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Tytuł artykułu

Coupled analytical and numerical approach to uncovering new regulatory mechanisms of intracellular processes

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Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper deals with the analysis of signaling pathways aimed at uncovering new regulatory processes regulating cell responses. First, general issues of comparing simulation and experimental data are discussed, and various aspects of data normalization are covered. Then, a model of a particular signaling pathway, induced by Interferon-\beta, is briefly introduced. It serves as an example illustrating how mathematical modeling can be used for inferring the structure of a regulatory system governing the dynamics of intracellular processes. In this pathway, experimental results suggest that a hitherto unknown process is responsible for a decrease in the levels of one of the important molecules used in the pathway. Then, equilibrium points of the model are analyzed, allowing the rejection of all but one explanation of the phenomena observed experimentally. Numerical simulations confirm that the model can mimic the dynamics of the processes in the pathway under consideration. Finally, some remarks about the applicability of the method based on an analysis of equilibrium points are made.
Rocznik
Strony
781--788
Opis fizyczny
Bibliogr. 15 poz., rys., tab., wykr.
Twórcy
autor
  • Institute of Automatic Control Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland, Jaroslaw.Smieja@polsl.pl
Bibliografia
  • Alexander, W. and Hilton, D. (2004). The role of suppressors of cytokine signaling (socs) proteins in regulation of the immune response, Annual Review of Immunology 22: 503-529.
  • Bekisz, J., Schmeisser, H., Hernandez, J., Goldman, N. and Zoon, K. (2004). Human interferons alpha, beta and omega, Growth Factors 22(4): 243-251.
  • Janeway, C. (2001). Immunobiology 5: The Immune System in Health and Disease, Garland Pub., New York, NY.
  • Ciliberto, A., Novak, B. and Tyson, J. (2005). Steady states and oscillations in the p53/mdm2 network, Cell Cycle 4: 488-493.
  • Levy, D.E. and Darnell Jr., J. (2002). Stats: Transcriptional control and biological impact, Nature Reviews Molecular Cell Biology 3: 651-662.
  • Kalvakolanu, D.V. (2003). Alternate interferon signaling pathways, Pharmacology & Therapeutics 100: 1-29.
  • Hoeve, J.D., 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.
  • Shuai, K. and Liu, B. (2003). Regulation of JAK-STAT signalling in the immune system, Nature Reviews Immunology 3: 900-911.
  • Pestka, S., Krause, C. and Walter, M. (2004). Interferons, interferon-like cytokines, and their receptors, Immunological Reviews 202: 8-32.
  • Sen, G. (2001). Viruses and interferons, Annual Review of Microbiology 55: 255-281.
  • Śmieja, J. (2009). Advantages and pitfalls of mathematical modelling used for validation of biological hypotheses, Proceedings of the 7th IFAC Symposium on Modelling and Control in Biomedical Systems 2009, Aalborg, Denmark, pp. 348-353.
  • Śmieja, J., Jamalludin, M., Brasier, A. and Kimmel, M. (2008). Model-based analysis of interferon-β induced signaling pathway, Bioinformatics 24(20): 2363-2369.
  • Lipniacki, T., Paszek, L., Brasier, P., Tian, A., Wang, B., H.-Q., Luxon, B. and Kimmel, M. (2006). Stochastic regulation in early immune response, Biophysical Journal 90: 725-742.
  • Wormald, S. and Hilton, D. (2004). Inhibitors of cytokine signal transduction, Journal of Biological Chemistry 279(2): 821-824.
  • Yamada, S., Shiono, S., Joo, A. and Yoshimura, A. (2003). Control mechanism of jak/stat signal transduction pathway, FEBS Letters 534: 190-196.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ1-0060-0027
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