ITR: Display of High-Dimensional Metabolic Networks in the C6 Immersive Virtual Reality System

正在为细菌、植物和动物系统生成多维全基因组基因表达谱数据集。这些复杂的数据揭示了控制细胞代谢的相互作用的代谢途径。最终，了解这些途径将提高我们预测特定药物对人体代谢的影响，单个基因对种子成分变化的后果，或癌症前细胞中特定突变的影响的能力。该项目的目标是开发一个独特的集成信息工作空间，使用三维图形、物理细胞模型和用于详细文本信息的无线手持设备来显示异构生物信息。这个项目将使用各种程度的沉浸，从桌面设置到C6沉浸式虚拟环境。将开发两种实验应用。首先，一个代谢网络的交互式可视化原型，光合作用的卡尔文循环，将被用来创建一个生化途径的活生生的动态例子，供K-12学生探索。这条道路将通过一款电脑游戏变得生动起来，学生们可以按照自己的节奏进行探索，如果取得了特殊的成就，比如组合合适的分子，就会得到奖励。复杂的概念，如化学，光能和热能的转换，代谢通量，生物化学成分的使用和合成都可以通过这一途径来说明。其次，将三维可视化技术应用于遗传模式植物拟南芥中乙酰辅酶a代谢网络的分析。这种可视化将与在该途径的特定步骤中从一组基因突变中获取的复杂数据集集成。该项目的研究目标是探索与三维图形交互的方法，以及整合不同模型进行数据探索。该项目将由具有生物学、生物信息学和计算机工程专业知识的跨学科研究小组执行，他们将应用图论、沉浸式软件可视化和模糊逻辑的元素来解决代谢网络可视化问题。

Multidimensional genome-wide gene expression profiling datasets are being generated for bacterial, plant and animal systems. This complex data reveals the interacting metabolic pathways that control cell metabolism. Ultimately, understanding these pathways will increase our ability to predict the effects of a given drug on human metabolism, the consequences of changes in a single gene on the composition of a seed, or the effect of a given mutation in a pre-cancer cell. The goal of this project is to develop a unique integrated information workspace that displays heterogeneous biological information using three-dimensional graphs, physical cell models, and wireless handheld devices for detailed textual information. This project will use a variety of levels of immersion, from desktop settings to the C6 immersive virtual environment. Two experimental applications will be developed. First, a prototype interactive visualization of a metabolic network, the Calvin cycle of photosynthesis, will be used to create a living dynamic example of a biochemical pathway for K-12 students to explore. The pathway will be brought alive by a computer game that students explore at their own pace, with rewards for particular achievements such as combining the proper molecules. Complex concepts such as the conversion of chemical, light and heat energy, metabolic flux, use and synthesis of chemical constituents of living organisms can all be illustrated through this pathway. Secondly, three-dimensional visualization will be applied to the analysis of the acetyl-CoA metabolic network in the genetic model-plant Arabidopsis. This visualization will be integrated with complex datasets taken from a group of genetic mutants in specific steps in this pathway. The research objectives of this project are to explore methods for interaction with three-dimensional graphs and the integration of different models for data exploration. The project will be performed by an interdisciplinary group of investigators with expertise in biology, bioinformatics, and computer engineering, who will apply elements of graph theory, immersive software visualization, and fuzzy logic to the problem of metabolic network visualization.