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

Iowa State University, Ames IA

Investigators

Abstract

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.