For example, searching for the potential targets of the 52 differentially expressed miRNAs using the TargetScan algorithm led to the identification of 11,031 putative conserved targets.
MiRNA targets were predicted using the current version (release 5.1) of the TargetScan algorithm (http://www.targetscan.org) as described previously [26], [27] (see [25] for a review).
We used the TargetScan algorithm [15] for our predictions due in part to our earlier successes in predicting target gene modulation.
Using the TargetScan algorithm [20] we selected four high scoring predicted target genes PTEN, SIRT1, SP1 and p300 to examine whether miR-22 affects their expression.
In addition, we investigated the number of microRNA binding sites predicted by the Targetscan algorithm [ 14].
Scanning for predicted microRNA binding sites was performed with the Targetscan algorithm [ 14].
1241 hits were found using the miRanda algorithm [ 54], whereas 353 targets were found using the TargetScan algorithm [ 12].
Putative binding sites were identified in the 3′UTR of differentially expressed hepatic genes under SNEB with the Targetscan algorithm.
The TargetScan algorithm was used to predict the biological targets of miRNAs with a stringency of 0.7.
The TargetScan algorithm was utilised to predict potential targets within these two groups for anti-correlated DE miRNAs.
