I am a PhD student supervised by Professor Michael Stumpf. I obtained a BSc in Molecular Bionics (in 2012) followed by an MSc in Infobionics (2013), both from the Faculty of Information Technology and Bionics, PPCU, Hungary.
During my previous projects I have tackled different aspects of the intramuscular actin-myosin interaction (through simulations of the cytokinetic ring and AFM studies on vertebrate thick filaments) and worked on a recent model of the blood glucose control system.
My PhD focuses on cellular decision making processes with respect to noise in signalling pathways. In particular, my aim is to investigate various aspects of how noise can alter, challenge or help major decisions cells has to take during their lifetime. To do so I start from simplified biochemical models of crucial network components, conduct in silico experiments and study the stochasticity of the system.
I use a variety of stochastic modelling tools to obtain the population-level dynamics of the models, and combine these methods with frameworks including inference, distribution reconstruction and control design. I apply my techniques on the p53 tumour suppressor protein, and Nanog and Oct4-Sox2 contributing to stem cell dynamics.
Outside research I spend most of my time (i) all round town on my beloved red bike, (ii) in the kitchen experimenting with new dishes and (iii) singing with the London International Gospel Choir.
Publications and Conferences
Control mechanisms for stochastic biochemical systems via computation of reachable sets
Lakatos E, Stumpf MP.
bioRxiv 079723; doi: https://doi.org/10.1101/079723
MEANS: python package for Moment Expansion Approximation, iNference and Simulation.
Fan* S, Geissmann* Q, Lakatos* E, Lukauskas* S, Ale A, Babtie AC, Kirk PD, Stumpf MP.
Bioinformatics. 2016 Sep 15;32(18):2863-5. doi: 10.1093/bioinformatics/btw229.
Multivariate moment closure techniques for stochastic kinetic models.
Lakatos E, Ale A, Kirk PD, Stumpf MP.
J Chem Phys. 2015 Sep 7;143(9):094107. doi: 10.1063/1.4929837.
E. Lakatos and M. P. H. Stumpf: Reachable state set computation of stochastic biological systems; 5th Student Conference on Complexity Sciences, Granada, Spain, September 9-11, 2015
E. Lakatos and M. P. H. Stumpf: Reachable state set computation of stochastic biological systems with controlled input and uncertainty; 25th Annual MASAMB (Mathematical and Statistical Aspects of Molecular Biology) Workshop, Helsinki, Finland, April 16-17, 2015
E. Lakatos, P. Kirk and M. P. H. Stumpf: Multivariate moment closure techniques for stochastic kinetic models; 11th International Workshop on Computation Systems Biology, Lisbon, Portugal, May 15-16, 2014
D. Meszena, E. Lakatos and G. Szederkenyi: Sensitivity analysis and parameter estimation of a human blood glucose regulatory system model; 11th International Workshop on Computation Systems Biology, Lisbon, Portugal, May 15-16, 2014
E. Lakatos, D. Meszena and G. Szederkenyi: Identifiablity analysis and improved parameter estimation of a human blood glucose control system model; Computational Methods in Systems Biology, 11th International Conference, Klosterneuburg, Austria, September 22-24, 2013. Proceedings
E. Lakatos, B. Decker and M. S. Z. Kellermayer: High-resolution structure and actin-binding of synthetic myosin thick filaments; From Medicine to Bionics, 1st European PhD Congress, Budapest, Hungary, June 13-15, 2013
E. Lakatos, B. Decker and M. S. Z. Kellermayer: Szintetikus miozin vastag filamentumok nagyfelbontású szerkezete és aktinkötése; 43. Membrán-transzport konferencia, Sümeg, Hungary, May 21-24, 2013
B. Decker, E. Lakatos and M. S. Z. Kellermayer: Structure of synthetic vertebrate myosin thick filaments explored with high-resolution AFM; Biophysical Society, 57th Annual Meeting, Philadelphia, Pennsylvania, US, February 2-6, 2013