Computational solutions enable plant scientists to model protein-mediated stress responses and characterize novel gene functions that coordinate responses to a variety of abiotic stress conditions. Recently, density functional theory was used to study proteins active sites and elucidate enzyme conversion mechanisms involved in iron deficiency responsive signaling pathways. Computational approaches for protein homology modeling and the kinetic modeling of signaling pathways have also resolved the identity and function in proteins involved in iron deficiency signaling pathways. Significant changes in gene relationships under other stress conditions, such as heat or drought stress, have been recently identified using differential network analysis, suggesting that stress tolerance is achieved through asynchronous control. Moreover, the increasing development and use of statistical modeling and systematic modeling of transcriptomic data have provided significant insight into the gene regulatory mechanisms associated with abiotic stress responses. These types of in silico approaches have facilitated the plant science community’s future goals of developing multi-scale models of responses to iron deficiency stress and other abiotic stress conditions.

计算解决方案使植物科学家能够对蛋白质介导的胁迫响应进行建模，并表征可协调对各种非生物胁迫条件响应的新型基因功能。最近，密度泛函理论用于研究蛋白质活性位点，并阐明涉及铁缺乏响应信号通路的酶转化机制。蛋白质同源性建模和信号传导途径动力学模型的计算方法也解决了铁缺乏信号传导途径中涉及的蛋白质的身份和功能。最近，利用差分网络分析已经发现了在其他胁迫条件下，如高温或干旱胁迫，基因关系的显着变化，这表明通过异步控制可以实现胁迫耐受性。此外，转录组数据的统计建模和系统建模的日益发展和使用，为与非生物胁迫反应相关的基因调控机制提供了重要见识。这些类型的计算机方法已经促进了植物科学界的未来目标，即开发针对铁缺乏胁迫和其他非生物胁迫条件的多尺度模型。