Micro RNAs, by regulating the expression of hundreds of target genes, play critical roles in developmental biology and the etiology of numerous diseases, including cancer. As vast amounts of micro RNA expression profile data are now publicly available, the integration of those data sets with gene expression profiles represents an extremely active area of life science research. However, the ability to conduct genome-wide micro RNA-mRNA (gene) integration currently requires sophisticated, high-end informatics tools, significant expertise in bioinformatics and computer science to carry out the complex integration analysis. In addition, increased computing infrastructure capabilities are essential in order to accommodate large data sets. In this study, we have extending BioVLAB cloud workbench to develop an environment for the integrated analysis of micro RNA and mRNA expression data, named BioVLAB-MMIA. The workbench facilitates computations on the Amazon EC2 and S3 resources orchestrated by XBaya Workflow Suite. The advantages of BioVLAB-MMIA over the web-based MMIA system include: 1) readily expanded as new computational tools become available, 2) easily modifiable by re-configuring graphic icons in the workflow, 3) on-demand cloud computing resources can be used on an "as needed" basis, 4) distributed orchestration supports complex and long running workflows asynchronously.