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Spatiotemporal modelling of DNA replication (jointly with IBM Research Zurich)



John Lygeros, Maria Anna Rapsomaniki

DNA replication, the duplication of a cell’s genetic material, ensures the maintenance of the genetic information and is the basis of biological inheritance. In eukaryotic cells, DNA replication initiates at multiple locations in the genome, known as origins of replication, and continues from there in both directions creating replication forks.
This project aims at developing a stochastic hybrid model of DNA replication that incorporates spatial information on origin locations and protein mobility dynamics. The ultimate goal is to understand the relationship between 3D structure and DNA replication. The model will be tailored for the case of fission yeast using recent experimental data and will be simulated in a high-performance computing set-up. The research will be conducted in collaboration between the Automatic Control Laboratory of ETH Zurich and IBM Research Zurich. More specifically, the project will involve:

• adapting an existing model of protein mobility (Cinquemani et al., 2008, Rapsomaniki et al., 2015) for the case of fission yeast nucleus and model origin locations in 3D using experimental data.
• integrating the origin location and existing DNA replication models (Lygeros et al., PNAS, 2008) to enable stochastic initiation of origin firing when activation factors diffuse and bind onto the origins.
• simulating the resulting integrated model to test various hypotheses, for example different kinetic parameters of the activation factors or different relative positioning of the origins.
• examining if and how relative origin positioning affects replication timing and how the process is affected by the dynamics of activation factors.

For more information please contact J. Lygeros ( and M. Rapsomaniki (

E. Cinquemani, V. Roukos, Z. Lygerou, and L. Lygeros, "Numerical analysis of FRAP experiments for DNA replication and repair," in IEEE Conference on Decision and Control, Cancun, Mexico, December 9-11, 2008.

M. Rapsomaniki, E. Cinquemani, N. Giakoumakis, P. Kotsantis, J. Lygeros, and Z. Lygerou, "Inference of protein kinetics by stochastic modeling and simulation of fuorescence recovery after photobleaching experiments," Bioinformatics, vol. 31, no. 3, pp. 355-362, 2015.

J. Lygeros, K. Koutroumpas, S. Dimopoulos, I. Legouras, P. Kouretas, C. Heichinger, P. Nurse, and Z. Lygerou, "Stochastic hybrid modeling of DNA replication across a complete genome," Proceedings of the National Academy of Sciences of the U.S.A., vol. 105, pp. 12295-12300, August 2008.

Weitere Informationen

John Lygeros

Art der Arbeit: 50% theory-50% computation
Anzahl StudentInnen: 1
Status: open
Projektstart: as doon as possible
Semester: 1