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

植物已经进化到可以科普各种环境压力，包括干旱、高温、寒冷、盐、病原体和昆虫。对植物施加压力导致基因组防御机制的排列。一些防御机制是共同的反应，以多种压力（例如，干旱和盐），而其他更具体。 防御机制可以相互协作以对抗压力，也可以独立工作以修复压力造成的多种损伤。 这项研究的前提是，功能基因组学和生物信息学方法，从干旱胁迫实验和信息的数据，从多个生物信息源可以阐明胁迫机制之间和内部的关系。 这个项目将捕捉这些关系的表示或模型称为多模态模型。 将利用的生物信息来源包括：（1）干旱胁迫实验数据，特别是微阵列杂交的基因表达数据;（2）序列、蛋白质和其他数据库;（3）生物学文献。 多模态模型将代表生物学知识和生物系统本身的这些多个方面：随时间的响应;亚细胞区室的响应变化;不确定性（我们缺乏对细胞状态的完整知识）;以及由于生物数据和知识的繁荣而引起的生物信息的动态变化。这些模型很容易可视化，探索，分析，并通过计算手段扩展。 干旱胁迫反应的现有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Experiment系统设计、管理和分析，Experiment系统是一个用于实验设计、数据采集和数据分析的微阵列实验管理系统。本研究中使用的实验和计算方法将影响生物学家使用微阵列技术和现代基因组学的其他工具来解决其他复杂的、相互关联的假设的能力。多模态网络将具有预测能力，使生物学家能够在实验之前通过计算探索假设，以获得与假设的干旱胁迫条件下的各种干旱响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，并作为具有更定量预测能力的数学模型的基础。 加强对植物对干旱和其他压力的反应的了解，最终将有利于农业和林业，使作物和树木更耐寒。

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.