training annotations

A user-friendly and streamlined protocol for CRISPR/Cas9 genome editing in budding yeast

Propagation of initial condition uncertainty for linear dynamical systems: Beyond the Gaussian assumption

Systematic In Vivo Characterization of Fluorescent Protein Maturation in Budding Yeast

The timing of Start is determined primarily by increased synthesis of the Cln3 activator rather than dilution of the Whi5 inhibitor

TORC1 and PKA activity towards ribosome biogenesis oscillates in synchrony with the budding yeast cell cycle

Moment-based uncertainty propagation for deterministic biochemical network models with rational reaction rates

Uncertainty propagation for deterministic models of biochemical networks using moment equations and the extended Kalman filter

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Pers/media

ENW Science-M grant for Andreas Milias Argeitis

Nineteen innovative research projects launched through Open Competition Domain Science-M programme

Negentien vernieuwende onderzoeksprojecten van start via Open Competitie ENW-M

Synthetische data versnellen onderzoek naar gist

Synthetic data speed up yeast research

Onderzoek naar de celcyclus van gistcellen naar hoger plan door Artificial Intelligence

Team iGEM Groningen 2020 wint gouden medaille

Studenten verjagen aardappelparasiet

Lage landen verdienen iGEM-prijzen

Instabiel eiwit is de hoofdschakelaar voor celdeling - Piek in eiwitproductie is startsignaal voor delingsproces

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