### An Overview on Computational Approaches to Modeling Mammalian Cell Cycle

#### Abstract

Biological systems such as cell cycle are “complex systems “consisting of an enormous number of elements interacting in ways that produce nonlinear and complex systems behavior. Computational modelling a promising approach to study such systems. However, representing structural and functional complexity of these systems is a major challenge to these models that can range from simpler discrete models such as Boolean networks to more complex mathematical model. Modeling methods and techniques have become popular for modeling biological systems because they can provide a deep understanding and insight of the complex biological system issues. These techniques can also be used in prediction, diagnosis and treatment of diseases such as cancer.

This paper overlays current and existing computational modeling approaches used in modeling mammalian cell cycle (discrete, continuous, stochastic and hybrid). In addition, it introduces a set of opened research questions related to cell cycle system. Furthermore, this paper exposes the pros and cons of the existing modelling approaches and presents a more flexible and intuitive fuzzy logic based system framework to modeling cell cycle system.

#### Keywords

#### Full Text:

PDF#### References

Aguda, B. and Y. Tang (1999). "The kinetic origins of the restriction point in the mammalian cell cycle." Cell proliferation 32(5): 321-335.

Albert, R. and H. G. Othmer (2003). "The topology of the regulatory interactions predicts the expression pattern of the segment polarity genes in Drosophila melanogaster." J Theor Biol 223(1): 1-18.

Alberts, B., et al. (2002). "Molecular Biology of the Cell Taylor & Francis." New York.

Alfieri, R., et al. (2009). "Towards a systems biology approach to mammalian cell cycle: modeling the entrance into S phase of quiescent fibroblasts after serum stimulation." BMC bioinformatics 10(12): 1.

Bean, J. M., et al. (2006). "Coherence and timing of cell cycle start examined at single-cell resolution." Molecular cell 21(1): 3-14.

Behaegel, J., et al. (2015). "A hybrid model of cell cycle in mammals." Journal of bioinformatics and computational biology: 1640001.

Behl, C. and C. Ziegler (2014). "Cell Aging: Molecular Mechanisms and Implications for."

Behl, C. and C. Ziegler (2014). Cell Cycle: The Life Cycle of a Cell. Cell Aging: Molecular Mechanisms and Implications for Disease, Springer: 9-19.

Braunewell, S. and S. Bornholdt (2007). "Superstability of the yeast cell-cycle dynamics: ensuring causality in the presence of biochemical stochasticity." J Theor Biol 245(4): 638-643.

Chen, K. C., et al. (2004). "Integrative analysis of cell cycle control in budding yeast." Molecular biology of the cell 15(8): 3841-3862.

Chiorino, G. and M. Lupi (2002). "Variability in the timing of G 1/S transition." Mathematical Biosciences 177: 85-101.

Csikász-Nagy, A. (2009). "Computational systems biology of the cell cycle." Briefings in Bioinformatics 10(4): 424-434.

Davidich, M. I. and S. Bornholdt (2008). "Boolean network model predicts cell cycle sequence of fission yeast." PloS one 3(2): e1672.

Fauré, A., et al. (2006). "Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle." Bioinformatics 22(14): e124-e131.

Ferrell, J. E., et al. (2011). "Modeling the cell cycle: why do certain circuits oscillate?" cell 144(6): 874-885.

Florens, L., et al. (2002). "A proteomic view of the Plasmodium falciparum life cycle." Nature 419(6906): 520-526.

Gérard, C. and A. Goldbeter (2012). "The cell cycle is a limit cycle." Mathematical Modelling of Natural Phenomena 7(06): 126-166.

Gérard, C. and A. Goldbeter (2012). "Entrainment of the mammalian cell cycle by the circadian clock: modeling two coupled cellular rhythms." PLoS Comput Biol 8(5): e1002516.

Gilbert, D. (1974). "The nature of the cell cycle and the control of cell proliferation." Biosystems 5(4): 197-206.

Glass, L. and S. A. Kauffman (1973). "The logical analysis of continuous, non-linear biochemical control networks." J Theor Biol 39(1): 103-129.

Hanahan, D. and R. A. Weinberg (2000). "The hallmarks of cancer." cell 100(1): 57-70.

Hay, E. D. (1991). Collagen and other matrix glycoproteins in embryogenesis. Cell biology of extracellular matrix, Springer: 419-462.

Huang, S. (1999). "Gene expression profiling, genetic networks, and cellular states: an integrating concept for tumorigenesis and drug discovery." Journal of Molecular Medicine 77(6): 469-480.

Irons, D. (2009). "Logical analysis of the budding yeast cell cycle." J Theor Biol 257(4): 543-559.

