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.

 

 

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.