Plant & Animal Genomes XI Conference Plant & Animal Genomes XI ConferenceJanuary 11-15, 2003
Town & Country Convention Center
San Diego, CA
Workshop: Arabidopsis
MetNet (www.botany.iastate.edu/~mash/metnetex/metabolicnetex.html) is in-development, publicly available software for analysis of genome-wide mRNA, protein, and metabolite profiling data. The software is designed to enable the biologist to visualize, statistically analyze, and model a metabolic and regulatory network map of Arabidopsis together with gene expression profiling data using interactive graph display modules. It contains a Java TM interface to an interactions database (MetNetDB) containing information on regulatory and metabolic interactions derived from WEB databases (TAIR, KEGG, BRENDA) and expert biologist input. The MetNetDB map, together with experimental profiling data, can be interactively visualized, statistically analyzed, and modeled. Data will be viewed using a multivariate graphic capability based on the statistical data visualization software GGobi. GGobi represents the current state of the art interactive and dynamic visual data mining tools that support exploratory analyses. Users can highlight different parts of the metabolic network, and see the relevant expression data highlighted in other data plots. Multi-dimensional expression data can be projected in two or three dimensions; the user can watch the data as it rotates through different dimensions, and stop it at any point that gives useful information. Thus, the biologist can conduct statistical analysis of the data, and superimpose it on the visualization. MANET, which can handle continuous as well as categorical data and offers tools for basic statistical inferences in an interactive environment, will be incorporated. This provides an intuitive way to identify genes with gene expressions that show trends over time or particular pattern or are similar to other genes. Statistical analysis applications in R for gene expression profiling data analysis are being incorporated into GGOBI. Metabolic or regulatory flow in the network can be modeled via FCModeler, a graph visualization and modeling tool within MetNet. FCModeler captures known metabolic information and expert knowledge of biologists, as input from MetNetDB, in a graphical form. This graph visualization enables the user to interact with dynamic information spaces. The graph display interface supports several forms of user interaction with the view of the network graph. Networks can be modeled and the results interpreted using simple fuzzy cognitive maps. FCModeler is intended to capture the intuitions of biologists, develop and evaluate hypotheses, and provide a modeling framework for assessing the large amounts of data captured by high-throughput gene expression experiments. FCModeler and MetNetDB is currently being extended to virtual reality. MetNet is designed to provide a framework for the formulation of testable hypotheses regarding the function of specific genes, and in the long term provide the basis for identification of metabolic and regulatory networks that control plant composition and development.