Abstract
The dynamic temporal regulatory effects of microRNA are not well known. We introduce a technique for integrating miRNA and mRNA time series microarray data with known disease pathology. The integrated analysis includes identifying both mRNA and miRNA that are signi cantly similar to the quantitative pathology. Potential regulatory miRNA/mRNA target pairs are identi ed through databases of both predicted and validated pairs. Finally, potential target pairs are ltered by examining the second derivatives of the fold changes over time. Our system was used on genome-wide microarray expression data of mouse lungs (n = 160) following aspiration of multi-walled carbon nanotubes. This system shows promise of readily identifying miRNA for further study as potential biomarker use.