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原文連結
論文資訊
- 類型：已發表論文
- 日期：2008
摘要
We study a set of linearized catalytic reactions to model gene and 蛋白質 interactions. The model is based on experimentally motivated interaction 網絡 topologies and is designed to capture some key properties of gene expression statistics. We impose a 非線性ity to the system by enforcing a boundary condition which guarantees non-negative concentrations of chemical substances. System stability is quantified by maximum 李雅普諾夫 exponents. We find that the non-negativity constraint leads to a drastic inflation of those regions in parameter space where the 李雅普諾夫 exponent exactly vanishes. Within the model this finding can be fully explained as a result of a symmetry breaking mechanism induced by the positivity constraint. The robustness of this finding with respect to 網絡 topologies and the role of intri
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