Interaction Based Functional Clustering of Genomic Data

We present the first report on Granger causality based detection of functional modules from temporal gene expression data. The approach uses temporal causal relationships shared between pair of genes to derive a connection matrix, which is further analyzed using graph-theoretic techniques. The approach is evaluated against a synthesized dataset and a real biological dataset obtained for Arabidopsis thaliana. We show the effectiveness of our approach by analyzing the results using the existing biological literature.