Did you profile miRNA expression in a tumor and a non-tumor control so you have a list of deferentially expressed miRNA?

The algorithms mentioned by others are all useful for predicting targets and I think the sites (multimir and others) that aggregate results from several algorithms are good for identifying candidate targets selected by multiple algorithms. Each algorithm uses somewhat different parameters or weightings so a consistent hit should be a good target to pursue.

Do you have gene expression data on your tumor as well? If not, you may be able to use online gene expression resources to narrow the targets for your tumor of interest.

You can use Diana miranda too

Hello

Discussion here will help you a lot :

https://www.researchgate.net/post/Using_Target_Scan_to_identify_miRNA_specific_to_the_gene_of_interest_how_do_you_select_the_specific_miRNA

also look at this link

Article Identifying miRNAs, targets and functions

Good Luck

I think that after finding the predicted target , we must examine each of top score for function in gene ontology

I highly recommend to use multiMir, a R programming based tool, which looks for your query among all available databases. In multimir, you can also search for your desired micro-RNA in a specific disease and vice versa.

Did you profile miRNA expression in a tumor and a non-tumor control so you have a list of deferentially expressed miRNA?

The algorithms mentioned by others are all useful for predicting targets and I think the sites (multimir and others) that aggregate results from several algorithms are good for identifying candidate targets selected by multiple algorithms. Each algorithm uses somewhat different parameters or weightings so a consistent hit should be a good target to pursue.

Do you have gene expression data on your tumor as well? If not, you may be able to use online gene expression resources to narrow the targets for your tumor of interest.

Hamed Hemati any reference is there ?