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A Comprehensive Computational Model to Simulate Transcription Factor Binding in Prokaryotes

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7223)

Abstract

Site specific transcription factors (TF) are proteins that orchestrate transcription by binding to specific target sites on the DNA. This binding can be both sequence- and conformation-specific. However, also non-specific binding with lower affinity can be observed [3]. The number of specific target sites is significantly smaller compared to the number of non-specific sites and, consequently, TF molecules bind, in a first instance, non-specifically to the DNA. Once bound to the DNA the TF molecules perform an one dimensional random walk on the DNA until they either find a target site or unbind from the DNA template. In particular, during the one dimensional random walk on the DNA, a molecule will perform one of the three types of movements: (i) sliding , (ii) hopping and (iii) jumping [6]. This combination of one and three dimensional diffusion is called facilitated diffusion and it is hypothesised that this speeds up the search process [3,2,5].

Keywords

  • Search Process
  • Specific Target Site
  • Downing Street
  • Physical Chemistry Chemical Physic
  • Ideal Entry Point

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Barnes, D.J., Chu, D.F.: An efficient model for investigating specific site binding of transcription factors. In: 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE), June 18-20, pp. 1–4. IEEE Xplore, Chengdu (2010)

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  4. Chu, D., Zabet, N.R., Mitavskiy, B.: Models of transcription factor binding: Sensitivity of activation functions to model assumptions. Journal of Theoretical Biology 257(3), 419–429 (2009)

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  5. Halford, S.E.: An end to 40 years of mistakes in dnaprotein association kinetics? Biochemical Society Transactions 37, 343–348 (2009)

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© 2012 Springer-Verlag Berlin Heidelberg

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Zabet, N.R., Adryan, B. (2012). A Comprehensive Computational Model to Simulate Transcription Factor Binding in Prokaryotes. In: Lones, M.A., Smith, S.L., Teichmann, S., Naef, F., Walker, J.A., Trefzer, M.A. (eds) Information Processign in Cells and Tissues. IPCAT 2012. Lecture Notes in Computer Science, vol 7223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28792-3_6

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  • DOI: https://doi.org/10.1007/978-3-642-28792-3_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28791-6

  • Online ISBN: 978-3-642-28792-3

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