Continuous surrogates versus threshold Boolean networks for modeling Arabidopsis ISR gene regulation

Gene regulatory network modeling often requires balancing predictive accuracy and mechanistic interpretability. In this work, we compare continuous surrogate models and a discrete mechanistic model on the same \textit{Arabidopsis thaliana} induced systemic resistance (ISR) dataset, using both the raw continuous gene-expression measurements and their sign-binarized representation. The study considers eight defense-related genes measured over nine time points and evaluates two continuous predictor

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ethics.ai (25 July 2026), “Continuous surrogates versus threshold Boolean networks for modeling Arabidopsis ISR gene regulation,” evidence record 14497, https://ethics.ai/record/14497 (originally published by arXiv cs.LG).

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