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

植物已经进化到能够应对各种环境压力，包括干旱、热、冷、盐、病原体和昆虫。施加在植物上的压力导致了基因组防御机制的编组。一些防御机制是对多种压力（如干旱和盐）的共同反应，而其他防御机制则更为具体。防御机制可以协同作用来对抗压力，也可以独立工作来修复压力造成的多种损害。本研究的前提是功能基因组学和生物信息学方法，结合干旱胁迫实验数据和多种生物信息源的信息，可以阐明胁迫机制之间和内部的关系。该项目将在称为多模态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、蛋白质等数据库；(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：随时间的反应；亚细胞区室的反应差异；不确定性（我们对细胞状态缺乏完整的了解）；由于生物数据和知识的激增，生物信息发生了动态变化。这些模型很容易通过计算手段可视化、探索、分析和扩展。目前的干旱应激反应模型将通过该项目的网站提供。研究干旱胁迫的火炬松和拟南芥（生物学研究的模式植物）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其他复杂的、相互关联的假设的能力产生影响。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，在假设的干旱胁迫条件下获得与各种干旱响应机制相关的概率估计，根据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以更耐寒的作物和树木的形式使农业和林业受益。

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.