Research
I am a biophysicist with background in mathematical modelling, scientific programming, and data analysis. I study the role of random effects and variability in the emergence of drug resistance in cancer. I build data analytic and visualisation pipelines for time series data from time-lapse fluorescent imaging and high-content screening.
Selected publications
M-A Jacques, M Dobrzyński, PA Gagliardi, R Sznitman, and O Pertz, “CODEX, a neural network approach to explore signaling dynamics landscapes”,
BioRxiv,
2020.
PA Gagliardi, M Dobrzyński, M-A Jacques, C Dessauges, RM Hughes, and O Pertz, “Collective ERK/Akt activity waves orchestrate epithelial homeostasis by driving apoptosis-induced survival”,
BioRxiv,
2020.
M Dobrzyński, M-A Jacques, and O Pertz, “Mining single-cell time-series datasets with Time Course Inspector”,
Bioinformatics,
2020.
Y Blum, J Mikelson, M Dobrzyński, et al., “Temporal perturbation of Erk dynamics reveals network architecture of FGF2-MAPK signaling,”
Mol Syst Biol 15:e8947,
2019.
H Ryu, M Chung, M Dobrzyński et al., “Frequency modulation of ERK activation dynamics rewires cell fate,”
Mol Syst Biol 11:838,
2015.
LK Nguyen, M Dobrzyński, D Fey, BK Kholodenko, “Polyubiquitin chain assembly and organization determine the dynamics of protein activation and degradation”,
Front Physiol,
2014.
M Dobrzyński et al., “Nonlinear signalling networks and cell-to-cell variability transform external signals into broadly distributed or bimodal responses”,
J R Soc Interface,
2014.
M Dobrzyński, D Fey, and L Nguyen, “Bimodal Protein Distributions in Heterogeneous Oscillating Systems”, in
Comp Meth in Syst Biol, 2012.
M Dobrzyński and FJ Bruggeman, “Elongation dynamics shape bursty transcription and translation”,
PNAS,
2009.
M Dobrzyński et al., “Computational methods for diffusion-influenced biochemical reactions”,
Bioinformatics,
2007.