VISUALIZATION

BLACKSBURG, VA -- The Virginia Bioinformatics Institute (VBI) at Virginia Tech has received a $289,429, 10-month contract from Phenomenome Discoveries, Inc. to collaborate with Phenomenome to develop innovative software that will allow scientists to visualize metabolomics data. Metabolomics is the study of changes in the expression of a large number of small organic molecules (such as sugars and vitamins) in biological systems. It complements study of the genome by providing objective measurements of an organism's state. It can be used to compare, at a very fine level, the differences between different mutants to find out the function of the mutated genes. The bioinformatics software developed under this collaboration will organize and display the expression level of large numbers of the small organic molecules in ways that assist scientists with its interpretation, explains Pedro Mendes, principal investigator of the project at VBI. The software will also combine data from gene and protein expression in the same view. "This will further help the scientist pinpoint the exact function of genes and proteins by putting them in the context of the underlying biochemistry," he says. Mendes leads a research group dedicated to modeling biochemical networks. The group is already studying algorithms to analyze gene networks and is developing simulation software for high-performance computers. He says of the collaboration with Phenomenome, "We have for some time been interested in combining metabolomics data with gene expression and proteomics. Metabolomics will aid in revealing how genotypes are associated with phenotypes and make large-scale computer simulations of cells. This collaboration with Phenomenome will help us test our analysis methods with the best technology for measuring the metabolome". Dayan Goodenowe, president and CEO of Phenomenome, stated, "We are very excited about working with the Virginia Bioinformatics Institute. Of the bioinformatics research groups we investigated, VBI has the right mix of biology and computer science to be able to integrate and reduce vast amounts of genomic and metabolomic data into a format that regular bench biologists can easily use to interpret the results of their experiments. The tools that will be developed as part of this collaboration mark the first real step in functional genomics research that goes beyond the isolated and static generation of data to begin the process of observing and understanding biological systems from a global and dynamic perspective."