Abstract
MicroRNA expression profiles can improve classification, diagnosis, and prognostic
information of malignancies, including lung cancer. In this paper, we undertook to develop
a miRNA-mRNA network and uncover unique growth suppressive miRNAs in lung cancer using
microarray data. The miRNA-mRNA network was developed based on a bipartite graph theory
approach, and a number of miRNA-mRNA modules have been identified to mine associations
between miRNAs and mRNAs. From the network, we identified totally 29 protective miRNA-mRNA
regulatory modules, since we restricted our search to protective miRNAs. Subsequently we
analyzed the pathways for the target genes in the protective miRNA-mRNA modules using
Pathway-Express. The miRNA-mRNA network efficiently detects hub mRNAs deregulated by the
protective miRNAs and identifies cancer specific miRNAs in lung cancer. From the pathway
analysis results, the
