Asbtract:  MicroRNAs (miRNAs) are short non-coding RNA molecules that act as post-transcriptional regulators of mRNA. Since miRNAs can act as oncogenes or tumour suppressors, an understanding of their regulatory mechanism could provide new insights into cancer and other diseases. The first part of the talk, I will discuss an odds-ratio (OR) statistic for identification of regulatory miRNAs. It is based on integrative analysis of miRNA and mRNA microarray data and is suitable for short time course microarray data. The OR-statistic can be used for (i) identification of miRNAs with regulatory potential, (ii) identification of miRNA-target mRNA pairs, and (iii) identification of time lags between changes in miRNA expression and those of its target mRNAs. We applied the OR-statistic to a cancer data set and identified a small set of miRNAs that were negatively correlated to mRNAs.
One major challenge in the identification of target-mRNAs is the need to accommodate the many-to-many mapping between miRNAs and mRNAs: a miRNA can target hundreds of mRNAs and several miRNAs target a single mRNA. In this talk, I will discuss a statistical approach for determining the miRNA regulatory modules and their target-mRNA modules. A simulation study is performed to determine whether the majority of mRNAs in a given module are indeed targeted by a small set of miRNAs. The preliminary results are encouraging even for low accuracy of predicted miRNA targets.
Joint work with Vivek Jayaswal