MBI Publications

MBI Publications for Yunjiao Wang (8)

  • D. Turner, P. Paszek, D. Woodcock, D. Nelso, C. Horton, Y. Wang, D. Spiller, D. Rand, M. White and C. Harper
    Physiological levels of TNFalpha stimulation induce stochastic dynamics of NF-kappaB responses in single living cells.
    Journal of Cell BiologyVol. 123 No. 16 (2010) pp. p.p 2834-2843


    Nuclear factor kappa B (NF-?ºB) signalling is activated by cellular stress and inflammation and regulates cytokine expression. We applied single-cell imaging to investigate dynamic responses to different doses of tumour necrosis factor alpha (TNF?±). Lower doses activated fewer cells and those responding showed an increasingly variable delay in the initial NF-?ºB nuclear translocation and associated I?ºB?± degradation. Robust 100 minute nuclear:cytoplasmic NF-?ºB oscillations were observed over a wide range of TNF?± concentrations. The result is supported by computational analyses, which identified a limit cycle in the system with a stable 100 minute period over a range of stimuli, and indicated no co-operativity in the pathway activation. These results suggest that a stochastic threshold controls functional all-or-nothing responses in individual cells. Deterministic and stochastic models simulated the experimentally observed activation threshold and gave rise to new predictions about the structure of the system and open the way for better mechanistic understanding of physiological TNF?± activation of inflammatory responses in cells and tissues.
  • M. Leite and Y. Wang
    Multistability, Oscillations and Bifurcations in Feedback Loops.
    Math. Biosci. EngVol. 7 No. 1 (2010) pp. 83-97


    Feedback loops are found to be important network structures in

    regulatory networks of biological signaling systems because they are responsi-

    ble for maintaining normal cellular activity. Recently, the functions of feedback

    loops have received extensive attention. The existing results in the literature

    mainly focus on verifying that negative feedback loops are responsible for oscil-

    lations, positive feedback loops for multistability, and coupled feedback loops

    for the combined dynamics observed in their individual loops. In this work,

    we develop a general framework for studying systematically functions of feed-

    back loops networks. We investigate the general dynamics of all networks with

    one to three nodes and one to two feedback loops. Interestingly, our results

    are consistent with Thomasâ?? conjectures although we assume each node in the

    network undergoes a decay, which corresponds to a negative loop in Thomasâ??

    setting. Besides studying how network structures influence dynamics at the

    linear level, we explore the possibility of network structures having impact on

    the nonlinear dynamical behavior by using Lyapunov-Schmidt reduction and

    singularity theory.
  • M. Golubitsky, D. Romano and Y. Wang
    Network periodic solutions: full oscillation and rigid synchrony
    NonlinearityVol. 23 (2010) pp. 3227-3243


  • Y. Wang, P. Paszek, C. Horton, D. Kell, M. White, D. Broomhead and M. Muldoon
    Interactions among oscillatory pathways in NF- kB signalling
    BMC Systems BiologyVol. 5 No. 23 (2011)


    Sustained stimulation with tumour necrosis factor alpha (TNF-alpha) induces substantial oscillationsâ???observed at both the single cell and population levelsâ???in the nuclear factor kappa B (NF-kappa B) system. Although the mechanism has not yet been elucidated fully, a core system has been identified consisting of a negative feedback loop involving NF-kappa B (RelA:p50 hetero-dimer) and its inhibitor I-kappa B-alpha. Many authors have suggested that this core oscillator should couple to other oscillatory pathways.
  • M. Golubitsky, D. Romano and Y. Wang
    Network periodic solutions: patterns of phase-shift synchrony
    NonlinearityVol. 25 (2012) pp. 1045-1074


  • Y. Wang, P. Paszek, C. Horton, H. Yue, M. White, D. Kell, M. Muldoon, M. Muldoon and D. Broomhead
    A systematic study of the response of a NF-kB signalling pathway to TNFalpha stimulation.
    Journal of Theoretical BiololgyVol. 297 (2012) pp. 137-147


  • Y. Wang, T. McMillen, M. Golubitsky and C. Diekman
    Reduction and dynamics of a generalized rivalry network with two learned patterns
    SIAM Journal of Applied Dynamical SystemsVol. 11 (2012) pp. 1270-1309


    We use the theory of coupled cell systems to analyze a neuronal network model for generalized rivalry posed by H. Wilson. We focus on the case of rivalry between two patterns and identify conditions under which large networks of n attributes and m intensity levels can reduce to a model consisting of two or three cells depending on whether or not the patterns have any attribute levels in common. (The two-cell reduction is equivalent to certain recent models of binocular rivalry.) Notably, these reductions can lead to large recurrent excitation in the reduced network even though the individual cells in the original network may have none. We also show that symmetry-breaking Takens??Bogdanov (TB) bifurcations occur in the reduced networks, and this allows us to further reduce much of the dynamics to a planar system. We analyze the dynamics of the quotient systems near the TB singularity, discussing how variation of the input parameter I organizes the dynamics. This variation leads to a degenerate path through the unfolding of the TB point. We also discuss how the network structure affects recurrent excitation in the reduced networks, and the consequences for the dynamics.
  • C. Diekman, M. Golubitsky and Y. Wang
    Derived patterns in binocular rivalry networks.
    Journal of mathematical neuroscienceVol. 3 No. 1 (2013) pp. 6


    Binocular rivalry is the alternation in visual perception that can occur when the two eyes are presented with different images. Wilson proposed a class of neuronal network models that generalize rivalry to multiple competing patterns. The networks are assumed to have learned several patterns, and rivalry is identified with time periodic states that have periods of dominance of different patterns. Here, we show that these networks can also support patterns that were not learned, which we call derived. This is important because there is evidence for perception of derived patterns in the binocular rivalry experiments of Kovács, Papathomas, Yang, and Fehér. We construct modified Wilson networks for these experiments and use symmetry breaking to make predictions regarding states that a subject might perceive. Specifically, we modify the networks to include lateral coupling, which is inspired by the known structure of the primary visual cortex. The modified network models make expected the surprising outcomes observed in these experiments.

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