It is important that you use only validated miRNA-mRNA interactions. There are databases of miRNA-mRNA interactions where the distinction between validated and predicted is made. So, use miRanda or Pictair or some other favorite miRNA database - or a combination of these - and select the validated interactions. Then, go onto Madhan's suggestion for teh pathway analysis.
Expression data. There is still not so much of these data for microRNAs as many would wish. An important paper has just been released on expression profiles of 863 microRNAs from 454 analyzed blood samples from individuals with lung cancer, prostate cancer, pancreatic ductal adenocarcinoma, melanoma, ovarian cancer, gastric tumors, Wilms tumor, pancreatic tumors, multiple sclerosis, chronic obstructive pulmonary disease (COPD), sarcoidosis, periodontitis, pancreatitis or acute myocardial infarction and from unaffected individuals (controls) (Keller, Meese et al 2011 Nature Methods, in press). While most would advocate that the microRNA and its target mRNA be co-expressed by cell type and by time, that may not necessarily be required. The HDL-cholesterol particle has been shown to transport microRNAs (Vickers, Remaley et al 2011 Nature Cell Biol 13:423-433) to it target tissues (those that take up HDL-C) and this may be a mechanism by which a microRNA can act at a distance, like a hormone.
Of course, you can scan GEO (NCBI) or ArrayExpress for microRNA expression sets - the 863 microRNAs mentioned above are in GEO. But it may be difficult to acquire from a public repository data taken under the precise conditions your research requires.
The second tool you mentioned still need the expression profile as the validation.The pathway level analysis however just get the enriched pathway for the predicted target genes. And I don't this method can provide a preciser prediction result for the miRNA-mRNA interactions.