The Cancer Genome Atlas(TCGA)(http://cancergenome.nih.gov) is a valuable data resource focused on an increasing number of well-characterized cancer genomes. In part, TCGA provides detailed information about cancer-dependent gene expression changes, including changes in the expression of transcription-regulating micro RNAs. We developed a web interface tool MMi RNA-Tar(http://bioinf1.indstate.edu/MMi RNA-Tar) that can calculate and plot the correlation of expression for m RNA micro RNA pairs across samples or over a time course for a list of pairs under different prediction confidence cutoff criteria. Prediction confidence was established by requiring that the proposed m RNA micro RNA pair appears in at least one of three target prediction databases: Target Profiler, Target Scan, or mi Randa. We have tested our MMi RNA-Tar tool through analyzing 53 tumor and 11 normal samples of bladder urothelial carcinoma(BLCA)datasets obtained from TCGA and identified 204 micro RNAs. These micro RNAs were correlated with the m RNAs of five previously-reported bladder cancer risk genes and these selected pairs exhibited correlations in opposite direction between the tumor and normal samples based on the customized cutoff criterion of prediction. Furthermore, we have identified additional 496 genes(830pairs) potentially targeted by 79 significant micro RNAs out of 204 using three cutoff criteria, i.e.,false discovery rate(FDR) < 0.1, opposite correlation coefficient between the tumor and normal samples, and predicted by at least one of three target prediction databases. Therefore, MMi RNATar provides researchers a convenient tool to visualize the co-relationship between micro RNAs and m RNAs and to predict their targeting relationship. We believe that correlating expression profiles for micro RNAs and m RNAs offers a complementary approach for elucidating their interactions. The Cancer Genome Atlas (TCGA) (http://cancergenome.nih.gov) is a valuable data resource focused on an increasing number of well-characterized cancer genomes. In part, TCGA provides detailed information about cancer-dependent gene expression changes, including changes in the expression of transcription-regulating micro RNAs. We developed a web interface tool MMi RNA-Tar (http://bioinf1.indstate.edu/MMi RNA-Tar) that can calculate and plot the correlation of expression for m RNA microRNA pairs across samples or over a time course for a list of pairs under different prediction confidence cutoff criteria. Prediction confidence was established by requiring that the proposed m RNA micro RNA pair appears in at least one of three target prediction databases: Target Profiler, Target Scan, or mi Randa. We have tested our MMi RNA-Tar tool through analyzing 53 tumor and 11 normal samples of bladder urothelial carcinoma (BLCA) datasets from TCGA and identified 204 micro RNAs. These micro RNAs were correlated with the m RNAs of five previously-reported bladder cancer risk genes and these selected pairs exhibiting correlations in the opposite direction between the tumor and normal samples based on the customized cutoff criterion of prediction. ie, false discovery rate (FDR) <0.1, opposite correlation coefficient between the tumor and normal samples, and predicted by at least one of three target prediction databases. Thus, MMi RNATar provides researchers a convenient tool to visualize the co-relationship between micro RNAs and m RNAs and to predict their targeting relationship. We believe that correlating expression profiles for micro RNAs and m RNAs offers a complementary approach for elucidating their interactions.