Iwamoto, K., et al. (2011). "Mathematical modeling of cell cycle regulation in response to DNA damage: exploring mechanisms of cell-fate determination." Biosystems 103(3): 384-391.

Kapuy, O., et al. (2009). "Mitotic exit in mammalian cells." Molecular systems biology 5(1): 324.

Kar, S., et al. (2009). "Exploring the roles of noise in the eukaryotic cell cycle." Proceedings of the National Academy of Sciences 106(16): 6471-6476.

Knoblauch, M., et al. (1999). "A galinstan expansion femtosyringe for microinjection of eukaryotic organelles and prokaryotes." Nature biotechnology 17(9): 906-909.

Kohn, K. W. (1998). "Functional capabilities of molecular network components controlling the mammalian G1/S cell cycle phase transition." Oncogene 16(8): 1065-1075.

Kumar, A. (2007). Fausto, and Mitchell, Basic Pathology, PA, USA: Saunders, Elsevier.

Li, F., et al. (2004). "The yeast cell-cycle network is robustly designed." Proceedings of the National Academy of Sciences of the United States of America 101(14): 4781-4786.

Ling, H., et al. (2010). "Robustness of G1/S checkpoint pathways in cell cycle regulation based on probability of DNA-damaged cells passing as healthy cells." Biosystems 101(3): 213-221.

Noel, V., et al. (2012). "Hybrid models of the cell cycle molecular machinery." arXiv preprint arXiv:1208.3854.

Noël, V., et al. (2013). "A hybrid mammalian cell cycle model." arXiv preprint arXiv:1309.0870.

Novak, B. and J. J. Tyson (1993). "Numerical analysis of a comprehensive model of M-phase control in Xenopus oocyte extracts and intact embryos." Journal of cell science 106(4): 1153-1168.

Novak, B. and J. J. Tyson (2004). "A model for restriction point control of the mammalian cell cycle." J Theor Biol 230(4): 563-579.

O'connor, P. (1996). "Mammalian G1 and G2 phase checkpoints." Cancer surveys 29: 151-182.

Orlando, D. A., et al. (2008). "Global control of cell-cycle transcription by coupled CDK and network oscillators." Nature 453(7197): 944-947.

Sahin, Ö., et al. (2009). "Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance." BMC systems biology 3(1): 1.

Sel'kov, E. (1969). "[2 alternative autooscillatory stationary states in thiol metabolism--2 alternative types of cell multiplication: normal and neoplastic]." Biofizika 15(6): 1065-1073.

Singhania, R., et al. (2011). "A hybrid model of mammalian cell cycle regulation." PLoS Comput Biol 7(2): e1001077.

Srividhya, J. and M. Gopinathan (2006). "A simple time delay model for eukaryotic cell cycle." J Theor Biol 241(3): 617-627.

Steuer, R. (2004). "Effects of stochasticity in models of the cell cycle: from quantized cycle times to noise-induced oscillations." J Theor Biol 228(3): 293-301.

Thomas, R. (1973). "Boolean formalisation of genetic control circuits." J Theor Biol 42: 565–583.

Weis, M. C., et al. (2014). "A data-driven, mathematical model of mammalian cell cycle regulation." PloS one 9(5): e97130.

Wille, J. J., et al. (1984). "Integrated control of growth and differentiation of normal human prokeratinocytes cultured in serum‐free medium: Clonal analyses, growth kinetics, and cell cycle studies." Journal of cellular physiology 121(1): 31-44.

Wolkenhauer, O., et al. (2004). "Modeling and simulation of intracellular dynamics: choosing an appropriate framework." NanoBioscience, IEEE Transactions on 3(3): 200-207.

Yao, G., et al. (2008). "A bistable Rb–E2F switch underlies the restriction point." Nature cell biology 10(4): 476-482.

Zámborszky, J., et al. (2007). "Computational analysis of mammalian cell division gated by a circadian clock: quantized cell cycles and cell size control." Journal of biological rhythms 22(6): 542-553.

Zhang, L., et al. (2013). "A mathematical analysis of DNA damage induced G2 phase transition." Applied Mathematics and Computation 225: 765-774.

Zhang, Y., et al. (2006). "Stochastic model of yeast cell-cycle network." Physica D: Nonlinear Phenomena 219(1): 35-39.

### Refbacks

- There are currently no refbacks.

Copyright (c) 2019 Mohammad Abdallah Alsharaiah, Mutaz Khazaaleh, Rana Shaher Soliman

This work is licensed under a Creative Commons Attribution 4.0 International License.