ITR: Understanding Stress Resistance Mechanisms in Plants: Multimodal Models Integrating Experimental Data, Databases, and the Literature

植物进化以适应各种环境压力，包括干旱、高温、寒冷、盐分、病原体和昆虫。对植物施加胁迫会导致基因组防御机制的改变。一些防御机制对多重胁迫(如干旱和盐分)的反应是共同的，而另一些机制则更具特异性。防御机制可以相互协作来对抗压力，也可以独立工作来修复压力造成的多种损害。这项研究的前提是，功能基因组和生物信息学方法结合干旱胁迫实验数据和来自多个生物信息源的信息可以阐明胁迫机制之间和内在的关系。该项目将在称为多模式模型的表示或模型中捕获这些关系。将被利用的生物信息来源包括(1)来自干旱胁迫实验的数据，特别是来自微阵列杂交的基因表达数据；(2)序列、蛋白质和其他数据库；以及(3)生物文献。多模式模型将代表生物知识和生物系统本身的这些多个方面：随时间的反应；亚细胞隔间的反应变化；不确定性(我们缺乏对细胞状态的完整了解)；以及由于生物数据和知识的激增而导致的生物信息的动态变化。这些模型很容易通过计算手段可视化、探索、分析和扩展。目前的干旱胁迫响应模型将通过项目网站提供。用于研究火炬松和拟南芥(生物研究的模式植物)干旱胁迫的微阵列实验将由Expresso系统设计、管理和分析，Expresso系统是一个用于实验设计、数据捕获和数据分析的微阵列实验管理系统。这项研究中使用的实验和计算方法将对生物学家使用微阵列技术和其他现代基因组学工具解决额外的复杂、相互关联的假设的能力产生影响。多模式网络将具有预测能力，这将使生物学家能够在实验之前通过计算探索假设，在假设的干旱胁迫条件下获得与各种干旱反应机制相关的概率估计，基于从实验中获得大量信息的估计可能性来决定未来的实验，并作为具有更多预测能力的数学模型的基础。加强对植物对干旱和其他胁迫反应的了解，最终将以更耐寒的作物和树木的形式惠及农业和林业。

Plants have evolved to cope with a variety of environmental stresses, including drought, heat, cold, salt, pathogens, and insects. The imposition of stress on a plant results in the marshaling of genomic defense mechanisms. Some defense mechanisms are common to the response to multiple stresses (e.g., drought and salt), while others are more specific. Defense mechanisms may interact collaboratively to combat a stress or may work independently to repair multiple kinds of damage inflicted by stress. This research proceeds on the premise that functional genomic and bioinformatics approaches together with data from drought stress experiments and information from multiple biological information sources can elucidate relationships among and within stress mechanisms. This project will capture these relationships in representations or models called multimodal models. Sources of biological information that will be utilized include (1) data from drought-stress experiments, especially gene expression data from microarray hybridizations; (2) sequence, protein, and other databases; and (3) the biological literature. Multimodal models will represent these multiple aspects of biological knowledge and of biological systems themselves: responses over time; response variation by subcellular compartments; uncertainty (our lack of complete knowledge of cell state); and the dynamic changes in biological information due to the boom in biological data and knowledge. These models are readily visualized, explored, analyzed, and extended via computational means. Current models for drought stress response will be available via the project web site.The microarray experiments for studying drought stress in loblolly pine and Arabidopsis thaliana (a model plant for biological research) will be designed, managed, and analyzed by the Expresso system, a microarray experiment management system for experimental design, data capture, and data analysis. The experimental and computational methods used in this research will have an impact on the ability of biologists to address additional complex, interrelated hypotheses using microarray technology and other tools of modern genomics. The multimodal networks will have predictive power that will enable biologists to explore hypotheses computationally in advance of experiments, to obtain estimates of probabilities associated with various drought response mechanisms given hypothesized drought stress conditions, to decide on future experiments based on the estimated likelihood of a large yield of information from the experiments, and to serve as the basis for mathematical models that have more quantitative predictive power. Enhanced understanding of responses to drought and other stresses in plants will ultimately benefit agriculture and forestry in the form of hardier crops and trees.