System for Automatically Inferring a Genetic Netwerk from Expression Profiles

A system is constructed to automatically infer a genetic network byapplication of graphical Gaussian modeling to the expression profiledata. Our system is composed of two parts: one part is automaticdetermination of cluster boundaries of profiles in hierarchicalclustering, and another part is inference of a genetic network byapplication of graphical Gaussian modeling to the clustered profiles.Since thousands of or tens of thousands of gene expression profiles aremeasured under only one hundred conditions, the profiles naturally showsome similar patterns. Therefore, a preprocessing for systematicallyclustering the profiles is prerequisite to infer the relationship betweenthe genes. For this purpose, a method for automatic determination ofcluster boundaries is newly developed without any biological knowledgeand any additional analyses. Then, the profiles for each cluster areanalyzed by graphical Gaussian modeling to infer the relationship betweenthe clusters. Thus, our system automatically provides a graph betweenclusters only by input the profile data. The performance of the presentsystem is validated by 2467 profiles from yeast genes. The clusters andthe genetic network obtained by our system are discussed in terms of thegene function and the known regulatory relationship between genes.