Abstract
An electrical network model is designed to represent the central dogma of molecular biology and simulate the response to study the behaviors of bacteria gene E. coli. The transcription and translation processes of a biological system are represented by differential equations. These equations are mapped into electrical domain, and an equivalent electrical circuit is realized. The electrical response of circuit is simulated in SPICE domain, and result shows the structural and repressor protein behaves like a toggle switch which truly matches with biological system.
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References
J. Hasty, D. McMillen, Engineered gene circuits. Nature 224–230 (2002). doi:10.1038/nature01257
M. Kaern, W.J. Blake, J.J. Collins, The engineering of gene regulatory networks. Annu. Rev. Biomed. Eng. 179–206 (2003). doi:10.1146/annurev.bioeng.5.040202.121553
F. Jacob, J. Monod, On the regulations of gene activity, in Symposium on Cellular Regulatory Mechanisms (Cold Spring Harbor laboratory, New York, 1961), pp 193–211
A. Becskei, Luis Serrano, Engineering stability in gene networks by autoregulation. Nature 405, 590–593 (2000)
M.B. Elowitz, S. Leibler, A synthetic oscillatory network of transcriptional regulators. Nature 403, 335–338 (2000)
S. Gardner, C.R. Cantor, J.J. Collins, Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339–342 (2000)
N.E. Buchler, U. Gerland, T. Hwa, Nonlinear protein degradation and the function of genetic circuits. Proc. Natl. Acad. Sci. U S A. 102, 9559–9564 (2005)
H. De Jong, Modeling and simulation of genetic regulatory systems: a literature review. J. Comput. Biol. 67–103 (2002)
H. Kim, E. Gelenbe, Stochastic gene expression modeling with hill function for switch-like gene responses. IEEE Transac. Comput. Biol. Bioinform. 9(X), 973–979 (2012)
H.H. McAdams, A. Arkin, Stochastic mechanisms in gene expression. Proc. Natl. Acad. Sci., USA 94, 814–819 (1997)
T. Chen, H.L. He, Modeling gene expression with differential equations, in Pacific Symposium of Biocomputing (1999), pp. 17–28
H.H. McAdams, A. Arkin, Stochastic mechanisms in gene expression. Proc. Natl. Acad. Sci. 94, 814–819 (1997)
I. Shmulevich et al., Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks. Bioinformatics 18, 261–274 (2002)
C. Ferreira, in Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence, vol 21, (Springer, 2006)
G. Bernot, et al., Modeling and analysis of gene regulatory networks, in Modeling in Computational Biology and Biomedicine, (Springer, Berlin, Heidelberg, 2013), pp. 47–80
S. Paul, D.A. Baxter, J.H. Byrne, Mathematical modeling of gene networks. Neuron 26, 567–580 (2000)
N.R. Zabet, A.N.W. Hone, D.F. Chu, Design principles of transcriptional logic circuits. ALIFE, (2010), pp. 186–194
J.L. Hargrove, F.H. Schmidt, The role of mRNA and protein stability in gene expression. FASEB J. 3, 2360–2370 (1989)
Acknowledgements
The authors wish to thank DST, Science and Engineering Research Board (SERB/F/4504/2013–2014), Govt. of India for funding support of research work.
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Dutta, M., Barman, S. (2018). Electrical Equivalent Model for Gene Regulatory System. In: Nath, V. (eds) Proceedings of the International Conference on Microelectronics, Computing & Communication Systems. Lecture Notes in Electrical Engineering, vol 453. Springer, Singapore. https://doi.org/10.1007/978-981-10-5565-2_14
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DOI: https://doi.org/10.1007/978-981-10-5565-2_14
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