From model organisms to organismal models: visualizing complex genomic datasets

Abstract

Genome research is rapidly expanding from the characterization of linear information (DNA and protein molecules) to information that contains spatial and temporal aspects (for example gene expression patterns and proteomics data). The analysis of these complex data sets poses new challenges for bioinformatics. A major challenge is the integration of highly diverse data types, ranging from gene functions and gene expression patterns over protein modifications to metabolic networks. New technologies need to be developed to integrate these data and build multi-dimensional models of cells, tissues, organs and entire organisms that reflect the results of functional genomics studies. The visualization of these models will be crucial for the success of genome research.