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Model based analysis of signaling pathways

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper is concerned with application of mathematical modeling to the analysis of signaling pathways. Two issues, deterministic modeling of gene transcription and model-driven discovery of regulatory elements, are dealt with. First, the biological background is given and the importance of the stochastic nature of biological processes is addressed. The assumptions underlying deterministic modeling are presented. Special emphasis is put on describing gene transcription. A framework for including unknown processes activating gene transcription by means of first-order lag elements is introduced and discussed. Then, a particular interferon-ß induced pathway is introduced, limited to early events that precede activation of gene transcription. It is shown how to simplify the system description based on the goals of modeling. Further, a computational analysis is presented, facilitating better understanding of the mechanisms underlying regulation of key components in the pathway. The analysis is illustrated by a comparison of simulation and experimental data.
Rocznik
Strony
139--145
Opis fizyczny
Bibliogr. 20 poz., rys., wykr.
Twórcy
autor
  • Institute of Automatic Control, Silesian University of Technology, ul. Akademicka 16, 44–100 Gliwice, Poland, Jaroslaw.Smieja@polsl.pl
Bibliografia
  • [1] Alexander W.S. and Hilton,D.J. (2004). The role of suppressors of cytokine signaling (SOCS) proteins in regulation of the immune response, Annual Review of Immunology 22: 503-529.
  • [2] Godfrey K. (1983). Compartmental Models and Their Application, Academic Press, London.
  • [3] Heinrich P.C., Behrmann I., Haan S., Hermanns H.M., Mueller-Newen G. and Schaper F. (2003). Principles of interleukin (IL)-6-type cytokine signalling and its regulation, Biochemical Journal 374: 1-20.
  • [4] Hoeve J.M. de, Ibarra-Sanchez J., Fu Y., Zhu W., Tremblay M., David M. and Shuai K. (2002). Identification of a nuclear Stat1 protein tyrosine phosphatase, Molecular and Cellular Biology 22(16): 5662-5668.
  • [5] Janeway C. (2001). Immunobiology 5: The Immune System in Health and Disease, Garland, New York.
  • [6] Kalvakolanu D.V. (2003). Alternate interferon signaling pathways, Pharmacology & Therapeutics 100: 1-29.
  • [7] Levy D.E. and J. Darnell Jr. (2002). STATs: Transcriptional control and biological impact, Nature Reviews Molecular Cell Biology 3: 651-662.
  • [8] Lipniacki T., P. Paszek, A.R. Brasier, B. Tian, H.-Q. Wang, B.Luxon and M. Kimmel (2006). Stochastic regulation in early immune response, Biophysical Journal 90: 725-742.
  • [9] Paszek P., T. Lipniacki, A.R. Brasier, B. Tian, D.E. Nowak and M. Kimmel (2005). Stochastic effects of multiple regulators on expression profiles in eukaryotes, Journal of Theoretical Biology 233(3): 423-433.
  • [10] Pestka, S., Krause, C.D. and Walter, M.R. (2004). Interferons, interferon-like cytokines, and their receptors, Immunological Reviews 202: 8-32.
  • [11] Segel L.A. (Ed.) (1991). Biological Kinetics, Cambridge University Press, Cambridge.
  • [12] Sen G.C. (2001). Viruses and interferons, Annual Review of Microbiology 55: 255-281.
  • [13] Shuai K. and B. Liu (2003). Regulation of JAK-STAT signalling in the immune system, Nature Reviews Immunology 3: 900-911.
  • [14] Śmieja, J., Jamalludin, M., Brasier, A. and Kimmel, M. (2006). Deterministic modeling of interferon-beta signaling pathway, Procedings of the 6th IFAC Symposium on Modelling and Control in Biomedical Systems MCBMS'06, Reims,France, pp. 423-428.
  • [15] Taniguchi T. and A. Takaoka (2001). A weak signal for strong responses: Interferon-α/β revisited, Nature Reviews Molecular Cell Biology 2: 378-386.
  • [16] Tyson J.J., K.C. Chen and B. Novak (2003). Sniffers, buzzers, toggles and blinkers: Dynamics of regulatory and signaling pathways in the cell, Current Opinion in Cell Biology 15: 221-231.
  • [17] Vinkemeier U., S.L.Cohen, I. Moarefi, B.T.Chait, J. Kuriyan and J.E. Darnell Jr. (1996). DNA binding of in vitro activated Stat1α, Stat1β and truncated Stat1: Interaction between NH2-terminal domains stabilizes binding of two dimers to tandem DNA sites. EMBO Journal 15(20): 5616-5626.
  • [18] Wormald, S. and Hilton, D.J. (2004). Inhibitors of cytokine signal transduction, Journal of Biological Chemistry, 279(2): 821-824,
  • [19] Yamada S., S. Shiono, A. Joo and A. Yoshimura (2003). Control mechanism of JAK/STAT signal transduction pathway, FEBS Letters 534: 190-196.
  • [20] Zi Z., K.-H. Cho, M.-H. Sung, X. Xia, J. Zheng and Z. Sun (2005). In silico identification of the key components and steps in IFN-γ induced JAK-STAT signaling pathway, FEBS Letters 579: 1101-1108.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ1-0044-0013
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