MicroRNA is small 22 nucleotides long non-coding RNA which regulates genesby targeting mRNA especially the 3 UTR region. Identification of miRNAs and theirtargets by laboratory experiment has had limited success especially for lowly expressedtherefore computational prediction approaches are needed. In this study groupingtechnique for miRNA precursor prediction is introduced. Compared with globalalignment, grouping miRNA by classes yield a better sensitivity with very highspecificity for pre-miRNA prediction even when a simple positional based secondary andprimary structure alignment are used.The program TarSpec was developed to predict miR-1a and miR-124 targetsbased on common features of miRNA and target binding characteristics observed fromalignment between miRNA and the 3UTR targets. TarSpec obtained 78% and 77%sensitivity for miR-1a and Mir-124 targets, and 98% specificity for both. TarSpec wasused to scan the Platypus 3UTR regions. This approach predicted 734 novel potentialtarget of miR-1a in Platypus 3UTR regions where 98 of them are in the well annotatedchromosomal region and 124 novel potential target of miR-124 where 32 of them are inthe well annotated chromosomal region.Some miRNAs are derivations of transposable elements (TE). In human these TEderived miRNAs have a potential to regulate thousands of human genes. Therefore TEsas potential miRNA targets were investigated using an L2 derived miRNA miR-28. Threedifferent miRNA target prediction programs miTarget, miRanda, and RNAhybrid wereused to predict a potential miRNA-28 targets in human L2 transposable elements. It wasdemonstrated that the human TE is also a potential target for miRNAs; subsequently1,094 of potential target were predicted in human L2.