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DAAD: Systems Biology of Mitosis

The cell cycle is controlled by a highly complex bio-chemical system. In this project we investigate the mitotic transition control mechanisms. In order to capture their complexity on a systems level, we apply mathematical and computational methods.


The growth of all organisms requires that the genome is accurately replicated and equally partitioned between two cellular progenies. In eukaryotes, the duplication of chromosomes, the separation of sister chromatids, and their segregation to opposite poles of the cell prior to cytokinesis are features of the cell cycle and grant maintenance of genomic integrity. Eukaryotic cells have evolved a surveillance mechanism for DNA segregation, the Mtotic Spindle Assembly Checkpoint (MSAC). This checkpoint blocks anaphase onset and prevents exit from mitosis until all chromosomes are properly attached and have aligned on the mitotic spindle. Its malfunction leads to cell death, generates aneuploidy, might facilitate tumorgenesis and aging , and might contribute to cancer.

The research focuses on modeling and simulation of the human's mitosis transition controls, the MSAC and the mitotic exit. Our modeling approaches base on biochemical reaction networks. We use In particular: Differential equations, stochastic simulation, evolutionary optimization, and three dimensional effects.

 The MSAC, is the major cell cycle control mechanism in mitosis. It delays the transition from metaphase to anaphase until all chromosomes are correctly aligned at the metaphase spindle equator. In early metaphase, the chromosomes are not attached to the spindle of microtubules, while in late metaphase most chromosomes are attached. Once all kinetochores are attached, anaphase initiation is rapid. The subscript n denotes the number of chromosomes (e.g. n = 46 for human)


Peer-reviewed articles in international journals

_caydasi2010 Ayse Koca Caydasi, Bahtiyar Kurtulmus, Maria I.L. Orrico, Astrid Hofmann, Bashar Ibrahim, Gislene Pereira (2010)
Elm1 kinase activates the spindle position checkpoint kinase Kin4.
J. Cell Biol., 190(6):975-989
Comment in: Leslie , M. (2010) Elm1 sparks the SPOC, J. Cell Biol., 190 (6): 944.

Gerd Gr√ľnert, Bashar Ibrahim, Thorsten Lenser, Maiko Lohel, Thomas Hinze, Peter Dittrich (2010)
Rule-based spatial modeling with diffusing, geometrically constrained molecules
BMC Bioinformatics, 11:307

Maiko Lohel, Bashar Ibrahim, Stephan Diekmann, Peter Dittrich (2009)
The role of localization in the operation of the mitotic spindle assembly checkpoint
Cell Cycle 8(16), 2009

_ibrahim2009 Bashar Ibrahim, Eberhard Schmitt, Peter Dittrich, Stephan Diekmann (2009)
In-silico study of kinetochore control, amplification, and inhibition effects in MCC assembly
Biosystems, 95(1), 35-50.

_ibrahim2008 Bashar Ibrahim, Peter Dittrich, Stephan Diekmann, Eberhard Schmidt (2008)
Mad2 binding is not sufficient for complete Cdc20 sequestering in mitotic transition control (an in silico study)
Biophysical Chemistry, 134(1-2), 93-100, 2008

Bashar Ibrahim, Peter Dittrich, Stephan Diekmann, Eberhard Schmidt (2007)
Stochastic effects in a compartmental model for mitotic checkpoint regulation
Journal of Integrative Bioinformatics, 4(3), 66, 2007
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Peer-reviewed articles in proceedings

Hendrik Rohn, Bashar Ibrahim, Thorsten Lenser, Thomas Hinze, Peter Dittrich (2008)
Enhancing Parameter Estimation of Biochemical Networks by Exponentially Scaled Search Steps
In: E. Marchiori, J.H. Moore (Eds.), Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, Proceedings EvoBio 2008, Naples, Series Lecture Notes in Computer Science, Vol. 4973, pp. 177-187, Springer Verlag, 2008

Thorsten Lenser, Thomas Hinze, Bashar Ibrahim, Peter Dittrich (2007)
Towards Evolutionary Network Reconstruction Tools for Systems Biology
In: E. Marchiori, J.H. Moore, J.C. Rajapakse (Eds.), Proceedings EvoBio 2007, Valencia, Series Lecture Notes in Computer Science, Vol. 4447, pp. 132-142, Springer Verlag, 2007

For pdf or update see publications of the Group page