Dr. Andreas Milias-Argeitis completed his MSc studies in electrical engineering with a focus on automatic control at the University of Patras, Greece. He subsequently worked on problems of computational systems biology during his PhD study at the Automatic Control Lab of ETH Zurich (degree obtained in 2013), and on experimental applications of optogenetics during his postdoctoral work at the Department of Biosystems Science and Engineering of ETH Zurich. In November 2016 he joined the GBB as a tenure-track assistant professor on computational biology. His research lies on the interface of mathematical modeling and biology. One of his primary theoretical interests has been the learning of dynamical models of biological networks from experimental data, an area that includes the problems of parameter inference, model selection/invalidation and inference of gene network structures. He has also worked on problems related to the analysis and efficient simulation of stochastic biochemical system models, and maintains a strong interest in the development of efficient and scalable uncertainty quantification methods for biochemical network models. On the experimental side, his work on optogenetic feedback control of gene expression in yeast and E. coli has received extensive media coverage as one of the first applications of sophisticated estimation and control techniques for regulating cellular behavior in real time. In his current work he aims to unravel the complex interplay between nutrient signaling and the cell cycle in yeast by creatively combining optogenetic, machine learning and control theory methods. This involves the design and application of targeted dynamic perturbations to the cells using single-cell optogenetic stimulation, an approach that can potentially extract more information on the system of interest compared to classical chemical and genetic perturbation.
Milias-Argeitis as junior scientist has published 20 peer-reviewed papers and has an h-index of 7 (Google Scholar) and 6 (Web of Science).
Three top publications 2010-2016
1. Milias-Argeitis A., M. Rullan Sabater, S.K. Aoki, P. Buchmann and M. Khammash (2016) Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth. Nature Communications 7: DOI:10.1038/ncomms12546
2. Milias-Argeitis A., A.P. Oliveira, L. Gerosa, L. Falter, U. Sauer and J. Lygeros (2016) Elucidation of genetic interactions in the yeast GATA-factor network using Bayesian model selection. PLoS Computational Biology 12 (3): DOI:10.1371/journal.pcbi.1004784
3. Milias-Argeitis A., S. Summers, J. Stewart-Ornstein, I. Zuleta, D. Pincus, H. ElSamad, M. Khammash, and J. Lygeros (2011) In silico feedback for in vivo regulation of a gene expression circuit. Nature Biotechnology 29 (12): 1114-1116. DOI:10.1038/nbt.201
|Last modified:||04 July 2017 10.12 a.m.|