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This article investigates the regulatory nonlinearity in biological networks by analyzing 137 Boolean network models. The findings suggest that biological regulation is generally less nonlinear than expected, indicating a potential evolutionary preference for linear regulation, while cancer networks exhibit greater variability and nonlinearity. This research has implications for understanding biological control mechanisms and developing therapeutic strategies in biomedicine.

Author

nd1706

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EN