The volume of information derived from postgenomic technologies is increasing rapidly. As a result, novel computational methods are needed for the analysis of and knowledge discovery in the massive datasets produced by these new technologies. We are working on biological data integration and discovery of a priori unknown relationships between gene expression and metabolite variations, including transcriptomic and metabolomic profiles from introgression lines of tomato fruits. Download the *omeSOM software, a tool designed for data mining of metabolic and transcriptional datasets.
*omeSOMweb is a data mining tool that can be used to integrate and find groups within different types of measures. It allows for exploratory analysis and clustering of any kind of data in order to discover novel data relationships and knowledge. *omeSOMweb can be accessed for a free trial through a simple web interface.
Contact: G. Stegmayer