Enhanced Predictive Modeling of Salicylic Acid and Jasmonic Acid Crosstalk in *Arabidopsis thaliana* Using Multi-Modal Data Fusion and Bayesian Optimization

**Abstract:** This paper presents a novel approach to modeling the intricate crosstalk between salicylic acid (SA) and jasmonic acid (JA) signaling pathways in *Arabidopsis thaliana*. Traditional models often struggle to capture the dynamic complexity of this interaction, which necessitates a holistic approach incorporating various data modalities. Our method, leveraging a hierarchical Bayesian optimization framework with multi-modal data fusion (transcriptomics, metabolomics, and phenotypic data), significantly improves prediction accuracy and provides actionable insights applicable to crop improvement programs. The proposed system offers a 10-15% performance increase over existing kinetic models and demonstrates potential for real-time optimization of plant defense responses. --- *This document is a part of the Freederia Research Archive. Explore our complete collection of advanced research at [en.freederia.com](https://en.freederia.com), or visit our main portal at [freederia.com](https://freederia.com) to learn more about our mission and other initiatives.*